The document discusses research challenges for trust, security and privacy in 6G networks. It identifies six main challenges: 1) Inherited and novel threats posed by the increased scale and diversity of 6G devices and systems. 2) Establishing end-to-end trust in 6G to ensure network-based information technology can be trusted. 3) Adopting post-quantum cryptography and revising security architectures for 6G. 4) Addressing machine learning as both a tool and risk for softwarized 6G security. 5) Developing physical layer security techniques for 6G. 6) Addressing privacy as an exploited resource in the highly connected world of 6G. The white paper provides an overview of these challenges and calls
The Future of 6G Wireless Networks Opportunities, Requirements, and Challenge...ijtsrd
The evolution of wireless communication has led to the rapid advancement of generations of networks, from 1G to the current 5G standard. As society becomes more interconnected and reliant on wireless technologies, the demand for faster, more reliable, and versatile networks continues to grow. This paper explores the potential landscape of 6G wireless networks, delving into the opportunities they present, the essential requirements they must fulfil, and the significant challenges they must overcome. Drawing insights from current technological trends and projecting into the future, this paper aims to provide a comprehensive overview of what the next generation of wireless networks might require. 6G will human interaction of DARQ. Manish Verma "The Future of 6G Wireless Networks: Opportunities, Requirements, and Challenges: A ChatGPT Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-5 , October 2023, URL: https://www.ijtsrd.com/papers/ijtsrd60072.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/60072/the-future-of-6g-wireless-networks-opportunities-requirements-and-challenges-a-chatgpt-analysis/manish-verma
Department of Homeland Security (DHS) | Cybersecurity and Infrastructure Security Agency
The 5G Strategy for 2020 is designed for Ensuring the Security and Resilience of 5G Infrastructure In the United States of America.
The Department of Homeland Security (DHS) Cybersecurity and Infrastructure Security Agency (CISA) leads 5G risk management efforts so the United States can fully benefit from all the advantages 5G connectivity promises to bring. In support of CISA’s operational priority to secure 5G, as outlined in the CISA Strategic Intent, the CISA 5G Strategy establishes five strategic initiatives that stem from the four lines of effort defined in the National Strategy to Secure 5G.
Guided by three core competencies: Risk Management, Stakeholder Engagement, and Technical Assistance, these initiatives include associated objectives to ensure there are policy, legal, security, and safety frameworks in place to fully leverage 5G technology while managing its significant risks. With the support of CISA and its partners, the CISA 5G Strategy seeks to advance the development and deployment of a secure and resilient 5G infrastructure, one that enables enhanced national security, technological innovation, and economic opportunity for the United States and its allied partners.
Neil McDonnell and the GovCon Chamber of Commerce is bringing this document to industry as part of our commitment to find and share information that will help small businesses better prepare to serve the federal market.
IRJET - A Study on Smart Way for Securing IoT DevicesIRJET Journal
This document discusses security challenges with Internet of Things (IoT) devices and potential solutions. It first describes how the widespread use of IoT devices has introduced new security issues as hackers can easily access information without proper security measures. The document then reviews 10 different papers on techniques used to enhance security for IoT devices, including security models, access mechanisms, encryption, authentication, and more. It evaluates various technologies like RFID, sensors, artificial intelligence. Finally, the document concludes that providing a security-enabled model to secure end-to-end communication is the best short-term solution, while various approaches are needed to address different security issues in IoT.
The document discusses several limitations of IoT-enabled automation solutions:
1. Cybersecurity and privacy concerns are significant as more devices are connected and hackers can more easily access building functions by exploiting vulnerabilities.
2. Lack of integration and interoperability standards means buildings use multiple incompatible protocols, increasing costs.
3. Data capturing and processing has limitations due to the expense of comprehensive sensor deployment and expert analysis needed to derive value from data.
Lightweight Cryptography Algorithms for Security of IoT Devices: A SurveyIRJET Journal
This document discusses lightweight cryptography algorithms for security in Internet of Things (IoT) devices. It provides an overview of IoT architecture and applications. It then discusses the need for lightweight cryptography due to constraints of IoT devices. Various lightweight cryptography algorithms are described, including symmetric key and asymmetric key algorithms. Challenges of lightweight cryptography are also outlined. Related work studying lightweight cryptography algorithms for IoT security is reviewed. The document analyzes and compares various lightweight cryptography algorithms suitable for securing resource-constrained IoT devices.
Blockchain based News Application to combat Fake newsIRJET Journal
This document proposes a blockchain-based news application to combat fake news. It discusses how a decentralized network of news agencies, editors, and third-party fact checkers could work together on a blockchain to create and verify news stories. The proposed system would allow news to be tracked from creation to publication, increasing transparency. It aims to make the news creation and verification process more reliable and trustworthy through the use of blockchain technology.
- The document discusses securing the Internet of Things (IoT), where every physical object has a virtual presence and can interact over the Internet.
- Several obstacles stand in the way of fulfilling the IoT vision, including security issues as the Internet and its users are already under attack and constrained IoT devices are vulnerable.
- To implement IoT security successfully, researchers must understand the IoT conceptually, evaluate current Internet security, and develop solutions that can reasonably assure a secure IoT.
In the past decade, internet of things IoT has been a focus of research. It makes more intelligent to core element of modern world such as hospitals, cities, organizations, and buildings. Usually, IoT has four major components including sensing, information processing, applications and services, heterogeneous access and additional components e.g. Security and privacy. In this paper, we are presenting security perspective from the perspective of layers that comprises IoT. In this we focus on the overview of IoT security perspective. Sunilkumar Malge | Pallavi Singh ""Internet of Things (IoT): Security Perspective"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd24010.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/24010/internet-of-things-iot-security-perspective/sunilkumar-malge
The Future of 6G Wireless Networks Opportunities, Requirements, and Challenge...ijtsrd
The evolution of wireless communication has led to the rapid advancement of generations of networks, from 1G to the current 5G standard. As society becomes more interconnected and reliant on wireless technologies, the demand for faster, more reliable, and versatile networks continues to grow. This paper explores the potential landscape of 6G wireless networks, delving into the opportunities they present, the essential requirements they must fulfil, and the significant challenges they must overcome. Drawing insights from current technological trends and projecting into the future, this paper aims to provide a comprehensive overview of what the next generation of wireless networks might require. 6G will human interaction of DARQ. Manish Verma "The Future of 6G Wireless Networks: Opportunities, Requirements, and Challenges: A ChatGPT Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-5 , October 2023, URL: https://www.ijtsrd.com/papers/ijtsrd60072.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/60072/the-future-of-6g-wireless-networks-opportunities-requirements-and-challenges-a-chatgpt-analysis/manish-verma
Department of Homeland Security (DHS) | Cybersecurity and Infrastructure Security Agency
The 5G Strategy for 2020 is designed for Ensuring the Security and Resilience of 5G Infrastructure In the United States of America.
The Department of Homeland Security (DHS) Cybersecurity and Infrastructure Security Agency (CISA) leads 5G risk management efforts so the United States can fully benefit from all the advantages 5G connectivity promises to bring. In support of CISA’s operational priority to secure 5G, as outlined in the CISA Strategic Intent, the CISA 5G Strategy establishes five strategic initiatives that stem from the four lines of effort defined in the National Strategy to Secure 5G.
Guided by three core competencies: Risk Management, Stakeholder Engagement, and Technical Assistance, these initiatives include associated objectives to ensure there are policy, legal, security, and safety frameworks in place to fully leverage 5G technology while managing its significant risks. With the support of CISA and its partners, the CISA 5G Strategy seeks to advance the development and deployment of a secure and resilient 5G infrastructure, one that enables enhanced national security, technological innovation, and economic opportunity for the United States and its allied partners.
Neil McDonnell and the GovCon Chamber of Commerce is bringing this document to industry as part of our commitment to find and share information that will help small businesses better prepare to serve the federal market.
IRJET - A Study on Smart Way for Securing IoT DevicesIRJET Journal
This document discusses security challenges with Internet of Things (IoT) devices and potential solutions. It first describes how the widespread use of IoT devices has introduced new security issues as hackers can easily access information without proper security measures. The document then reviews 10 different papers on techniques used to enhance security for IoT devices, including security models, access mechanisms, encryption, authentication, and more. It evaluates various technologies like RFID, sensors, artificial intelligence. Finally, the document concludes that providing a security-enabled model to secure end-to-end communication is the best short-term solution, while various approaches are needed to address different security issues in IoT.
The document discusses several limitations of IoT-enabled automation solutions:
1. Cybersecurity and privacy concerns are significant as more devices are connected and hackers can more easily access building functions by exploiting vulnerabilities.
2. Lack of integration and interoperability standards means buildings use multiple incompatible protocols, increasing costs.
3. Data capturing and processing has limitations due to the expense of comprehensive sensor deployment and expert analysis needed to derive value from data.
Lightweight Cryptography Algorithms for Security of IoT Devices: A SurveyIRJET Journal
This document discusses lightweight cryptography algorithms for security in Internet of Things (IoT) devices. It provides an overview of IoT architecture and applications. It then discusses the need for lightweight cryptography due to constraints of IoT devices. Various lightweight cryptography algorithms are described, including symmetric key and asymmetric key algorithms. Challenges of lightweight cryptography are also outlined. Related work studying lightweight cryptography algorithms for IoT security is reviewed. The document analyzes and compares various lightweight cryptography algorithms suitable for securing resource-constrained IoT devices.
Blockchain based News Application to combat Fake newsIRJET Journal
This document proposes a blockchain-based news application to combat fake news. It discusses how a decentralized network of news agencies, editors, and third-party fact checkers could work together on a blockchain to create and verify news stories. The proposed system would allow news to be tracked from creation to publication, increasing transparency. It aims to make the news creation and verification process more reliable and trustworthy through the use of blockchain technology.
- The document discusses securing the Internet of Things (IoT), where every physical object has a virtual presence and can interact over the Internet.
- Several obstacles stand in the way of fulfilling the IoT vision, including security issues as the Internet and its users are already under attack and constrained IoT devices are vulnerable.
- To implement IoT security successfully, researchers must understand the IoT conceptually, evaluate current Internet security, and develop solutions that can reasonably assure a secure IoT.
In the past decade, internet of things IoT has been a focus of research. It makes more intelligent to core element of modern world such as hospitals, cities, organizations, and buildings. Usually, IoT has four major components including sensing, information processing, applications and services, heterogeneous access and additional components e.g. Security and privacy. In this paper, we are presenting security perspective from the perspective of layers that comprises IoT. In this we focus on the overview of IoT security perspective. Sunilkumar Malge | Pallavi Singh ""Internet of Things (IoT): Security Perspective"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd24010.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/24010/internet-of-things-iot-security-perspective/sunilkumar-malge
the world of technology is changing at an unprecedented pace, and th.docxpelise1
the world of technology is changing at an unprecedented pace, and these changes represent business opportunities as well as challenges. Mass connectivity and faster speeds create opportunities for businesses to network more devices, complete more transactions, and enhance transaction quality. Internet Protocol version 6 (IPv6) and Internet of things (IoT) are two such technologies that represent significant opportunities for strategic cybersecurity technology professionals to create lasting value for their organizations.
IoT is the phenomenon of connecting devices used in everyday life. It provides an interactive environment of human users and a myriad of devices in a global information highway, always on and always able to provide information. IoT connections happen among many types of devices — sensors, embedded technologies, machines, appliances, smart phones — all connected through wired and wireless networks.
Cloud architectures such as software as a service have allowed for big data analytics and improved areas such as automated manufacturing. Data and real-time analytics are now available to workers through wearables and mobile devices.
Such pervasive proliferation of IoT devices gives hackers avenues to gain access to personal data and financial information and increases the complexity of data protection. Given the increased risks of data breaches, newer techniques in data loss prevention should be examined.
Increased bandwidth and increased levels of interconnectivity have allowed data to become dispersed, creating issues for big data integrity. In such a world, even the financial transactions of the future are likely to be different — Bitcoin and digital currency may replace a large portion of future financial transactions.
To survive and thrive, organizational technology strategists must develop appropriate technology road maps. These strategists must consider appropriate function, protection, and tamper-proofing of these new communications and transactions.
It will be impossible to protect data by merely concentrating on protecting repositories such as networks or endpoints. Cybersecurity strategists have to concentrate on protecting the data themselves. They will need to ensure that the data are protected no matter where they reside.:
Step2
Select Devices and Technologies
By now, you have an idea of your team members and your role on the team project. Now, it's time to get the details about the devices and technologies needed to be included in the Strategic Technology Plan for Data Loss Prevention.
You should limit the scope of this project by selecting a set of devices and technologies which are most appropriate for data loss prevention for your business mission and future success. Based on your prior knowledge of your company and based on the project roles you agreed upon in the previous step, perform some independent research on the following topics and identify a set of devices and technologies that you propose for.
6G Security Challenges And Potential SolutionsKristen Carter
This document discusses security challenges and potential solutions for 6G networks. It begins by outlining new 6G requirements like enhanced ultra-reliable low latency communication that will impact how security is implemented. It then describes new elements of the 6G architecture like intelligent radio and edge intelligence that may introduce new security threats. Next, it examines new applications in 6G like connected autonomous vehicles and how they have varying security needs. It concludes by surveying the security threats posed by key 6G technologies such as artificial intelligence, distributed ledger technology, quantum communication and terahertz bands, and potential solutions to address these threats.
6G Security Challenges And Potential SolutionsWendy Berg
The document discusses security challenges and potential solutions for 6G networks. It outlines how 6G requirements like high bandwidth, low latency, and massive device connectivity will impact security. New 6G technologies like edge intelligence, distributed AI, and quantum communication introduce new attack surfaces. The document surveys security challenges from the 6G architecture, requirements, and applications. It also discusses potential security solutions using technologies like distributed ledger, physical layer security, and quantum security.
Design of a Hybrid Authentication Technique for User and Device Authenticatio...IRJET Journal
The document proposes a hybrid authentication technique using blockchain authentication and artificial intelligence for user and device authentication in an integrated Internet of Things (IoT) environment. It discusses challenges with IoT security and reviews existing literature on blockchain and AI approaches for IoT authentication. The proposed technique aims to create a decentralized authentication system using a blockchain to store authentication records that are then used to train a neural network model. This trained model can authenticate new users and devices in the IoT network. The document outlines the objectives, methodology, and potential benefits of the proposed hybrid authentication approach for improving IoT security.
5G Drones with 5G Gaming and Application of 5G in Other Industries A ChatGPT ...ijtsrd
This paper explores the integration of 5G drones with 5G gaming and the application of 5G in various industries. The integration of 5G drones and gaming opens up new possibilities for immersive experiences within the met averse, enabling enhanced realism, aerial exploration, multiplayer aerial combat, and live event streaming. Additionally, the application of 5G in industries such as entertainment, agriculture, construction, logistics, public safety, healthcare, and more, brings significant benefits and advancements. 5G enables faster data transfer, low latency, and massive connectivity, empowering industries to optimize processes, enhance productivity, and deliver innovative services. The paper highlights the transformative impact of these technologies in different sectors, showcasing how they can revolutionize entertainment, improve efficiency, enable remote operations, and drive sustainable practices. Overall, the integration of 5G drones with 5G gaming and the application of 5G in various industries present exciting opportunities for innovation and progress. Manish Verma "5G Drones with 5G Gaming and Application of 5G in Other Industries: A ChatGPT Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd56341.pdf Paper URL: https://www.ijtsrd.com.com/computer-science/artificial-intelligence/56341/5g-drones-with-5g-gaming-and-application-of-5g-in-other-industries-a-chatgpt-analysis/manish-verma
In the past decade, internet of things (IoT) has been a
focus of research. Security and privacy are the key issues for IoT
applications, and still face some enormous challenges. In order to
facilitate this emerging domain, we in brief review the research
progress of IoT, and pay attention to the security. By means of
deeply analyzing the security architecture and features, the
security requirements are given. On the basis of these, we discuss
the research status of key technologies including encryption
mechanism, communication security, protecting sensor data and
cryptographic algorithms, and briefly outline the challenges.
Dissertations are among the most important pieces of work which students complete at university. And they allow you to work individually and on something that truly attracts you. Computer science is a hot field for researchers. Many topic ideas can be generated for a dissertation in this special branch of engineering.
Ph.D. Assistance serves as an external mentor to brainstorm your idea and translate that into a research model. Hiring a mentor or tutor is common and therefore let your research committee know about the same. We do not offer any writing services without the involvement of the researcher.
Learn More: https://bit.ly/3bWsGpz
Contact Us:
Website: https://www.phdassistance.com/
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Email: info@phdassistance.com
Deep Learning and Big Data technologies for IoT SecurityIRJET Journal
The document discusses using deep learning and big data technologies to improve security for Internet of Things (IoT) devices and networks. Specifically, it proposes using deep learning models to analyze large amounts of data from IoT sensors to better detect and classify security threats. This can help identify attacks like botnets and distributed denial-of-service (DDoS) attacks. The document also outlines some common IoT security challenges and how approaches like Apache Hadoop, Spark, and Storm can process large volumes of IoT data to improve real-time monitoring and threat prevention.
A STUDY ON ADOPTION OF BLOCKCHAIN TECHNOLOGY IN CYBERSECURITYIRJET Journal
This document discusses adopting blockchain technology in cybersecurity. It begins by introducing blockchain and its potential benefits for cybersecurity. These include decentralized data storage, improved availability against DDoS attacks, and enhanced security for IoT systems. The document then outlines the objectives of using blockchain to enhance cybersecurity by making systems more secure and tamper-proof. It presents the methodology and block diagram of how blockchain would work in a cybersecurity system. Several use cases are described, such as decentralized storage, availability, and IoT security. The document concludes by discussing common cybersecurity threats on blockchain networks and outlining the two-part workflow of an integrated blockchain-cybersecurity system.
I want you to Read intensively papers and give me a summary for ever.pdfamitkhanna2070
I want you to Read intensively papers and give me a summary for every paper and the linghth for
each paper is 2 pages or more. In the summary, you need to provide some of your own ideas.
Research Interests: Privacy-Aware Computing,Wireless and Mobile Security,Fog
Computing,Mobile Health and Safety, Cognitive Radio Networking,Algorithm Design and
Analysis.
You should select papers from the following conferences:
IEEE INFOCOM, IEEE Symposium on security and privacy, ACM CCS, USENIX Security.
Solution
PRIVACY AWARE COMPUTING
Introduction
With the increasing public concerns of security and personal data privacy worldwide, security
and privacy become an important research area. This research area is very broad and covers
many application domains.
The security and privacy aware computing research group actually focuses on
(1) privacy-preserved computing,
(2) Video surveillance, and
(3) secure biometric system.
Now let us briefly discuss the above three groups.
Privacy-preserved Computing
Concerns on the data privacy have been increasing worldwide. For example, Apple was
reportedly fined by South Korea’s telecommunications regulator for allegedly collecting and
storing private location data of iPhone users. The privacy concerns raised by both end-users and
government authorities have been hindering the deployment of many valuable IT services, such
as data mining and analysis, data outsourcing, and mobile location-aware computing.
soo, in response to the growing necessity of protecting data privacy, our research group has been
focusing on developing innovative solutions towards information services --- to support these
services while preserving users’ personal privacy.
Video Surveillance
With the growing installation of surveillance video cameras in both private and public areas, the
closed-circuit TV (CCTV) has been evolved from a single camera system to a multiple camera
system; and has recently been extended to a large-scale network of cameras.
One of the objectives of a camera network is to monitor and understand security issues in the
area under surveillance. While the camera network hardware is generally well-designed and
roundly installed, the development of intelligent video analysis software lags far behind. As
such, our group has been focusing on developing video surveillance algorithms such as face
tracking, person re-identification, human action recognition.
Our goal is to develop an intelligent video surveillance system.
Secure Biometric System
With the growing use of biometrics, there is a rising concern about the security and privacy of
the biometric data. Recent studies show that simple attacks on a biometric system, such as hill
climbing, are able to recover the raw biometric data from stolen biometric template. Moreover,
the attacker may be able to make use of the stolen face template to access the system or cross-
match across databases. Our group has been working on face template protection, multimodality
template protection, and .
SECURITY AND PRIVACY AWARE PROGRAMMING MODEL FOR IOT APPLICATIONS IN CLOUD EN...ijccsa
This document summarizes a research paper on privacy-preserving techniques for IoT data in cloud environments. It introduces two differential privacy algorithms: 1) Generic differential privacy (GenDP) which provides generalized privacy protection for homogeneous and heterogeneous IoT metadata through data portioning. 2) Cluster-based differential privacy which groups similar data into clusters before defining classifiers to validate privacy. The paper evaluates these techniques and finds the cluster-based approach offers better security than customized interactive algorithms while maintaining data utility. Overall, the study presents new differential privacy methods for anonymizing IoT metadata stored in the cloud.
1) Information security is undergoing significant change driven by evolving technology trends and how people use technology. Key trends include the growth of cloud computing, connected devices, data sharing, and new identity and trust models.
2) Over the next decade, information security requirements will be shaped by factors like globalization, regulation, and demographics. Suppliers will need to specialize to meet diverse needs.
3) Organizations require holistic information security approaches considering technology, processes, and people to adapt to threats and remain compliant with changing rules. Proactive strategies can provide competitive advantages over reactive ones.
Io t security_review_blockchain_solutionsShyam Goyal
This document reviews security issues related to the Internet of Things (IoT) and potential blockchain solutions. It presents a survey of emerging topics in IoT security and blockchain technology. The document maps major IoT security issues to possible solutions and reviews how blockchain could help address challenging security problems in IoT. It also identifies open challenges for IoT security.
CICS: Cloud–Internet Communication Security Framework for the Internet of Sma...AlAtfat
This document proposes a Cloud-Internet Communication Security (CICS) framework to provide secure communication among smart devices connected to the internet. The framework has four layers - a presentation layer on smart devices, a communication security layer providing encryption/decryption, a ubiquitous network layer, and a cloud layer. The cloud layer collects encrypted data from devices, processes it, and stores it securely. This framework aims to address security challenges like attacks that could disrupt services or cause denial of service when smart devices communicate using cloud computing.
Privacy and security policies in supply chainVanya Vladeva
Nowadays, Industry 4.0 era and the progress of technologies are moving on the society. Business solutions are aiming to perform cross functional and cross border services. In the years where the e-trade and supply are growing digitally and reaching every spot in the world via technologies, the problem for the security solutions are more than important and contemporary topic
The document discusses the Internet of Things (IoT) and its implications for insurance. It notes that as more "things" become connected to the internet and collect data, this creates opportunities for new types of insurance products based on device interactions and data-driven risk assessments. However, it also raises issues around data integrity, privacy, security and regulation that must be addressed. The insurance industry could gain over $1 trillion in new premiums if it properly manages risks related to data, cybersecurity, cloud computing and more.
"Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech...IRJET Journal
This document summarizes the key challenges of blockchain technology discussed in a research paper, including scalability, security, interoperability, regulation/governance, trust among users, financial resources, skills gaps, public perception, energy consumption, privacy issues, and inefficient technology design. It provides details on the causes and potential solutions for each challenge. The research methodology used surveys and statistical analysis to test hypotheses about blockchain technologies and the use of solutions like layer 2 scaling.
No One Can Write My Essay For Me Freely. Online assignment writing service.Kristen Flores
The book of Esther takes place in the Persian Empire during King Ahasuerus' reign. Esther, a Jew whose parents had died, was taken in by her cousin Mordecai. At the king's command, a beauty pageant was held to find a new queen. Esther entered and won. Meanwhile, the king's prime minister Haman plotted to kill all Jews, including Mordecai and Esther. Through Esther's intervention with the king, the Jews were spared and Haman was executed.
What Are Good Topics For An Argumentative ResearcKristen Flores
1. Earth is the only known planet capable of supporting life. It has the necessary conditions like a temperature range conducive to liquid water, abundant water, and other elements essential for life like carbon and oxygen.
2. Life plays a crucial role in regulating Earth's climate and atmosphere. Plants and algae produce oxygen and absorb carbon dioxide, keeping temperatures stable.
3. All of humanity relies on Earth's living systems like forests and oceans for survival. We depend on ecosystems for food, medicine, clean air and water. The extinction of species threatens our own existence on the planet.
More Related Content
Similar to 6G White paper Research challenges for Trust, Security and Privacy.pdf
the world of technology is changing at an unprecedented pace, and th.docxpelise1
the world of technology is changing at an unprecedented pace, and these changes represent business opportunities as well as challenges. Mass connectivity and faster speeds create opportunities for businesses to network more devices, complete more transactions, and enhance transaction quality. Internet Protocol version 6 (IPv6) and Internet of things (IoT) are two such technologies that represent significant opportunities for strategic cybersecurity technology professionals to create lasting value for their organizations.
IoT is the phenomenon of connecting devices used in everyday life. It provides an interactive environment of human users and a myriad of devices in a global information highway, always on and always able to provide information. IoT connections happen among many types of devices — sensors, embedded technologies, machines, appliances, smart phones — all connected through wired and wireless networks.
Cloud architectures such as software as a service have allowed for big data analytics and improved areas such as automated manufacturing. Data and real-time analytics are now available to workers through wearables and mobile devices.
Such pervasive proliferation of IoT devices gives hackers avenues to gain access to personal data and financial information and increases the complexity of data protection. Given the increased risks of data breaches, newer techniques in data loss prevention should be examined.
Increased bandwidth and increased levels of interconnectivity have allowed data to become dispersed, creating issues for big data integrity. In such a world, even the financial transactions of the future are likely to be different — Bitcoin and digital currency may replace a large portion of future financial transactions.
To survive and thrive, organizational technology strategists must develop appropriate technology road maps. These strategists must consider appropriate function, protection, and tamper-proofing of these new communications and transactions.
It will be impossible to protect data by merely concentrating on protecting repositories such as networks or endpoints. Cybersecurity strategists have to concentrate on protecting the data themselves. They will need to ensure that the data are protected no matter where they reside.:
Step2
Select Devices and Technologies
By now, you have an idea of your team members and your role on the team project. Now, it's time to get the details about the devices and technologies needed to be included in the Strategic Technology Plan for Data Loss Prevention.
You should limit the scope of this project by selecting a set of devices and technologies which are most appropriate for data loss prevention for your business mission and future success. Based on your prior knowledge of your company and based on the project roles you agreed upon in the previous step, perform some independent research on the following topics and identify a set of devices and technologies that you propose for.
6G Security Challenges And Potential SolutionsKristen Carter
This document discusses security challenges and potential solutions for 6G networks. It begins by outlining new 6G requirements like enhanced ultra-reliable low latency communication that will impact how security is implemented. It then describes new elements of the 6G architecture like intelligent radio and edge intelligence that may introduce new security threats. Next, it examines new applications in 6G like connected autonomous vehicles and how they have varying security needs. It concludes by surveying the security threats posed by key 6G technologies such as artificial intelligence, distributed ledger technology, quantum communication and terahertz bands, and potential solutions to address these threats.
6G Security Challenges And Potential SolutionsWendy Berg
The document discusses security challenges and potential solutions for 6G networks. It outlines how 6G requirements like high bandwidth, low latency, and massive device connectivity will impact security. New 6G technologies like edge intelligence, distributed AI, and quantum communication introduce new attack surfaces. The document surveys security challenges from the 6G architecture, requirements, and applications. It also discusses potential security solutions using technologies like distributed ledger, physical layer security, and quantum security.
Design of a Hybrid Authentication Technique for User and Device Authenticatio...IRJET Journal
The document proposes a hybrid authentication technique using blockchain authentication and artificial intelligence for user and device authentication in an integrated Internet of Things (IoT) environment. It discusses challenges with IoT security and reviews existing literature on blockchain and AI approaches for IoT authentication. The proposed technique aims to create a decentralized authentication system using a blockchain to store authentication records that are then used to train a neural network model. This trained model can authenticate new users and devices in the IoT network. The document outlines the objectives, methodology, and potential benefits of the proposed hybrid authentication approach for improving IoT security.
5G Drones with 5G Gaming and Application of 5G in Other Industries A ChatGPT ...ijtsrd
This paper explores the integration of 5G drones with 5G gaming and the application of 5G in various industries. The integration of 5G drones and gaming opens up new possibilities for immersive experiences within the met averse, enabling enhanced realism, aerial exploration, multiplayer aerial combat, and live event streaming. Additionally, the application of 5G in industries such as entertainment, agriculture, construction, logistics, public safety, healthcare, and more, brings significant benefits and advancements. 5G enables faster data transfer, low latency, and massive connectivity, empowering industries to optimize processes, enhance productivity, and deliver innovative services. The paper highlights the transformative impact of these technologies in different sectors, showcasing how they can revolutionize entertainment, improve efficiency, enable remote operations, and drive sustainable practices. Overall, the integration of 5G drones with 5G gaming and the application of 5G in various industries present exciting opportunities for innovation and progress. Manish Verma "5G Drones with 5G Gaming and Application of 5G in Other Industries: A ChatGPT Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd56341.pdf Paper URL: https://www.ijtsrd.com.com/computer-science/artificial-intelligence/56341/5g-drones-with-5g-gaming-and-application-of-5g-in-other-industries-a-chatgpt-analysis/manish-verma
In the past decade, internet of things (IoT) has been a
focus of research. Security and privacy are the key issues for IoT
applications, and still face some enormous challenges. In order to
facilitate this emerging domain, we in brief review the research
progress of IoT, and pay attention to the security. By means of
deeply analyzing the security architecture and features, the
security requirements are given. On the basis of these, we discuss
the research status of key technologies including encryption
mechanism, communication security, protecting sensor data and
cryptographic algorithms, and briefly outline the challenges.
Dissertations are among the most important pieces of work which students complete at university. And they allow you to work individually and on something that truly attracts you. Computer science is a hot field for researchers. Many topic ideas can be generated for a dissertation in this special branch of engineering.
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Deep Learning and Big Data technologies for IoT SecurityIRJET Journal
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I want you to Read intensively papers and give me a summary for ever.pdfamitkhanna2070
I want you to Read intensively papers and give me a summary for every paper and the linghth for
each paper is 2 pages or more. In the summary, you need to provide some of your own ideas.
Research Interests: Privacy-Aware Computing,Wireless and Mobile Security,Fog
Computing,Mobile Health and Safety, Cognitive Radio Networking,Algorithm Design and
Analysis.
You should select papers from the following conferences:
IEEE INFOCOM, IEEE Symposium on security and privacy, ACM CCS, USENIX Security.
Solution
PRIVACY AWARE COMPUTING
Introduction
With the increasing public concerns of security and personal data privacy worldwide, security
and privacy become an important research area. This research area is very broad and covers
many application domains.
The security and privacy aware computing research group actually focuses on
(1) privacy-preserved computing,
(2) Video surveillance, and
(3) secure biometric system.
Now let us briefly discuss the above three groups.
Privacy-preserved Computing
Concerns on the data privacy have been increasing worldwide. For example, Apple was
reportedly fined by South Korea’s telecommunications regulator for allegedly collecting and
storing private location data of iPhone users. The privacy concerns raised by both end-users and
government authorities have been hindering the deployment of many valuable IT services, such
as data mining and analysis, data outsourcing, and mobile location-aware computing.
soo, in response to the growing necessity of protecting data privacy, our research group has been
focusing on developing innovative solutions towards information services --- to support these
services while preserving users’ personal privacy.
Video Surveillance
With the growing installation of surveillance video cameras in both private and public areas, the
closed-circuit TV (CCTV) has been evolved from a single camera system to a multiple camera
system; and has recently been extended to a large-scale network of cameras.
One of the objectives of a camera network is to monitor and understand security issues in the
area under surveillance. While the camera network hardware is generally well-designed and
roundly installed, the development of intelligent video analysis software lags far behind. As
such, our group has been focusing on developing video surveillance algorithms such as face
tracking, person re-identification, human action recognition.
Our goal is to develop an intelligent video surveillance system.
Secure Biometric System
With the growing use of biometrics, there is a rising concern about the security and privacy of
the biometric data. Recent studies show that simple attacks on a biometric system, such as hill
climbing, are able to recover the raw biometric data from stolen biometric template. Moreover,
the attacker may be able to make use of the stolen face template to access the system or cross-
match across databases. Our group has been working on face template protection, multimodality
template protection, and .
SECURITY AND PRIVACY AWARE PROGRAMMING MODEL FOR IOT APPLICATIONS IN CLOUD EN...ijccsa
This document summarizes a research paper on privacy-preserving techniques for IoT data in cloud environments. It introduces two differential privacy algorithms: 1) Generic differential privacy (GenDP) which provides generalized privacy protection for homogeneous and heterogeneous IoT metadata through data portioning. 2) Cluster-based differential privacy which groups similar data into clusters before defining classifiers to validate privacy. The paper evaluates these techniques and finds the cluster-based approach offers better security than customized interactive algorithms while maintaining data utility. Overall, the study presents new differential privacy methods for anonymizing IoT metadata stored in the cloud.
1) Information security is undergoing significant change driven by evolving technology trends and how people use technology. Key trends include the growth of cloud computing, connected devices, data sharing, and new identity and trust models.
2) Over the next decade, information security requirements will be shaped by factors like globalization, regulation, and demographics. Suppliers will need to specialize to meet diverse needs.
3) Organizations require holistic information security approaches considering technology, processes, and people to adapt to threats and remain compliant with changing rules. Proactive strategies can provide competitive advantages over reactive ones.
Io t security_review_blockchain_solutionsShyam Goyal
This document reviews security issues related to the Internet of Things (IoT) and potential blockchain solutions. It presents a survey of emerging topics in IoT security and blockchain technology. The document maps major IoT security issues to possible solutions and reviews how blockchain could help address challenging security problems in IoT. It also identifies open challenges for IoT security.
CICS: Cloud–Internet Communication Security Framework for the Internet of Sma...AlAtfat
This document proposes a Cloud-Internet Communication Security (CICS) framework to provide secure communication among smart devices connected to the internet. The framework has four layers - a presentation layer on smart devices, a communication security layer providing encryption/decryption, a ubiquitous network layer, and a cloud layer. The cloud layer collects encrypted data from devices, processes it, and stores it securely. This framework aims to address security challenges like attacks that could disrupt services or cause denial of service when smart devices communicate using cloud computing.
Privacy and security policies in supply chainVanya Vladeva
Nowadays, Industry 4.0 era and the progress of technologies are moving on the society. Business solutions are aiming to perform cross functional and cross border services. In the years where the e-trade and supply are growing digitally and reaching every spot in the world via technologies, the problem for the security solutions are more than important and contemporary topic
The document discusses the Internet of Things (IoT) and its implications for insurance. It notes that as more "things" become connected to the internet and collect data, this creates opportunities for new types of insurance products based on device interactions and data-driven risk assessments. However, it also raises issues around data integrity, privacy, security and regulation that must be addressed. The insurance industry could gain over $1 trillion in new premiums if it properly manages risks related to data, cybersecurity, cloud computing and more.
"Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech...IRJET Journal
This document summarizes the key challenges of blockchain technology discussed in a research paper, including scalability, security, interoperability, regulation/governance, trust among users, financial resources, skills gaps, public perception, energy consumption, privacy issues, and inefficient technology design. It provides details on the causes and potential solutions for each challenge. The research methodology used surveys and statistical analysis to test hypotheses about blockchain technologies and the use of solutions like layer 2 scaling.
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6G White paper Research challenges for Trust, Security and Privacy.pdf
1. 6G WHITE PAPER:
RESEARCH CHALLENGES FOR
TRUST, SECURITY AND
PRIVACY
Editor in chief: Mika Ylianttila
Section editors: Raimo Kantola, Andrei Gurtov, Lozenzo Mucchi, Ian Oppermann
Document history:
v. 0.1. Feb. 1st
2020: First combined document draft structure with
placeholders for chapter contributions.
v. 0.2. Feb. 12th
2020: Modifications to structure based on telco 7th
Feb and
initial contributions merged into one single document.
v. 0.3. Mar. 2nd
2020: Section edits merged into one single document and
executive summary added. Document ready for first internal review.
v. 0.4. Mar. 8th
2020: Document ready for external review of 6G Summit
participants
v. 0.5. Apr. 7th
2020: Revision after 6G summit
v. 1.0. Apr. 24nd
2020: Document draft ready to be submitted to arXiv
2. Table of Contents
Executive summary: main research challenges........................................................................................................................ 3
Acknowledgement .................................................................................................................................................................... 4
List of contributors.................................................................................................................................................................... 4
Citation information.................................................................................................................................................................. 4
Abstract..................................................................................................................................................................................... 5
1. Trust networking for 6G....................................................................................................................................................... 6
1.1. What is trust networking? ............................................................................................................................................. 6
1.2. Principles of trust networking........................................................................................................................................ 7
1.3. Research challenges in trust networking....................................................................................................................... 9
2.Network security architecture and cryptographic technologies reaching for post-quantum era....................................... 10
2.1. Network Security Architecture in 6G........................................................................................................................... 10
2.2. Post-Quantum Crypto-Security in the 6G Architecture............................................................................................... 10
2.3. Software and AI defined security in beyond 5G and 6G.............................................................................................. 11
2.4. Securing the convergence of telco cloud..................................................................................................................... 13
2.5. Research challenges for 6G security architectures...................................................................................................... 14
3.Physical Layer Security solutions and technologies............................................................................................................. 15
3.1. Physical-layer security as confidentiality enabler in 6G connectivity.......................................................................... 15
3.2. Distributed and cooperative PHY-security protocols for 6G networks........................................................................ 16
3.3. Security of Cell-free Massive MIMO and Intelligent Reflective Surface...................................................................... 17
3.4. Physical Layer Security using Visible Light Communications in 6G.............................................................................. 18
3.5. Research challenges for physical layer security........................................................................................................... 20
4. Privacy protection in 6G: principles, technologies and regulation..................................................................................... 21
4.1. Privacy Requirements in a future hyper-connected mobile world.............................................................................. 21
4.2. How Personal is Information?...................................................................................................................................... 22
4.3. Privacy-Preserving Technologies.................................................................................................................................. 23
4.4. Standardization and Regulatory Aspects..................................................................................................................... 23
4.5. Research challenges for privacy in 6G ......................................................................................................................... 24
References .............................................................................................................................................................................. 25
3. Executive summary: main research challenges
Vision: Trustworthy 6G. The challenges in creating a trustworthy 6G are multidisciplinary spanning technology, regulation,
techno-economics, politics and ethics. A combination of the current regulation, economic incentives and technology are
maintaining the current level of hacking, lack of trust, privacy and security on the Internet. In 6G, this will not suffice, because
physical safety will more and more depend on information technology and the networks we use for communication. Therefore,
we need trustworthy 6G. The roles of trust, security and privacy are somewhat interconnected, but different facets of next
generation networks. This white paper addresses their fundamental research challenges.
Research challenge 1: Inherited and novel threats in 6G scale. The diversity and volume of novel IoT devices and their control
systems will continue to pose significant security and privacy risks and additional threat vectors as we move from 5G to beyond
towards 6G system. The volume of new IoT devices introduced into 6G network will increase 10x from 10 billion scale of 5G
networks to 100 billion scale in 6G. As a result of such deployment and use of 6G, the dependence of the economy and societies
on IT and the networks will deepen. Safety will depend on IT and the networks. The development of AI blurs the line between
reality and fake content and helps to create ever more intelligent attacks. The role of IT and the networks in national security
keeps rising – a continuation of what we see in 5G.
Research challenge 2: End-to-end trust in 6G. In current “open internet” regulation, the telco cloud can be used for trust services
only equally for all users. 6G should position the future cellular network as a solution to the all issues of trustworthy or trust
networking such that network based information technology can be trusted to provide expected outcomes even in the face of
malicious actors trying to interfere. 6G network must support embedded trust such that the resulting level of information
security in 6G and the packet data networks where 6G provides connectivity to is significantly better than in state-of-the art
networks commonly used today. Trust modeling, trust policies and trust mechanisms need to be defined.
Research challenge 3: Post-quantum cryptography and security architecture for 6G. The current 5G standard does not address
the issue of quantum computing but relies on traditional cryptography. The development towards cloud and edge native
infrastructures is expected to continue in 6G networks. While large-scale quantum computing can be expected to take longer,
it is time to prepare for the shift to cryptography that is secure in the post-quantum world. According to current knowledge,
contemporary symmetric cryptography remains secure for the most part even after the advent of quantum computing. Future
of SIM cards and use of asymmetric cryptography will be interesting research questions.
Research challenge 4: Machine-learning as tool and risk in softwarized 6G. As 6G moves toward THz spectrum with much higher
bandwidth, more densification and cloudification for a hyper connected world by joining billions of devices and nodes with
global reach for terrestrial, ocean and space, automated security utilizing the concepts of security function softwarization and
virtualization, and machine learning will be inevitable. There are two facets: on the one hand, security algorithms can use
machine learning to orchestrate attacks and respond to them in an optimal way. On the other hand, also the attacking algorithms
can learn better how the network operates and create better attacks. Continuous deep learning is needed on a packet/byte
level and applying machine learning to enforce policies, detect, contain, mitigate and prevent threats or active attacks.
Research challenge 5: Physical layer security in 6G. Physical layer security techniques can represent efficient solutions for
securing the most critical and less investigated network segments which are the ones between the body sensors and a sink or a
hub node. Research questions include which are the most suitable physical layer features to be exploited for the definition of
security algorithms in 6G challenging environment characterized by high network scalability, heterogeneous devices and
different forms of malicious attacks, and should PhySec be a stand-alone security design or interactions with upper layers are
mandatory in 6G networks.
Research challenge 6: Privacy as exploited resource in 6G. The relevance specifically for 6G is that, 5G is still largely device /
network specific, 6G envisages far more immersive engagement with the network. It is now the subject of ongoing discussion in
the standards world. There is currently no way to unambiguously determine when linked, deidentified datasets cross the
threshold to become personally identifiable. This is a major, unaddressed problem for many digital technologies in different
sectors, such as in Smart Healthcare, Industrial Automation, and Smart Transportation. Courts in different parts of the world are
making decisions about whether privacy is being infringed without formal measures of the level of personal information, while
companies are seeking new ways to exploit private data to create new business revenues. As solution alternatives, we may
consider blockchain, distributed ledger technologies and differential privacy approaches.
4. Acknowledgement
This draft white paper has been written by an international expert group, led by the Finnish 6G Flagship program
(http://6gflagship.com) at the University of Oulu, within a series of twelve 6G white papers to be published in their final format
in June 2020.
List of contributors
Editor in chief
Mika Ylianttila, mika.ylianttila@oulu.fi, Centre for Wireless Communications, University of Oulu, Finland.
Section editors
Raimo Kantola, raimo.kantola@aalto.fi, Department of Communications and Networking, Aalto University, Finland
Andrei Gurtov, gurtov@acm.org, Department of Computer and Information Sciences, Linköping University, Sweden
Lozenzo Mucchi, lorenzo.mucchi@unifi.it, Department of Information Engineering, University of Florence, Italy
Ian Oppermann, ianopper@outlook.com, NSW Government Australia, University of Technology Sydney, Australia
Section contributors
Zheng Yan, zheng.yan@aalto.fi, Department of Communications and Networking, Aalto University, Finland
Tri Hong Nguyen, tri.nguyen@oulu.fi, Centre for Ubiquitous Computing, University of Oulu, Finland
Fei Liu, liufei19@huawei.com, Singapore Research Center, Huawei International
Tharaka Hewa, tharaka.hewa@oulu.fi, Centre for Wireless Communications, University of Oulu, Finland
Madhusanka Liyanage, madhusanka@ucd.ie, University College Dublin, Ireland
Ahmad Ijaz, ijaz.ahmad@vtt.fi, VTT Technical Research Centre of Finland Ltd, Finland
Juha Partala, juha.partala@oulu.fi, Center for Machine Vision and Signal Analysis, University of Oulu, Finland
Robert Abbas, robert.abbas@mq.edu.au, Macquarie university, Australia
Artur Hecker, artur.hecker@huawei.com, Huawei Technologies Munich Research Center, Germany
Sara Jayousi, sara.jayousi@unifi.it, Department of Information Engineering, University of Florence, Italy
Alessio Martinelli, alessio.martinelli@unifi.it, Department of Information Engineering, University of Florence, Italy
Stefano Caputo, stefano.caputo@unifi.it, Department of Information Engineering, University of Florence, Italy
Jonathan Bechtold, j.bechtold@wiosense.de, WIOsense GmbH & Co. KG, Bremen, Germany
Iván Morales, i.morales@wiosense.de, WIOsense GmbH & Co. KG, Bremen, Germany
Andrei Stoica, r.stoica@wiosense.de, WIOsense GmbH & Co. KG, Bremen, Germany
Giuseppe Abreu, g.abreu@jacobs-university.de, Jacobs University Bremen, Bremen, Germany
Shahriar Shahabuddin, shahriar.shahabuddin@nokia.com, Mobile Networks, Nokia, Oulu, Finland
Erdal Panayirci, eepanay@khas.edu.tr, Kadir Has University, Istanbul, Turkey
Harald Haas, h.haas@ad.ac.uk, University of Edinburgh, UK
Tanesh Kumar, tanesh.kumar@oulu.fi, Centre for Wireless Communications, University of Oulu, Finland
Basak Ozan Ozparlak, basak@ozan.av.tr, Ozyegin University Faculty of Law Istanbul, Turkey
Juha Röning, juha.roning@oulu.fi, Biomimetics and Intelligent Systems Group, University of Oulu, Finland
Citation information
M. Ylianttila, R. Kantola, A. Gurtov, L. Mucchi, I. Oppermann (eds), “6G White paper: Research challenges for Trust, Security
and Privacy”. 6G Flagship, University of Oulu, arXiv preprint, April 2020, arXiv:2004.11665, https://arxiv.org/abs/2004.11665
M. Ylianttila, R. Kantola, A. Gurtov, L. Mucchi, I. Oppermann (eds), “6G White paper: Research challenges for Trust, Security
and Privacy”. 6G Flagship, University of Oulu, June 2020.
5. Abstract
The roles of trust, security and privacy are somewhat interconnected, but different facets of next generation networks. The
challenges in creating a trustworthy 6G are multidisciplinary spanning technology, regulation, techno-economics, politics and
ethics. This white paper addresses their fundamental research challenges in three key areas:
Trust: Under the current “open internet” regulation, the telco cloud can be used for trust services only equally for all users. 6G
network must support embedded trust for increased level of information security in 6G. Trust modeling, trust policies and trust
mechanisms need to be defined. 6G interlinks physical and digital worlds making safety dependent on information security.
Therefore, we need trustworthy 6G.
Security: In 6G era, the dependence of the economy and societies on IT and the networks will deepen. The role of IT and the
networks in national security keeps rising – a continuation of what we see in 5G. The development towards cloud and edge
native infrastructures is expected to continue in 6G networks, and we need holistic 6G network security architecture planning.
Security automation opens new questions: machine learning can be used to make safer systems, but also more dangerous
attacks. Physical layer security techniques can also represent efficient solutions for securing less investigated network segments
as first line of defense.
Privacy: There is currently no way to unambiguously determine when linked, deidentified datasets cross the threshold to
become personally identifiable. This is a major, unaddressed problem for many digital technologies in different sectors. Courts
in different parts of the world are making decisions about whether privacy is being infringed without formal measures of the
level of personal information, while companies are seeking new ways to exploit private data to create new business revenues.
As solution alternatives, we may consider blockchain, distributed ledger technologies and differential privacy approaches.
6. 1. Trust networking for 6G
Section editor: Raimo Kantola
Section contributors: Zheng Yan, Tri Hong Nguyen, Fei Liu, Tharaka Hewa, Madhusanka Liyanage
This chapter discusses the motivations, use cases, solutions, relevant technical mechanisms, visions and research
challenges in trust management in beyond 5G and 6G systems.
1.1. What is trust networking?
Trust in a network context is about expected outcomes of communicating with a remote party in a session, when clicking on a
link or believing in what an email says. The possible outcomes are either the positive value of the communication or being
hacked or cheated in some way. Trust spans all protocol layers from the IP layer to applications and content.
A system of trust in a network communication, i.e. trust networking should help in addressing questions like: can this host
communicate with a remote party without being attacked or hacked in the process? Can this interaction lead to loss of data?
Should flows from a remote network be served or not under heavy load? Or would it be best to drop this flow and devote
resources to other flows? Is it possible that a source address in a packet is spoofed? When communicating with a remote party,
how does a host minimize its exposure to possible future attacks or long-term loss of privacy? How do the parties protect their
communicated data from leakage or being accessed by any unauthorized parties? In state of the art, a number of frameworks
for trust networking can be found: ITU-T Y.3052 [1], Y3053 [2], virtual network and SDN trust framework and Customer Edge
Switching (CES) [3]. The latter is advanced since it supports personalized security policies for all devices, at extreme, turning a
network into a firewall such that the network transmits only expected traffic [4]. It also supports interworking with legacy IP
networks.
Why is trust networking needed in 6G?
6G will be used to build a wide digital/physical world boundary for sensing the world, understanding it and programming it. As
a result, in addition to loss of information, loss of control over your device or host or loss of money, breach of information
security can endanger physical safety of people and cause loss of property. At worst, during international conflicts foreign
cyberwar troops could cause havoc in a country on a level that using traditional warfare will not be needed to pressure the
victim to accept the terms and conditions issued by the attacker. Like we are seeing in the 5G era, national security concerns
are playing an increasing role in mobile technology. This trend will be even more prominent in 6G. To address these concerns
6G network must support embedded trust such that the resulting level of information security in 6G and the packet data
networks where 6G provides connectivity to is significantly better than in state-of-the art networks commonly used today.
Use cases for trust networking in 6G
Trust networking can be applied in specialized 6G networks for local or nation-wide use, it can be applied to packet data
networks (PDN) that provide remote access to such specialized networks or any other critical infrastructure. It could be
offered to consumers as a PDN service. Finally, trust networking may be applied to all mobile use. The use cases range from
simple, single administration handling the whole trusted network with all its devices to cases where devices are owned by
independent parties and different segments, layers or subsystems in the network are owned and managed by multiple
different stakeholders with possible conflicts of interest. Therefore, trust networking should be able to handle multi-admin
relations in flexible ways. Trusted networking shall be provided over multiple trust domains where sharing of trust related
information is set up to take place within a trust domain. Some level of trust related information can also be shared across
several trust domains. Trust domain is a mechanism to scale trust networking into a large number of hosts, network segments,
administrations, applications etc.
Constraints of trust networking
The introduction of trust networking in an IP network or a mobile network requires changes in the network. It must be
possible to deploy those changes one network at a time. If changes are needed both in devices and the network, they are
realistically limited to a single administration. An important case of single admin solution is when a server is able to attest the
client software and vice versa. If a multi-stakeholder trust networking is desired, no compulsory changes are allowed in the
hosts for ease of adoption. We assume that the device market is separate from the network market and that the MNOs
7. cannot dictate security or trust properties of the devices that can be connected beyond what they are able to do today.
The current EU “open internet” regulation [8, 9] does not allow personalized filtering of traffic for Internet Access Services
(IAS) for consumers by the network. If filtering is applied by the ISP or Mobile Operator (MNO), it must be applied to all users
in the same way. While this regulation is in force, trust networking can be applied to specialized networks that are out of
scope for net neutrality or “open internet”. Provided the telco cloud is deregulated, the MNO or ISP could sell trust
networking e.g. as “Software as a Service” (SaaS) to its subscribers. The users would then define all aspects of using the cloud
software for trust networking and would only use operator defined trust services with a well understood API. This would give
the widest impact from trust networking without sacrificing the ideals of “open internet” in any way.
1.2. Principles of trust networking
Our earlier White Paper of 2019 [5], ITU-T trusted networking [1,2] and CES [3] all agree on the first principle of applying
ID/Locator split into the communication such that devices have a stable ID against which all trust and reputation related
information can be collected, claims on bad behavior can be made. The edge nodes that assign these IDs will also translate
them to IP and other addresses on request. The devices may use private addresses while the edge node will translate between
the private addresses and the globally unique routing locators. The ID/Locator split is illustrated in Figure 1. Policy
management shall be used in trust networking to tailor the generic trust engine to a use case or to end user and admin needs.
Policies are used to describe the expectations of each entity and many aspects of the behavior of the nodes. Each entity
(admin, subscriber, user) shall have its own policy. Policies may scale to the level of individual applications. All aspects of trust
negotiation may be controlled by policy.
Figure 1: Conceptual model and ID/locator split for trust networking [5]
Nodes supporting trust networking shall ubiquitously collect evidence of behavior of all seen remote network entities. The
collected evidence may be shared between nodes in a domain. The evidence is used to produce a reputation for the remote
entities. The trust networking nodes will have an embedded reputation system. Reputation is used to make trust decisions
such as asking for more information, admitting a flow, refusing to communicate, allocating resources for an incoming flow
depending on the load situation etc. In wide area networking, trust and reputation management may be organized in different
ways. The first aspect is to control trust related information sharing. Another aspect is how to manage the trust claims
between the entities and domains such as: “your host Z is too aggressive, restrain it using X”, or the explicit acknowledgement
like “I have now restored Z into a normal behavior”. Alternatively, instead of such an elaborate claims system, reputation may
be restored to an indifferent state by aging. Wide area trust management might be implemented with a hierarchical or
centralized system [6] or by a distributed system or a combination of the two. In order to encourage evidence sharing across
administrative boundaries, the evidence could be encrypted and processed in encrypted form by using e.g. homomorphic
8. encryption [7]. In addition, incentives should be provided in order to encourage trust-related data sharing for reputation
generation, as depicted in Figure 2.
Figure 2: Trust-related data sharing for reputation generation
Trust modeling
A trust model describes what evidence is used, how this data is collected, processed, stored and distributed among the
stakeholders and how trust decisions are made. The model describes the claims and actions the stakeholders can and will take
to restore trust. The model also describes the lifecycle of the trust status of the elements. The myriad of different end user
scenarios including vertical networks, advanced vehicular networks, user-tenancy etc., demand that the trust model(s)
encompass all elements and entities participating in communications and provide flexibility such that the trust engine is as
generic as possible and that it can be tuned to different scenarios and use cases with little effort.
The trust model must have resistance to system attacks such as ballot stuffing or bad-mouthing. To incentivize evidence
sharing, data may be shared and processed in an encrypted form. The system should be able to process non-conclusive evidence
but all available techniques for producing conclusive evidence should be applied. The trust systems need to be measured and
evaluated against the requirements of multiple operators across the globe and the requirements of the regulatory standards
ratified across different regions, such as GDPR. In the state of the art, the 5G trust model is focused on the subscriber to MNO
relation and on the relations of the different Virtualized Network Functions (VNFs). In Beyond 5G and 6G, an extended trust
model for distributed processing including device to device relations should be added in order to support trustworthy use of
the mobile system. Trust modeling includes also application trust. This can be supported by trust intelligence, malware
detection, software attestation etc. There is a need that the 6G trust model and industry specific trust models should interwork,
in particular when 6G is used on the physical/digital world boundary and the operation is safety critical.
Constraints on trust models: Agreement on unified terms of quantifying trust among various telecom institutions as well as
governments will impose a new challenge. For example, we may need to define liabilities in case when someone has been
careless or malicious and his/her resources are used in attacks against other entities. On the same lines the agreement of
security transparency or anonymity/obscurity among these parties will need clear practices and rules.
Distributed Ledgers and 6G
On the open Internet, decentralized systems where the participants freely leave and join to be a part of a distributed system
has been developing without any controllers. This leaves the issue of trust to the end systems. To verify the trust on the
services or participants, a traditional solution is based on a third party who proves and confirms for the correctness of the
services. In many cases, the parties cannot agree on a single 3rd
trusted party, and in fact many 3rd
parties are used in parallel
weakening security overall. Now, an alternative is emerging with the use of distributed ledgers (DL) with many alternative
consensus mechanisms which can support consensus on trust among all parties in a system. The information stored in DL can
be plain text or encrypted. The DL is at best when conclusive facts are stored immutably. In addition, smart contracts can be
applied to offer autonomic trust networking by automatically triggering trust networking functions based on evaluated trust
relationships. In 6G, when conclusive data related to dynamic trust relations is generated, it could be stored in a DL and the
9. possible conclusive responses of the related parties could be suitably processed. As a result, a long-term history reflecting
long term quality or trustworthiness of the different parties could be produced. This could be utilized to drive longer term
improvement in the operations that use 6G.
Trust and routing
The current Internet wide area routing based on the Border Gateway Protocol (BGP) to which mobile systems are exposed in
the connected Packet Data Networks (PDN) has many weaknesses, such as the routing prefixes are sometimes hijacked either
due to configuration errors or by malicious intent, convergence can take a long time leading to limited availability of the
carried services, Quality of Services over the wide area remains an unsolved problem etc. In order to fully leverage the trust
and security solutions developed for 6G itself, it is worth to point out that a more trustworthy routing solution is needed for
the Internet and the PDNs to which 6G connect.
1.3. Research challenges in trust networking
Many research challenges in trust networking remain.
• Open Internet regulation that allows the widest use of trust networking to the maximum benefit for the end users.
• Verification of trust networking in multiple use cases with various needs.
• Scalability of the policy management to all kinds of devices and application use patterns.
• Scaling trust networking to wide area with multiple stakeholders; Scaling trust networking to high network speeds,
large number of flow setups, to large number of remote entities, etc.
• Trust management for the wide area across multiple trust domains.
• Extending trust networking to span the whole end to end session, device to network to device.
• How to improve the privacy of DL in 6G era, but still keep its characteristics?
• A specific DL for 6G mobile network
• A study on particular consensus algorithms for trust networking
• What are the key requirements for meeting the trust system of data transparency, AI anonymization, and privacy
protection?
• What does the trust model/set of trust models look like, based on the comprehensive consideration of different phases
of the trust lifecycle, different service scenarios, and different roles of the ecosystem?
• What are the main factors related to the initial establishment of trust, trust measurement, and trust decision-making
within the network and among the different roles of telecom?
10. 2.Network security architecture and cryptographic technologies reaching for
post-quantum era
Section editor: Andrei Gurtov
Section contributors: Ahmad Ijaz, Juha Partala, Robert Abbas, Artur Hecker
This chapter discusses about the challenges, solutions and visions of network security architecture and of
cryptographic technologies in beyond 5G systems from several aspects. Future of SIM cards and use of
asymmetric cryptography are pondered upon. We discuss also future convergence of telecom networks with the
Internet infrastructure. Other topics include security of software defined networking with AI capabilities and
trustworthy cloud computing with remote attestation when applied to 6G.
2.1. Network Security Architecture in 6G
Since inception of digital mobile communication in 2G, mobile networks are reliant on a physical storage of symmetric keys in
a Subscriber Identity Module known also as SIM card. Encryption algorithms migrated from customary to international
standards, and additional cryptographic mechanisms were added for mutual authentication. However, fundamentally the
security model in 5G is still reliant on SIM cards [16]. While SIM cards became smaller (now at "nano" size), those still need to
be plugged to devices, which limits applicability e.g. to IoT. Introduction of eSIMs partly addresses this challenge, though
leaves issues with physical size. iSIM under development could be a part of System-on-Chip in future devices although it faces
opposition from operators due to possible loss of control.
The need for 6G network security architecture model
Traditional SIM cards rely on proven symmetric key encryption, which scaled well up to billions of users. But it has drawback
for example with IoT, privacy, network authentication and false base stations. Is it going to be a fundamental shift from
symmetric crypto to asymmetric public/private keys? This was never deployed before at such scale. In addition to SIM, 5G
plans to support authentication through a public-key infrastructure (PKI). The core of 5G is implemented as a set of
microservices communicating over HTTPS. The authentication, confidentiality and integrity for such communication is
provided by Transport Layer Security (TLS) using elliptic curve cryptography (ECC). However, this has not yet been deployed
yet and can be left for 6G.
This chapter tries to answer key questions about 6G security model. Is it still going to be physical SIM cards in the devices? Or
most IoT devices will have clones of software SIMs or Trusted Platform Modules? A certificate system for WWW works
although with eventual certificate revocation and Certificate Authority (CA) break-ins. DNSSEC is an example of gradually
deploying asymmetric key system. Host Identity Protocol implements this concept at the network layer [25]. Preventing Man-
in-the-Middle attacks is a critical requirement for asymmetric encryption. Network slicing in 5G, as it has been defined by the
3GPP in Rel15, has hardly any security impact, as it does not permit to separate traffic of different services. Instead, deploying
IPsec/VPN or HIP services in 6G would help to isolate user traffic.
2.2. Post-Quantum Crypto-Security in the 6G Architecture
The quantum computing paradigm is fundamentally different from classical computing. There are computational problems we
do not know how to solve efficiently on a contemporary computer, but there are algorithms that solve those problems
efficiently on a quantum one. One of these problems is the discrete logarithm problem which is the basis of modern asymmetric
cryptography. If large-scale quantum computing becomes a reality, these cryptographic primitives need to be replaced for
quantum-secure ones. According to a recent survey [17], quantum computing may be commercially available in a few years.
While large-scale quantum computing can be expected to take longer, it is time to prepare for the shift to cryptography that is
secure in the post-quantum world. According to current knowledge, contemporary symmetric cryptography remains secure for
the most part even after the advent of quantum computing. In general, it suffices to double the size of the symmetric keys due
to Grover's algorithm. The problems lie in asymmetric primitives based on integer factorization and the discrete logarithm
11. problem that are solvable in polynomial time on a quantum computer using Shor's algorithm.
Why is consideration of quantum computing important for 6G?
The current 5G standard does not address the issue of quantum computing, but relies on traditional cryptography such as ECC.
However, the elliptic curve discrete logarithm problem (ECDLP) can be solved in polynomial time on a quantum computer.
The development towards cloud and edge native infrastructures is expected to continue in 6G networks. Compared to earlier
generations, the security architecture of 6G will be more complex, dominated by current transport layer security standards and
be increasingly dependent on the PKI. This development will make the core network completely reliant on the functionality and
security of the underlying PKI. However, currently there are no post-quantum secure primitives, for example, in TLS.
There are public-key primitives considered to be quantum-safe [19]. These include for example, code-based encryption
schemes such as McEliece [22] and lattice-based NTRU [21]. Many of these suggestions have survived decades of attacks and
can thus be considered secure both in the classical and the quantum setting. However, their efficiency is poor and key sizes big
compared to, for example, ECDLP-based schemes. Replacement of contemporary asymmetric cryptography with post-quantum
secure schemes will incur costs both in the communication and operational efficiency of the network. Research is needed to
identify the correct application of post-quantum secure cryptography in order to satisfy the envisioned performance and
functionality of the 6G architecture. In addition, research into new, more efficient post-quantum secure asymmetric schemes
is needed in order to reach this goal [18-22]
Standardization efforts for post-quantum cryptography are ongoing. In the United States, National Institute of Standards and
Technology (NIST) is currently hosting a selection process NIST PQC for post-quantum cryptography standardization. These new
primitives are expected to provide post-quantum secure key exchange, as well as to augment the Digital Signature Standard
(DSS) FIPS 186-4. We propose that the 6G standardization community pays close attention to these efforts.
2.3. Software and AI defined security in beyond 5G and 6G
As 6G moves toward THz spectrum with much higher bandwidth, more densification and cloudification for a hyper connected
world by joining billions of devices and nodes with global reach for terrestrial, ocean and space, automated security utilizing
the concepts of security function softwarization and virtualization, and machine learning will be inevitable. To eliminate
constraints in existing and evolving 5G networks security, security systems using the existing concepts of SDN and NFV must
be further improved with embedding intelligence for dynamicity to match the needs of 6G security. In this vain, intelligent
security functions in containerised VNF box will monitor traffic in 6G residing in gateways to scan the traffic using continuous
deep learning on a packet/byte level and applying machine learning to enforce policies, detect, contain, mitigate and prevent
threats or active attacks. Security functions using container technology offers better utilization rates, less storage
requirements, enhanced security and faster reboot time. Containers will be grouped into Pods, each Pod consisting of
multiple containers on a single machine, with security service functions and providing availability through scaling up or down.
The advances in cloud computing such as edge and fog computing will be used to maintain and deploy security functions
(security VNFs) in different network perimeters as the use arises through proactive decision-making using machine learning.
Building on the concepts of SDN, global resource visibility and event monitoring, with synchronized network security policies
among different stakeholders, and programmable APIs, network abstractions will be used to ensure end-to-end network
security.
6G networks will harmonize the concepts of SDN, NFV, and AI in an integrated environment not only to provide the necessary
service [23], but also to ensure end-to-end network security, as shown in Figure 3. Programmable interfaces on
programmable forwarding plane will enable deploying softwarized security functions much like VNFs in any network
perimeter or instance in a virtual environment using AI not only proactively discover threats, but also to initiate security
function transfer from point to point throughout the network.
12. Figure 3: A holistic software defined security platform leveraging AI
6G total automated, zero touch and zero trust security where zero trust for all North-South (N-S outbound/Inbound
traffic from/to data center) and East-West (E-W form Container to another) cloud traffic must be checked with AI
based ML for threat detection [24], prevention and containment where the network can be treated as a giant
firewall that integrates the flowing security functions:
• Access security (inbound/ outbound gateway, end points security)
• Cloud security (edge cloud and central cloud)
• Orchestration platform security
13. 2.4. Securing the convergence of telco cloud
With the advent of virtualization and softwarization, the Cloud Computing has become the driving paradigm for service
provisioning in the smartphone era. With 5G, these principles have found their way both into the recent releases of the 3GPP
standards (e.g. Rel15 SBA) and in the underlying support systems (ETSI NFV, ONF SDN, ETSI MEC, orchestration, etc).
Furthermore, similar virtualization, sandboxing and Cloud-provided service concepts are widespread in the application areas
on the modern powerful terminals: for instance, it is quite common to seamlessly integrate remote (e.g. Cloud-based) service
end-points in the smartphone apps; specific computation-intensive or dataset-based functions like optimizations, search,
pattern recognition in multimedia, etc., are often seamlessly performed on a remote Cloud.
With the inclusion and the expected further fusion of IoT and mobile telecommunications domains, the number of connected
devices, their density and their service needs will increase by several magnitudes, in turn requiring a considerable increase in
available network access points, network capacity and service capabilities. Consequently, and given the performance
constraints of the typical IoT devices, such offloading of compute, storage and networking capabilities to other nodes can be
expected to increase with the success and during the course of 5G and to generalize and finally become common place
functionality in 6G. Indeed, given its presumed better reliability and higher throughputs with lower latencies, it is only natural
to expect diverse computations in 6G to be offloaded both from terminals to the network (e.g. IoT) and from the network to
particular terminals or groups of the latter (Customer-Premises Data Centers in the factories, smart cities and smart hospitals).
Opportunities related to Execution Offloading in 6G
If the questions above can be addressed, the generic offloading of computation paves path to also improving the security
posture of the system:
- Privacy improvement: users could avoid giving out raw data by only allowing critical computations within their own
virtual machines running on their or on remote equipment.
- Green computing: through the support of load-dependent offloading, green computations e.g. on nodes with
available eco-produced current become possible. At the system level, it allows to remove nodes such as Data Centers,
and therefore to flatten the regional peaks in the power consumption.
Challenges related to Execution Offloading in 6G
Executing various functions on different remote ends is an outstanding feature, which allows to dynamically adjust the
application to the available resources and the resources to the application requirements and has the potential to introduce
new appealing features into 6G. However, it also poses several well-known security threats:
- Data confidentiality: if data must be sent to remote endpoints, how can a tenant be sure that this data is only used
for the intended computation?
- Data integrity: how can we ensure that the data is not lost, modified in the process? This, in particular, applies to the
obtained results. How do we know that the communicated results are indeed the expected outcome?
- Platform integrity: as such computational offloading can be seen as a generalization of the Cloud-computing, the
platform of any service environment therefore will spread dynamically over all resources currently involved into the
computation. Therefore, in addition to the questions above, the question of the integrity of that virtual, possibly
dynamically changing, service computation domain should be addressed.
- User privacy: in addition to the raw data, which might or might not be private data of the user, the statistics and
meta-data of the requests should be protected against abuse.
Existing Approaches and Research Challenges
There are several approaches, how the security challenges above can be overcome or mitigated:
- Authentication of remote endpoints: authentication of endpoints allows to verify the claimed identity of the endpoint.
However, it is not capable of making statements with regard to the integrity of that endpoint. Therefore, it is not
alone sufficient to protect against such threats as errors in the internal implementation, failures during the runtime,
malicious modifications of the remote endpoint (e.g. after intrusion).
- Certification of the platforms: certification of the platform verifies particular features and claims with regard to that
platform. Security verification methods such as Common Criteria are well-understood and could be applied to verify
the soundness of the implementation of a set of security mechanisms (e.g. as per protection profile). However, such
measures are also costly and cannot per se guarantee the security posture of a node at a particular point of time, as
intrusions cannot be prevented.
14. - Support of remote attestation: some security frameworks, such as the so-called Trusted Computing (TC), can provide
verifiable remote attestation services in some scenarios. By tying key platform operations to tamper-resistant on-
board hardware modules (so-called TPM) and introducing a cryptographic framework on top of the latter, the
integrity of a remote platform including its operating system, virtual machines and services can be addressed.
However, TC also requires a sound key management and standardized interfaces. Generally speaking, TC raises many
questions as to the feasibility (e.g., scalability) and economic viability (e.g. OPEX overhead) of such integration in the
operational highly multi-tenant environment of 6G (with many operators, verticals and end-users).
- Support of secure properties in spite insecure execution platforms: in the recent years, quite some research has been
devoted to the novel mechanisms, which do not require a trusted platform for (particular) secure computations.
Among such approaches, we can broadly mention Encrypted Search, Private Information Retrieval and Search, ORAM,
Fully Homomorphic Encryption libraries, etc. Since these methods do not require platform certification, they have the
potential for better inclusion (also on the fly) and for cost reduction. However, not all of these methods are suitable
for general offloading, and some are known to be extremely computation-intensive. Therefore, it remains to be seen,
if, where and how such and similar methods can be integrated in the 6G.
The list above is not mutually exclusive and several such mechanisms can coexist. The impacts of such co-existence should be
carefully addressed in the operational reality of mobile networks.
2.5. Research challenges for 6G security architectures
Among important general challenges is whether future 6G networks will reply on web CAs or DNSSEC instead of SIM cards to
admit devices to the network. Another fundamental issue is legal interception requirement for current telecom operators
providing mobile services. It is going to be still present in 6G with all-IP voice, chat, and data communication? Are authorities
required e.g. to read all sensor, remote vehicle or tactile Internet data under a court order? This affects fundamentally the
security architecture, as end-to-end encryption would not be allowed in place of proxy-time communication with key escrow.
Research challenges/questions:
• How to replace SIM cards for IoT devices?
• How to apply 6G security automation vision based on full visibility?
• How to utilize AI to provide real time full protection End to End against known and unknown threat?
• 6G Security platform and framework.
• How to ensure post-quantum security of 6G and how will post-quantum secure cryptography affect the
performance of 6G networks?
• What post-quantum cryptographic primitives will be the optimal choices for 6G?
• Secure remote computations and secure offloading
15. 3.Physical Layer Security solutions and technologies
Section editor: Lorenzo Mucchi
Section contributors: Sara Jayousi, Alessio Martinelli, Stefano Caputo, Jonathan Bechtold, Iván Morales, Andrei Stoica,
Giuseppe Abreu, Shahriar Shahabuddin, Erdal Panayirci, Harald Haas
6G is envisioned to be a full connectivity fabric, whose nodes can span from satellite to inside the human body. This ultra-dense
network of heterogeneous nodes provides tons of information, often extremely sensitive. In this context, full security is a
mandatory feature to let people trust the services. Physical-layer security is the first line of defense, and it can provide security
even to low complex nodes in different scenarios. This chapter discusses about the challenges, solutions and visions of physical-
layer security in beyond-5G systems from several aspects. Section 3.1 discusses the vision of PhySec over 6G and provides, as
an example of application, the human body communications. Section 3.2 discusses the use of PhySec for key distribution, attack
detection and protocols for low-complex D2D communications. Sections 3.3 and 3.4 provide effective implementations of
PhySec, from massive MIMO and intelligent reflecting surfaces to visible-light communications.
3.1. Physical-layer security as confidentiality enabler in 6G connectivity
Moving beyond the 5G technology, 6G will enhance the key performance indicators of 5G, enabling the definition of more
demanding applications, ranging from augmented reality and holographic projection to ultra-sensitive applications. In this
context, a holistic approach of security is required to cope with the plethora of different systems and platforms. The large
amount of the world data collected by networks of sensors (environmental, human-body, etc.) and the mobility features of
most scenarios ask for advanced security techniques that take into account new constraints in terms of device capabilities,
network environment and network dynamic topology [26]. Physical layer security, moving the security strategy at physical layer,
might be one of the confidentiality enablers in 6G connectivity. Its features, combined with the advances in artificial intelligence
algorithms and the trend of distributed computing architectures, can be exploited either to enhance the classical cryptographic
techniques or to meet the security requirements when dealing with simple but sensitive devices which are unable to implement
cryptographic methods, e.g. devices and nano-devices of the internet of things and bio-nano-things where the human inner
bodies become nodes of the future internet [27] (Figure 4).
Figure 4: 6G needs to solve novel physical layer security threats
Computational and energy resources of a network node can be reduced by adapting the security algorithm to the environmental
context where the communication occurs, leading to the definition of a context-aware security approach. The dynamic context
in terms of mobility, network nodes density, frequency spectrum utilization and technology heterogeneity which is envisaged
in 6G scenarios should be taken into account in the definition of security communication strategies both for the identification
of the level of security countermeasure needed in a specific moment and for the exploitation of these environmental
characteristics in the security algorithm definition. Environmental and operational intelligent physical layer security also based
on the adoption of Artificial Intelligence algorithms may lead to a the definition of new techniques that can early detect the
16. need of enhanced security mechanism to be dynamically activated (e.g. based on the battery level of the involved devices or
the degree of trustworthiness of the specific context) and do not considerably affect the transmission spectral efficiency [28].
This approach complies with the main 6G key features that the enabling communication technologies should meet in term of
low energy consumption and long battery life, high affordability and full customization and distributed artificial intelligence
architectures.
Physical layer security addresses one of the most important application of 6G: the human-centric mobile communications. In
this framework, an increasing interest of scientific research has been oriented to wireless body area network and in particular
to on-body and in-body nano-devices, including biochemical communications. In the next future, the human body will be part
of the network architectures, it will be seen as a node of the network or a set of nodes (wearable devices, implantable sensors,
nano-devices, etc.) that collect sensitive information to be exchanged for multiple purposes (e.g. health, statistics, safety, etc.).
By coping with the high security and privacy requirements and the energy and miniaturization constraints of the new
communication terminals the Physical layer security techniques can represent efficient solutions for securing the most critical
and less investigated network segments which are the ones between the body sensors and a sink or a hub node.
Two interesting potential application scenarios for physical layer security in 6G context are Human Bond Communication and
Molecular Communication. The former requires a secure transmission of all the five human senses for replicating human
biological features, allowing disease diagnosis, emotion detection, biological characteristics gathering and human body remote
interaction. While the latter, based on the shifting of the information theory concepts in the biochemical domain
(communications among biological cells inside the human body) requires advanced low-complexity and reliable mechanisms
for securing intra-body communications and enabling trustworthy sensing and actuation in a challenging environment as the
human body is (e.g. secure Internet of bio-nano things) [29]. ETSI SmartBAN group is working on the standardization of security
& privacy for the future body area networks, and physical layer security is one candidate to handle the confidentiality of in- and
on-body devices with typically low resources available. This is important also when 6G will include in- or on-body nodes as part
of the Network (Figure 5).
Figure 5: Human body as part of the global network.
3.2. Distributed and cooperative PHY-security protocols for 6G networks
Besides providing a keyless and innately secure communication channel via maximization of secrecy rate, PLS may also exploit
the intrinsic characteristics of the wireless channel to co-generate a cryptographic key for symmetric encryption. For latency-
constrained communication scenarios and resource-constrained radio devices the secrecy enhancing techniques detailed above
17. become cumbersome or impractical. This is usually the case for high device densities under opportunistic self-organizing
network formation paradigms. State-of-the-art encryption itself is considered unassailable when it comes to data confidentiality
and integrity, however, there exists doubts in the traditional authentication and key distribution design for the future.
PHY-based key generation solutions distinguish themselves from traditional key exchange solutions by being completely
decentralized and not relying on any fixed parameters designed by a particular entity, but rather on the distributed entropy
source that is the wireless channel. So far, in D2D protocols the totality of the raw data needed to synthesize such a key has
not been readily available to higher abstraction levels. In future, newly developed or extended communication protocol
implementations should see PHY-layer attributes (CSI, RSSI, CFO, etc.) of all PHY-exchanges easily available to higher layers,
allowing for a much deeper level of integration, control, and interchangeability of security modules. Such attribute granularity
and unprecedented network visibility at the PHY-level will encourage the development of security and authentication solutions
which leverage these previously unused characteristics. Thus, providing resilience to the existing vulnerabilities that the state-
of-the-art Diffie-Hellman (DH) key exchange algorithm poses [30] as well as provide immunity against the real-time computation
of discrete logarithms that will come about by the time 6G is deployed and quantum computing has matured.
Besides current vulnerabilities at a cryptographic level, more issues arise with future network deployments thanks to the
introduction of D2D communication in 3GPP Release 12 [31], opening the door to Proximity-based services (ProSe) [32]. If a
comprehensive security is not embedded into these services, new attack vectors will arise at the PHY-layer in the form of range
extension/reduction attacks that can spoof distances between devices. With a secure communication link, the available PHY-
layer attributes can then also be used for PHY-threat detection. These can be implemented using classical signal processing
techniques that highlight and discover anomalies in the PHY-attributes of the particular received signal or through the detection
of abnormalities in the packet exchanges.
Such lightweight implementations are ideal for networks of resource-constrained devices; however, the true potential for
threat detection lies in learning (ML), where massively aggregated attributes can be used to train the ML models for monitoring
and classification. The usage of ML methods in networks with high PHY-Attribute visibility will enable real-time PHY-Layer
monitoring and knowledge-based detection, making it highly attractive for leading AI companies to develop Security-as-a-
Service (SecaaS) applications. The deployment of SecaaS applications will be highly dependent on the topology of the networks
to be safeguarded. For instance, in networks with facilitator nodes (and/or gateways) which actively route local packets, such
nodes can be used as data aggregators of the necessary PHY-attributes of communicating devices and their respective links for
active threat detection. Alternatively, a passive observer with higher processing power can be introduced as part of a SecaaS
application, functioning as the aggregator of the exchanged packets to enhance the embedded D2D threat real time detection
capabilities of the network.
Eventually a security paradigm will form in which a great number of highly diversified, independently generated threat
detection models will be formed at each aggregator/node. This diversity of models can then open up the possibility for the
deployment of transfer learning techniques to share learned parameters between adjacent networks in order to detect novel
malicious attacks and prepare networks against attacks like a vaccine would.
3.3. Security of Cell-free Massive MIMO and Intelligent Reflective Surface
The two physical layer technologies that grabbed most attention from the research community are: (1) Cell-free massive MIMO
and (2) Intelligent reflective surface (IRS). They are currently the two strongest candidates for physical layer of 6G
communication systems.
Cell Free Massive MIMO. A large number of antennas are typically used to equip a bulky and expensive massive MIMO BS which
resides on an elevated location, for example, on top of a building, to increase the size of cell radius. A single massive MIMO BS
covers a large number of users from a distance and therefore, large variations of received signal strength exists between
different users [33]. Cell-free massive MIMO is a form of network MIMO where the antennas are not centralized but distributed
among different locations. A central baseband processing unit, which is connected to all the antenna stripes through cables, is
used to perform the necessary baseband signal processing operations [34]. The antenna stripes can be as small as a matchbox
in size and can be integrated in an adhesive tape as displayed by Ericsson at MWC 2019.
The biggest security issue of a cell-free massive MIMO system is the exposed location of radio stripes. A local active attacker
18. may get physical access to the BS and interfere with the internal elements. The attacker may exploit internal lines by direct
wiretapping to inject malicious software and configuration parameters. Due to their vulnerable location, passive attacks, such
as, eavesdropping on authentication keys, user-specific keys and short-term session keys may also become easier. It is rather
easy to destroy a miniature stripe from their exposed physical location than a bulky massive MIMO BS to disrupt the overall
communication. In addition, the use of complex encryption method, to provide data confidentiality between antenna stripes
and central baseband processing unit, is also not possible due to the small size of an antenna stripe.
Intelligent Reflective Surface (IRS) is comprised of an array of IRS units which can be used to change the phase, amplitude, or
frequency of incident signals. Typically, signals transmitted from different antennas are sent towards IRS, which reflects a
beamformed signal towards the legitimate users (Figure 6). Thus, IRS creates an alternative transmission path when the line-
of-sight (LOS) is blocked between the transmitter and receiver. The IRS scheme will be particularly important for high
frequency communications where the penetration loss is significant [35]. Massive MIMO uses techniques like beamforming
and jamming with artificial noise insertion to secure physical layer communications.
Figure 6: MIMO and IRS focusing information to legitimate users while noise-only to eavesdroppers.
However, the achievable secrecy rate is limited even with these techniques when the links of the legitimate user and the
eavesdropper are highly correlated. IRS can be used in such a scenario to constructively add the beamformed signal towards
the user and destructively add towards the eavesdropper. As the signal travels in a NLOS path, it is difficult for the eavesdropper
to detect the incident angle of the signal. However, to make the system secure with IRS, the system needs to detect and locate
the eavesdropper which is not a trivial issue. The IRS controller, which controls the phase of IRS, can be compromised by an
active attacker to focus the beam towards unintended users. If the location of the IRS is exposed, a passive attacker can also
locate itself near the IRS to exploit a correlated channel for eavesdropping.
3.4. Physical Layer Security using Visible Light Communications in 6G
The area of physical layer security (PLS) can play a vital role in reducing both the latency as well as the complexity of novel
security standards. It is expected that the dramatic increase in high data rate services will continue its trend to meet the
demands of 6G networks. Optical Wireless Communications and one of its variants, Visible Light Communications (VLC), offer
attractive features such as high capacity, robustness to electromagnetic interference, a high degree of spatial confinement,
inherent security (Fig. 7) and unlicensed spectrum. VLC is particularly considered as an emerging technology that has been
introduced as a promising solution for 6G. It is a special form of optical wireless communications and uses white-LEDs to encode
data in the optical frequencies and some works have suggested that it is a good candidate to meet the data rate requirements
of 6G. Depending on the intended application, VLC can serve as a powerful complementary technology to the existing ones.
Such as, Wireless Body Area Network (WBAN) and personal area network (PAN), Wireless Local Area Network (WLAN), Vehicular
Area Network (VANET) and Underwater hybrid acoustic/VLC underwater sensor network. VLC will also be useful in scenarios in
19. which traditional RF communication is less effective such as in-cabin internet service in airplanes, underwater communication,
healthcare zones and etc.
Figure 7: Visible light communications (Li-Fi) vs radio frequency communications (Wi-Fi).
During the past few years, PLS in VLC networks has emerged as a promising approach to complement conventional encryption
techniques and provide a first line of defense against eavesdropping attacks. The key idea behind it is to utilize the intrinsic
properties of the VLC channel to realize enhanced physical layer security. The evolution toward 6G wireless communications
poses new and technical challenges which remain unresolved for PLS in VLC research, including physical layer security coding,
massive multiple-input multiple-output, non-orthogonal multiple access, full duplex technology and so on. Moreover, it is not
possible to employ conventional PLS techniques as in RF communications, in fact the most practical communication scheme for
VLC systems is intensity modulation and direct detection. Due to the nature of light, the intensity-modulating data signal must
satisfy a positive-valued amplitude constraint. A brief summary of the PLS enhancement methods proposed for VLC is shown
in Fig. 8, and the details are given in [36-39].
Figure 8: Taxonomy of the PHY layer security for VLC systems
20. 3.5. Research challenges for physical layer security
• Which are the most suitable physical layer features to be exploited for the definition of security algorithms in 6G
challenging heterogeneous environments characterized by high network scalability and different forms of active
malicious attacks?
• How artificial intelligence can be exploited to dynamically tune physical layer security algorithms?
• How to best develop lightweight key distribution and authorization techniques that leverage the previously obscured
PHY-layer attributes, while maintaining ULL QoS?
• What are the relevant, unique dimension reduction / feature extraction methods to enable transfer learning while
maintaining the privacy of aggregator networks over various RF interfaces?
• How to ensure platform security with antennas distributed in different locations?
• How to provide confidentiality between central baseband processing unit and antenna stripes?
• What kind of security mechanisms could be used between the transmitter and the IRS panel and how to ensure security
of IRS controller?
• New and novel algorithms for PLS in multiuser and broadband VLC systems, with new modulation schemes such as
spatial modulations techniques that are derived from it such as index modulation, space shift keying, OFDM-index
modulation techniques (OFDM-IM). Other techniques include optical multiple-input-multiple output with non-
orthogonal multiple excess (NOMA) system.
• The algorithms to be designed have high power efficient and must have the capability to work in multi-user scenarios.
In particular, the artificial jamming signal generation property of these modulation techniques is the most important
advantage in providing PLS compared to the traditional approaches. Moreover, the theoretical methods, to develop
the maximum achievable secrecy capacity and secrecy rate of the physical layer security algorithms will be much
different than the approaches adopted by the by traditional RF systems because of the different system architectures
employed.
• Also, incorporating user mobility and device orientation into the VLC channel models and combining VLC andRF systems
pose new challenges in PLS research and development.
21. 4. Privacy protection in 6G: principles, technologies and regulation
Section editor: Ian Oppermann
Section contributors: Tanesh Kumar, Basak Ozan Ozparlak, Juha Röning
This chapter discusses about the challenges, solutions and visions of privacy protection in beyond 5G systems from several
aspects. Developing a measure of Personal Information (PI) in linked identified data sets used to provide smart services, and a
threshold test for Personally Identifiable Information (PII) which considers personal features, spatial and temporal aspects of
data, a context within which data is captured and analyzed. Use these measures and frameworks to underpin governance
systems which support regulatory requirements for the protection of citizen data in different economies which adopt beyond
5G technology. Moreover, this chapter presents some of the potential privacy-preserving technological candidates that may
be vital for future wireless applications. At the end, some insight is given about standardization and regulatory aspects in the
context of 6G privacy.
4.1. Privacy Requirements in a future hyper-connected mobile world
6G is expected to move us much further towards the ideal of ubiquitous connectivity for a myriad of devices, sensors and
autonomous applications. This creates the fundamental enabler for Future Smart Services for homes, factories, cities, and
governments, which in turn rely on sharing of large volumes of often personal data between individuals and organizations, or
between individuals and governments [40]. A smart light in your home which turns on and off as you move around the house
can provide a more efficient use of energy for lighting, but will use de-identified data about when you are home, which rooms
you use and when, if there are other people in your home, where in your home you spend your time. Within this deidentified
data, there are insights about you, your relationships, habits and preferences. In aggregate form, this data can be used by a
smart lighting provider to deliver more efficiency lighting services to a suburb, or by a smart grid to match energy demand to
energy supply or by a smart micro energy service provider to make best use of spot energy prices.
The benefit is the ability to create locally optimized or individually personalized services based on personal preference, as well
as an understanding of the wider network of users and providers. When we consider just how wide scope “smart” covers in our
personal lives (smart TV, smart scales, smart toilet, smart phone, virtual assistant, smart home, smart car), or in the wider
community (smart grid, smart materials, smart factory, smart city, even smart government), the benefits in terms of improved
efficiency, improved effectiveness and increased personalization to our individual needs can be enormous. If these datasets
are linked, a great of personal information may be contained in the joined data, sufficient to reasonably reidentify individuals
represented in the data. How this data is used and by whom for what purposes creates risks and concerns. In many economies,
it may also force services providers and operators to think about difference governance paradigms to support regulatory
requirements such as GDPR.
With the multidimensional flows of rich data, the challenge is quantifying what deidentified data means, to develop measures
for the level of personal information in a data set at any point in time, and to develop threshold tests for when an individual is
reasonably identifiable (PII) all while considering personal attributes, temporal and spatial aspects of data, and rich contextual
environments. Furthermore, the post 5G smart ecosystem will be a shared network infrastructure where multiple stakeholders
collaboratively provide diverse set of services to the consumers. Therefore, it also opens up the discussion between the trade-
off between managing privacy with building the required trust. As we give more trust to the involved entities/stakeholders, the
risk of privacy leakage increases. Thus 6G will require new trust models along with updated privacy protection approaches to
provide balance between maintaining consumer’s privacy and trust [41, 42].
22. 4.2. How Personal is Information?
The terms personal information (PI) and personally identifiable information (PII) are often used interchangeably in legislative
frameworks as well as in different technical literature. PI is typically described in a way that covers a very wide field, and this
description varies in different parts of the world. For example [43]:
“… personal information means information or an opinion (including information or an opinion forming part of a database and
whether or not recorded in a material form) about an individual whose identity is apparent or can reasonably be ascertained
from the information or opinion” [2 Section 4].
For example, date of birth is considered PI but not PII as it cannot uniquely identify an individual. Similarly, spatial location or
time of service use will not uniquely identify anyone, except in isolated cases. The question becomes, how many features must
be linked before PI becomes PII for an individual known to be in a dataset? Context and rarity play important roles in the answer
to this question. The legal tests for PI generally relate to the situation where an individual's identity can “reasonably be
ascertained”. The definition is very broad and in principle covers any information that relates to an identifiable individual, during
their lifetime or for decades after their death [43]. A recent paper published in Nature Communications [44] provides a means
to “estimate the likelihood of a specific person to be correctly re-identified, even in a heavily incomplete dataset”. The paper
is part of a long series showing that only a small number of features need to be linked to identify an individual from a population.
The degree of PI contained in data may be very high (a unique identifier such as a social security number), moderate (surname),
low (eye color) or very low (month of birth). It is expected that the PIF in a linked dataset will generally increase as more
datasets are linked. Conceptually shown in Figure 9, as more datasets containing PI are linked, a point may be reached where
an individual is personally identifiable (a PIF of 1), or “reasonably” identifiable (a PIF within “epsilon” of 1). The “epsilon” is an
indication of the difference presented by the gap before the “reasonable” threshold is met.
Figure 9: Conceptualization of a PIF and PII threshold point
The focus of this chapter is the call for a quantitative measure and risk framework for “reasonably” in different contexts. In
[45], the authors explored a personal information factor (PIF) which is a measure of the PI contained in a linked, deidentified
dataset or in the outputs of its analysis. A PIF above a certain threshold (for example, 1.0) means sufficient PI exists to identify
an individual: this re-identification risk makes this PII. A value of 0 means there is no PI. It is important to note that the PIF
envisaged is not a technique for anonymization; rather, it is a heuristic measure of potential risk of re-identification and of the
amount of information which would be revealed from re-identification.
The PIF for both data and the outputs of any analysis based on this data are described in using:
• A measure of the information content of the dataset or the output of the analysis of the data
• The smallest unique group in the dataset or output
• Additional information required to identify an individual from data or output (“epsilon”).
There is currently no way to unambiguously determine when linked, deidentified datasets cross the threshold to become
personally identifiable. This is a major, unaddressed problem for many digital technologies from AI, and IoT to communications
23. systems as a whole. Applications are relevant in Smart Healthcare, Industrial Automation, and Smart Transportation. Courts in
different parts of the world are making decisions about whether privacy is being infringed without formal measures of the level
of personal information. This has significant consequences for all future smart services and smart networks.
The relevance specifically for 6G is that, 5G is still largely device / network specific, 6G envisages far more immersive
engagement with the network. This means the focus of privacy will move from human-device-network or machine-device-
network privacy issues to a much richer set of contextual considerations including time/space/usecase/context. This is an issue
which is still to be addressed for 5G. It has largely been ignored to date but GDPR makes it impossible to ignore in future. It is
now the subject of ongoing discussion in the standards world.
4.3. Privacy-Preserving Technologies
As 5G networks evolve, it is expected that there will be increased reliance on AI enabled smart applications requiring situational,
context-aware and customized privacy solutions. Traditional privacy preserving approaches may not be well suited for the
future wireless applications due to a diverse and complex set of novel privacy challenges. One potential solution already
highlighted in chapter 1 is the use of DLT technologies. DLT technologies such as Blockchain may be an enabler for the use of
trustless computing between stakeholders as well as offering privacy protection mechanisms in the network. Blockchain
provides security and privacy features such as immutability, transparency, verifiability, anonymity and pseudonymous among
other. Blockchain can offer privacy-preserving data sharing mechanisms, optimize the authentication and access control,
provide key characteristics such as data integrity, traceability, monitoring, and ensure efficient accountability mechanism
among others.
Privacy protection using differential privacy (DP) approaches also seem promising when addressing key challenges that are
likely to arise in future intelligent 6G wireless applications. DP operates by perturbing the actual data using artificial design
random noise functions before sending the final output to the assigned server [46]. This prevents attackers undertaking a
statistical analysis of the received data and prevents inferring personal information from user’s data. The concepts related to
Federated Learning (FL) are also active topics in the research community for ensuring privacy protection. FL is a distributed
machine learning technique that allows model training for large amounts of data locally on its generated source and the
required modeling is done at each individual learner in the federation. Instead of sending a raw training dataset, each individual
learner transmits their local model to an “aggregator” to build a global model. FL can provide solutions to vital challenges of
data privacy, data ownership and data locality as it follows the approach of “bringing the code to the data, instead of the data
to the code” [47, 48].
4.4. Standardization and Regulatory Aspects
Regulation and standardization work will affect our future technological solutions in 5G networks and beyond. Protection of
individual privacy and identity have long been a challenge for standardization bodies since different nations have widely
different perspectives and regulation in this area. International standards bodies such JTC 1 have committees working on
privacy frameworks and are making progress, but much more remains to be done. Using the European Commission’s framework
of “Privacy by Design” is one way to frame the challenge. The European Commission implemented decision (20.1.2015) states
“The security industry has thus to face a growing challenge: improving the protection of privacy and personal data, while
meeting the requirements of their customers. Whilst legally speaking the customers of the security industry often bear the legal
responsibility for complying with data protection rules (being the data controllers), their providers also bear some responsibility
for data protection from a societal and ethical point of view. These involve those who design technical specifications and those
who actually build or implement applications or operating systems.”
The interconnectedness of global markets means that “Privacy by Design” will likely prevail in many future products and
communication techniques, and impact how we will live. Work in standards groups such as JTC 1/WG 11 (Smart cities) reflect
this when considering future smart cities [49].
24. According to the GDPR, if data is collected directly from the data subject, there is a duty to provide the data immediately (Article
13) to the data subject. If the data is collected from a third party (indirectly from the data subject) the information must be
provided at the latest after a month from the date of collection (Article 14). If the data subject requests the data, it should be
provided upon the request (Article 15). If, as expected, the GDPR continues to provide a data protection framework for 6G, the
digital twins of the data subjects may well be assumed to be data subjects as well as their physical, real world counterparts. If
the realm of virtual reality was deemed to be a public space, a question arises as to which jurisdiction’s laws are applicable. If
this question is left without an answer, the choice may well be determined by the private sector. Big tech companies already
have significant data and control power and are well prepared to decried how the digital world will operate through control of
data and even through digital currencies. If this question is left unanswered; human rights may be jeopardized and 6G may not
achieve the expected social benefits.
A future which sees us working via our digital avatars or by telepresence will also have health and safety issues. While the right
of employees to ‘disconnect’ is beginning to be accepted as a legal norm through some European countries such as France, the
EU is preparing to formalize this [50]. Finland’s Working Hour Act came into force January 2020. This Act allows workers the
right to determine how and where to work for half of their yearly working time. 6G communication is expected to have benefits
for workers on this flexible working system. However, new legal consequences may arise around industrial relations matters in
a digital, mirror workplace where telepresence and avatars are essential parts of the production system where human
employees work in collaboration. Furthermore, the Future digital and physical worlds will be deeply entangled, malicious cyber
activities could lead to loss of property and life. Attribution of responsibility in case of a physical harm caused by a digital twin
or an automated system against a human is a compelling legal issue. A critical question will always remain: Who is liable? After
answering this question the next is the type of liability which will be applied to the case. Liability occurs either from a contractual
relationship or tort or unjust enrichment. Tort on the other hand, may depend on fault (by intention or by negligence) or strict
liability. Multiple liability issues may appear related to Work health and safety issues (physical harm to life of human or to
workplace), data protection and cyber security.
4.5. Research challenges for privacy in 6G
• Develop a measure of Personal Information (PI) in linked identified data sets used to provide smart services
• Develop a threshold test for Personally Identifiable Information (PII)
• Consider the impact of temporal, spatial, contextual settings in the measures of PI
• What can 5G privacy protection approaches offer to 6G systems?
• Develop frameworks to understand the trade-offs between privacy and trust in 6G systems
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