The document discusses frameworks for managing privacy in complex information and communication technology ecosystems like smart cities. It presents standards like ISO/IEC 30145-1 and ISO/IEC 27570 which provide frameworks for smart city business processes and privacy guidelines. It also discusses viewpoints for data sharing agreements between organizations in different ecosystems. A panel discussion addresses questions around what kind of framework is needed to address data protection issues in ecosystems, what kinds of collaboration is required between stakeholders, and how to develop a roadmap and community around privacy engineering.
This document discusses model-driven engineering methods and tools for achieving GDPR compliance through privacy and data protection. It presents an overview of the Privacy and Data Protection for Engineering (PDP4E) project, which aims to develop an integrated framework of engineering processes, methods and tools to support privacy by design. The key processes addressed are risk management, requirements engineering, model-driven design, and assurance. The document describes tools developed by the project for each process and potential future work, such as handling system of systems and sharing tools and models through a community platform.
This document discusses establishing a community and roadmap for a "Privacy-by-Model" initiative. It proposes forming task forces to develop an operational governance model, privacy-by-model processes, and initial application privacy protection and engineering projects. The roadmap outlines working towards commitments and published models by end of 2021, with an announcement at CPDP 2022. The goal is an open repository of privacy models for applications and engineering practices, developed and managed collaboratively.
This document discusses the impact of AI on privacy and data protection. It provides examples of current and upcoming AI applications like autonomous vehicles and drones. It also discusses how AI can both improve processes like risk analysis and cybersecurity lifecycles, but also potentially increase risks through techniques like data poisoning. The document concludes that governance models for AI need empowerment and explainability capabilities to meet privacy requirements.
1) The document discusses the status of privacy engineering standardization and outlines several emerging standards.
2) It notes that privacy engineering standards aim to integrate privacy concerns into system design processes. Approaches discussed include the LINDDUN and DPIA frameworks.
3) The speaker advocates for sharing best practices in privacy engineering to help drive the development of new standards, such as through the IPEN repository of models and use cases.
Main Description of project PDP4E of H2020 which tackle the compliance of GDPR through engineering by providing methods and tools to achieve this goal.
The document discusses frameworks for managing privacy in complex information and communication technology ecosystems like smart cities. It presents standards like ISO/IEC 30145-1 and ISO/IEC 27570 which provide frameworks for smart city business processes and privacy guidelines. It also discusses viewpoints for data sharing agreements between organizations in different ecosystems. A panel discussion addresses questions around what kind of framework is needed to address data protection issues in ecosystems, what kinds of collaboration is required between stakeholders, and how to develop a roadmap and community around privacy engineering.
This document discusses model-driven engineering methods and tools for achieving GDPR compliance through privacy and data protection. It presents an overview of the Privacy and Data Protection for Engineering (PDP4E) project, which aims to develop an integrated framework of engineering processes, methods and tools to support privacy by design. The key processes addressed are risk management, requirements engineering, model-driven design, and assurance. The document describes tools developed by the project for each process and potential future work, such as handling system of systems and sharing tools and models through a community platform.
This document discusses establishing a community and roadmap for a "Privacy-by-Model" initiative. It proposes forming task forces to develop an operational governance model, privacy-by-model processes, and initial application privacy protection and engineering projects. The roadmap outlines working towards commitments and published models by end of 2021, with an announcement at CPDP 2022. The goal is an open repository of privacy models for applications and engineering practices, developed and managed collaboratively.
This document discusses the impact of AI on privacy and data protection. It provides examples of current and upcoming AI applications like autonomous vehicles and drones. It also discusses how AI can both improve processes like risk analysis and cybersecurity lifecycles, but also potentially increase risks through techniques like data poisoning. The document concludes that governance models for AI need empowerment and explainability capabilities to meet privacy requirements.
1) The document discusses the status of privacy engineering standardization and outlines several emerging standards.
2) It notes that privacy engineering standards aim to integrate privacy concerns into system design processes. Approaches discussed include the LINDDUN and DPIA frameworks.
3) The speaker advocates for sharing best practices in privacy engineering to help drive the development of new standards, such as through the IPEN repository of models and use cases.
Main Description of project PDP4E of H2020 which tackle the compliance of GDPR through engineering by providing methods and tools to achieve this goal.
This document summarizes the results of Work Package 6 which developed methods and tools for GDPR compliance through privacy engineering. The key results include:
1) Demonstrating the feasibility of using assurance principles from safety engineering for privacy engineering and modelling privacy regulations as reference frameworks.
2) Developing a tool-supported method for handling multiple privacy reference frameworks using mapping models.
3) Providing reusable privacy assurance patterns contained in a knowledge base, along with reference framework models and mapping models between standards.
4) Releasing tool features and an open source knowledge base to support the privacy assurance method.
This document presents PDP-ReqLite, a lightweight approach for eliciting privacy and data protection requirements from functional requirements. It aims to improve upon existing methods like ProPAn by reducing redundancy, simplifying documentation, and better aligning with legal standards like GDPR. PDP-ReqLite introduces Requirements Data Flow Diagrams and Personal Information Diagrams to model requirements and private data flows. A case study applying the method to a smart grid system is also described. Future work includes expanding the privacy requirement taxonomies, applying the method to more domains, and developing tools to help navigate and prioritize generated requirements.
The document discusses MecaTech, a competitiveness cluster in Belgium that aims to boost activity and employment in the mechanical engineering sector. It does this through large innovative projects combining large companies, SMEs, universities, and research centers. MecaTech has supported 105 projects, invested 290 million euros, and helped create over 2,000 jobs since 2006. It focuses on strategic fields like additive manufacturing and helps companies adopt new technologies to drive productivity and competitiveness.
The document summarizes the LightKone H2020 project, which aims to develop a model for general-purpose computing on edge networks. The project brings together 9 partners over 3 years with a budget of 3.57M€. It combines synchronization-free programming and hybrid gossip techniques to enable applications to run efficiently on heterogeneous edge networks despite their dynamic and unreliable nature. The goal is to address challenges of edge computing like latency, scalability, resilience and security by performing more computations locally at network edges rather than centralized data centers. Several use cases are highlighted like sensor-based management, content search, community network services and factory transportation. Open-source software is being developed to serve both independent edge and hybrid edge-datacenter models.
Towards Large-Scale, High-Density Indoor Ultra Wideband Geolocation SystemsAgence du Numérique (AdN)
This document discusses research into indoor ultra wideband (UWB) geolocation systems being conducted by M. Charlier and B. Quoitin at the University of Mons in Belgium. It describes a UWB-based positioning system with fixed anchors and mobile nodes that can achieve positioning accuracy of centimeters. The research aims to expand this system to cover larger indoor areas with more anchors and mobile nodes, and increase the ranging and positioning rate, potentially using techniques like time-division multiplexing, time difference of arrival, and sensor fusion.
Data Privacy and Security in Autonomous Vehiclessulaiman_karim
1) The document outlines the key components of autonomous vehicles including sensors like LiDAR, RADAR, and GPS that enable autonomous driving capabilities.
2) It discusses the different modes of autonomous vehicles from fully autonomous to driver assistance technologies.
3) The main security challenges for autonomous vehicles are discussed as authentication, availability, integrity, and privacy of data transmitted between vehicles and infrastructure. Attacks on each of these aspects are outlined along with potential solutions.
4) The research scope focuses on improving security for information exchanged between vehicles and infrastructure to address current privacy weaknesses. This will help enable more secure autonomous vehicle connectivity in the future.
The document outlines a method and tools for privacy and data protection by design to help engineers comply with GDPR, including a personal data detector to identify personal data, a privacy model-driven designer to integrate privacy into system models, and a code validation module to verify privacy properties in code. It also discusses how the tools interact and support the overall method, and provides updates on progress and future perspectives of the work.
The document discusses several cybersecurity and cryptography projects in Wallonia, Belgium. It first describes the UserMEDIA and CryptoMEDIA projects, which focus on securing multimedia and media data storage in the cloud. It then discusses the needs of Walloon industrial structures for cryptography expertise in areas like e-voting and lightweight primitives. Finally, it examines the need for specific security mechanisms for internet of things (IoT) communication given constraints like low computer resources and the importance of securing IoT data transmission.
This document summarizes a presentation on the PDP4E-Req tool, which assists engineers in managing GDPR requirements. The tool implements a methodology for requirements engineering targeting privacy and data protection. It includes features such as a dedicated profile implementing GDPR concepts, transformation of functional requirements into a requirements data flow diagram and personal information diagram, validation of models for correctness, and automatic generation of GDPR and data protection requirements with traceability. The tool aims to provide a correct-by-construction approach to eliciting GDPR requirements.
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)ijdms
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
2 nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)ijwscjournal
2
nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a
major forum for the presentation of innovative ideas, approaches, developments, and research
projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange
of information between researchers and industry professionals to discuss the latest issues and
advancement in the area of Cloud, Big Data and IoT.
Applying IoT to the Management of Natural Disasters Risk NIAGRISK - A digital...Agence du Numérique (AdN)
The document discusses NIAGRISK, a digital platform for alerting systems that applies IoT to natural disaster risk management. It integrates real-time and historical data like rainfall and forecasts with maps of slopes, land usage, and elevations. New IoT elements being integrated include sensors for slope monitoring, land movement, soil conditions, and machine learning models. The major challenge is reliable communication and maintenance of the sensor networks.
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)albert ca
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)ijdms
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research
projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
e-SIDES workshop at ICT 2018, Vienna 5/12/2018e-SIDES.eu
This document summarizes a session discussing how to build the next privacy and security research agenda for big data. The session included an introduction, a discussion of the e-SIDES community position paper and process for providing input, a mentimeter voting activity, and a panel on ensuring responsible research and innovation responds to real needs. The panel featured representatives from universities and research organizations discussing issues like integrating privacy from the start, understanding cultural and regional differences, and ensuring research aligns with societal values and needs. The position paper and future research agenda aim to provide recommendations for an ethically sound approach to big data.
2 nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)ijdms
2 nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
6th International Conference on Cryptography and Information Security (CRIS 2...IJNSA Journal
6th International Conference on Cryptography and Information Security (CRIS 2020) provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum. It aims to bring together scientists, researchers and students to exchange novel ideas and results in all aspects of cryptography, coding and Information security.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in applied cryptography and Information security.
Internet of Things is at the top of the Gartner Hype Cyle and scores of entrepreneurs are out building IoT products and solutions. A key question that requires discussion and clarity is – Who will pay for IoT and why? This talk demystifies the novelty of IoT and explains the roles played by various actors in the IoT ecosystem.
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)IJCNCJournal
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
4th International Conference on Cloud, Big Data and IoT (CBIoT 2023)IJMIT JOURNAL
4th International Conference on Cloud, Big Data and IoT (CBIoT 2023) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Cloud, Big Data and IoT.
The slides defines IoT and show the differnce between M2M and IoT vision. It then describes the different layers that depicts the functional architecture of IoT, standard organizations and bodies and other IoT technology alliances, low power IoT protocols, IoT Platform components, and finally gives a short description to one of IoT low power application protocols (MQTT).
This document summarizes the results of Work Package 6 which developed methods and tools for GDPR compliance through privacy engineering. The key results include:
1) Demonstrating the feasibility of using assurance principles from safety engineering for privacy engineering and modelling privacy regulations as reference frameworks.
2) Developing a tool-supported method for handling multiple privacy reference frameworks using mapping models.
3) Providing reusable privacy assurance patterns contained in a knowledge base, along with reference framework models and mapping models between standards.
4) Releasing tool features and an open source knowledge base to support the privacy assurance method.
This document presents PDP-ReqLite, a lightweight approach for eliciting privacy and data protection requirements from functional requirements. It aims to improve upon existing methods like ProPAn by reducing redundancy, simplifying documentation, and better aligning with legal standards like GDPR. PDP-ReqLite introduces Requirements Data Flow Diagrams and Personal Information Diagrams to model requirements and private data flows. A case study applying the method to a smart grid system is also described. Future work includes expanding the privacy requirement taxonomies, applying the method to more domains, and developing tools to help navigate and prioritize generated requirements.
The document discusses MecaTech, a competitiveness cluster in Belgium that aims to boost activity and employment in the mechanical engineering sector. It does this through large innovative projects combining large companies, SMEs, universities, and research centers. MecaTech has supported 105 projects, invested 290 million euros, and helped create over 2,000 jobs since 2006. It focuses on strategic fields like additive manufacturing and helps companies adopt new technologies to drive productivity and competitiveness.
The document summarizes the LightKone H2020 project, which aims to develop a model for general-purpose computing on edge networks. The project brings together 9 partners over 3 years with a budget of 3.57M€. It combines synchronization-free programming and hybrid gossip techniques to enable applications to run efficiently on heterogeneous edge networks despite their dynamic and unreliable nature. The goal is to address challenges of edge computing like latency, scalability, resilience and security by performing more computations locally at network edges rather than centralized data centers. Several use cases are highlighted like sensor-based management, content search, community network services and factory transportation. Open-source software is being developed to serve both independent edge and hybrid edge-datacenter models.
Towards Large-Scale, High-Density Indoor Ultra Wideband Geolocation SystemsAgence du Numérique (AdN)
This document discusses research into indoor ultra wideband (UWB) geolocation systems being conducted by M. Charlier and B. Quoitin at the University of Mons in Belgium. It describes a UWB-based positioning system with fixed anchors and mobile nodes that can achieve positioning accuracy of centimeters. The research aims to expand this system to cover larger indoor areas with more anchors and mobile nodes, and increase the ranging and positioning rate, potentially using techniques like time-division multiplexing, time difference of arrival, and sensor fusion.
Data Privacy and Security in Autonomous Vehiclessulaiman_karim
1) The document outlines the key components of autonomous vehicles including sensors like LiDAR, RADAR, and GPS that enable autonomous driving capabilities.
2) It discusses the different modes of autonomous vehicles from fully autonomous to driver assistance technologies.
3) The main security challenges for autonomous vehicles are discussed as authentication, availability, integrity, and privacy of data transmitted between vehicles and infrastructure. Attacks on each of these aspects are outlined along with potential solutions.
4) The research scope focuses on improving security for information exchanged between vehicles and infrastructure to address current privacy weaknesses. This will help enable more secure autonomous vehicle connectivity in the future.
The document outlines a method and tools for privacy and data protection by design to help engineers comply with GDPR, including a personal data detector to identify personal data, a privacy model-driven designer to integrate privacy into system models, and a code validation module to verify privacy properties in code. It also discusses how the tools interact and support the overall method, and provides updates on progress and future perspectives of the work.
The document discusses several cybersecurity and cryptography projects in Wallonia, Belgium. It first describes the UserMEDIA and CryptoMEDIA projects, which focus on securing multimedia and media data storage in the cloud. It then discusses the needs of Walloon industrial structures for cryptography expertise in areas like e-voting and lightweight primitives. Finally, it examines the need for specific security mechanisms for internet of things (IoT) communication given constraints like low computer resources and the importance of securing IoT data transmission.
This document summarizes a presentation on the PDP4E-Req tool, which assists engineers in managing GDPR requirements. The tool implements a methodology for requirements engineering targeting privacy and data protection. It includes features such as a dedicated profile implementing GDPR concepts, transformation of functional requirements into a requirements data flow diagram and personal information diagram, validation of models for correctness, and automatic generation of GDPR and data protection requirements with traceability. The tool aims to provide a correct-by-construction approach to eliciting GDPR requirements.
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)ijdms
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
2 nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)ijwscjournal
2
nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a
major forum for the presentation of innovative ideas, approaches, developments, and research
projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange
of information between researchers and industry professionals to discuss the latest issues and
advancement in the area of Cloud, Big Data and IoT.
Applying IoT to the Management of Natural Disasters Risk NIAGRISK - A digital...Agence du Numérique (AdN)
The document discusses NIAGRISK, a digital platform for alerting systems that applies IoT to natural disaster risk management. It integrates real-time and historical data like rainfall and forecasts with maps of slopes, land usage, and elevations. New IoT elements being integrated include sensors for slope monitoring, land movement, soil conditions, and machine learning models. The major challenge is reliable communication and maintenance of the sensor networks.
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)albert ca
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)ijdms
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research
projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
e-SIDES workshop at ICT 2018, Vienna 5/12/2018e-SIDES.eu
This document summarizes a session discussing how to build the next privacy and security research agenda for big data. The session included an introduction, a discussion of the e-SIDES community position paper and process for providing input, a mentimeter voting activity, and a panel on ensuring responsible research and innovation responds to real needs. The panel featured representatives from universities and research organizations discussing issues like integrating privacy from the start, understanding cultural and regional differences, and ensuring research aligns with societal values and needs. The position paper and future research agenda aim to provide recommendations for an ethically sound approach to big data.
2 nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)ijdms
2 nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
6th International Conference on Cryptography and Information Security (CRIS 2...IJNSA Journal
6th International Conference on Cryptography and Information Security (CRIS 2020) provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum. It aims to bring together scientists, researchers and students to exchange novel ideas and results in all aspects of cryptography, coding and Information security.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in applied cryptography and Information security.
Internet of Things is at the top of the Gartner Hype Cyle and scores of entrepreneurs are out building IoT products and solutions. A key question that requires discussion and clarity is – Who will pay for IoT and why? This talk demystifies the novelty of IoT and explains the roles played by various actors in the IoT ecosystem.
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)IJCNCJournal
2nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
4th International Conference on Cloud, Big Data and IoT (CBIoT 2023)IJMIT JOURNAL
4th International Conference on Cloud, Big Data and IoT (CBIoT 2023) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Cloud, Big Data and IoT.
The slides defines IoT and show the differnce between M2M and IoT vision. It then describes the different layers that depicts the functional architecture of IoT, standard organizations and bodies and other IoT technology alliances, low power IoT protocols, IoT Platform components, and finally gives a short description to one of IoT low power application protocols (MQTT).
This document presents a project on developing a security-oriented cloud computing platform for critical infrastructures. It includes an introduction to cloud computing and critical infrastructures. It discusses problems in migrating critical infrastructures to the cloud, specifically security issues. It then outlines the methodology, including using trusted computing platforms, protecting data in cloud platforms, and securing the cloud network. It also includes a case study on a Parkinson's disease app and concludes that secure cloud platforms are important for critical infrastructure adoption of cloud services.
A key initiative of Europe is to accelerate the deployment of Data Spaces in different domains. Manufacturing Data Spaces are among the top 9 priorities set by the EC.
Data sharing among manufacturing companies and with (service) providers will be increasing in the near future, demonstrating how sharing industrial data improves company operations. Both the discrete manufacturing and process industry are impacted by such a transformation.
Consequently, the priority for manufacturing stakeholders will be to develop collaborative services based on a trusted and common framework for sharing and exchanging data and models multilaterally to overcome the interoperability challenge and implement next generation autonomous cross-enterprise industrial operations.
Currently approaches to Digital Manufacturing Platforms (DMP) and Industrial Data Platforms (IDP) do lack the ability to consistently share data across organisations at scale. In fact, it is already acknowledged that peer-to-peer data sharing, especially when involving SMEs, will not scale to unveil high-quality data sharing for manufacturing value set above.
The FIWARE Smart Industry Mission Support Committee (SIMSC) is playing a major role in this twin and green transition, facilitating the definition and adoption of common protocol and data models, as well as the spreading of enabling technologies such as Digital Twins and Artificial Intelligence. The session will drive you through the context analysis, the needs and benefits, the technologies adoption in relevant use cases and the offering of Testing and Experimental Facilities in several industrial domains.
BDE-BDVA Webinar: BigDataEurope Overview & Synergies with BDVABigData_Europe
The document discusses BigDataEurope, a H2020 CSA project that aims to lower barriers for using big data technologies and demonstrate societal value through 7 pilot use cases. It describes the Integrator Platform, which provides a flexible, generic platform for deploying big data value chains using open source solutions. The platform has been instantiated 7 times for the pilot uses cases. It also discusses synergies between BigDataEurope and the Big Data Value Association (BDVA) in advancing big data technical priorities.
2 nd International Conference on Cloud, Big Data and IoT (CBIoT 2021)ijwscjournal
2
nd International Conference on Cloud, Big Data and IoT (CBIoT 2021) will act as a
major forum for the presentation of innovative ideas, approaches, developments, and research
projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange
of information between researchers and industry professionals to discuss the latest issues and
advancement in the area of Cloud, Big Data and IoT.
Call for paper - 3rd International Conference on Cloud, Big Data and IoT (CBI...ijgca
The 3rd International Conference on Cloud, Big Data and IoT (CBIoT 2022) will be held from July 23-24, 2022 in Toronto, Canada. The conference aims to facilitate the exchange of information between researchers and industry professionals on topics related to cloud computing, big data, and IoT. Authors are invited to submit papers by May 28, 2022 on research results, projects, surveys, and case studies within areas of cloud, big data, and IoT. Selected papers will be published in conference proceedings and various related journals.
This document presents the Unicorn Reference Architecture which is comprised of three layers: 1) the Unicorn Cloud IDE Plugin built on Eclipse Che, 2) the Unicorn Platform which validates applications, enforces policies, and manages the application lifecycle, and 3) the Multi-Cloud Execution Environment using Docker, CoreOS, Kubernetes, and Arcadia Smart Orchestrator. It defines Unicorn microservices and describes how the layers interact to deploy and manage applications across multiple clouds. The document also presents Unicorn use cases, demonstrators, and how the project will contribute to open source.
PAPER SUBMISSION START NOW-4th International Conference on Cloud, Big Data an...IJDKP
4th International Conference on Cloud, Big Data and IoT (CBIoT 2023)
July 29 ~ 30, 2023, London, United Kingdom
Webpage URL:
https://itcse2023.org/cbiot/index
Submission Deadline: July 01, 2023
Contact us:
Here's where you can reach us: cbiot@itcse2023.org (or) cbiot.conf@yahoo.com
Submission URL:
https://itcse2023.org/submission/index.php
C|CSE by EC-Council is the first certification to offer a blend of vendor-neutral and vendor-specific concepts. Checkout this brochure to know more about cloud security and it's importance. Also here you will find C|CSE training and exam details. For more details visit: https://bit.ly/3cuw4vj
3rd International Conference on Cloud, Big Data and IoT (CBIoT 2022)ijccsa
3rd International Conference on Cloud, Big Data and IoT (CBIoT 2022) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT
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.
3rd International Conference on Cloud, Big Data and IoT (CBIoT 2022)ijccsa
The 3rd International Conference on Cloud, Big Data and IoT (CBIoT 2022) will be held on July 23-24, 2022 in Toronto, Canada. The conference aims to facilitate the exchange of information between researchers and industry professionals on topics related to cloud computing, big data, and IoT. Authors are invited to submit papers by April 23, 2022 presenting research, projects, case studies, and experiences on cloud, big data, and IoT topics. Selected papers will be published in conference proceedings and considered for publication in related journals.
Call for Paper - 3rd International Conference on Cloud, Big Data and IoT (CBI...ijgca
3rd International Conference on Cloud, Big Data and IoT (CBIoT 2022) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
3 rd International Conference on Cloud, Big Data and IoT (CBIoT 2022)ijgca
3
rd International Conference on Cloud, Big Data and IoT (CBIoT 2022) will act as a
major forum for the presentation of innovative ideas, approaches, developments, and research
projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange
of information between researchers and industry professionals to discuss the latest issues and
advancement in the area of Cloud, Big Data and IoT.
3 rd International Conference on Cloud, Big Data and IoT (CBIoT 2022)ijgca
3
rd International Conference on Cloud, Big Data and IoT (CBIoT 2022) will act as a
major forum for the presentation of innovative ideas, approaches, developments, and research
projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange
of information between researchers and industry professionals to discuss the latest issues and
advancement in the area of Cloud, Big Data and IoT.
Call for Paper - 3rd International Conference on Cloud, Big Data and IoT (CBI...ijgca
3rd International Conference on Cloud, Big Data and IoT (CBIoT 2022)
July 23 ~ 24, 2022, Toronto, Canada
https://www.itcse2022.org/cbiot/index
Submission Deadline: April 09, 2022
Contact us:
Here's where you can reach us: cbiot@itcse2022.org (or) cbiot.conf@yahoo.com
Submission Link:
https://www.itcse2022.org/submission/index.php
The document summarizes various technologies used for cloud computing security. It discusses three main methods: data splitting, data anonymization, and cryptographic techniques.
Data splitting involves separating confidential data into fragments that are stored in different locations. Data anonymization irreversibly hides data to protect sensitive information while still allowing analysis. Cryptographic techniques like encryption can be used to encrypt data before outsourcing, but limit cloud capabilities unless advanced encryption methods are used.
The document compares the advantages and disadvantages of each method for security, overhead, functionality, and key criteria. It provides an overview of approaches for maintaining data security in cloud computing.
Similar to Long term security evolution of ai and data protection antonio kung trialog pdp4 e (20)
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Long term security evolution of ai and data protection antonio kung trialog pdp4 e
1. Methods and Tools for GDPR Compliance through
Privacy and Data
Protection 4 Engineering
Long term security evolution of AI
and data protection
Antonio Kung
Trialog, 25 rue du Général Foy 75008 Paris
antonio.kung@trialog.com
26 March 2021 Long-term security evolution of AI and data protection Slide 1
This project has received funding from the European
Union’s Horizon 2020 research and innovation
programme under grant agreement No 787034
2. Long term security evolution of AI and
data protection
❑Background
❑Characterisation of AI-based systems
❑Long term security evolution
❑Using models
26 March 2021 Long-term security evolution of AI and data protection Slide 2
3. Background
❑Embedded systems, Cyberphysical systems, Internet of things
❑Various domains
❑Privacy
❑Security
❑Trustworthiness
❑Interoperability
❑Architecture
❑AI
❑Involvement in standards
❑Guidance for organisations
❑Guidance for ecosystems
26 March 2021 Long-term security evolution of AI and data protection 3
https://edps.europa.eu/data-protection/ipen-internet-privacy-engineering-network_en
https://ipen.trialog.com/wiki/Wiki_for_Privacy_Standards_and_Privacy_Projects
4. Background on AI
❑Study impact of AI on security and privacy (ISO/IEC SC27)
❑Study 132 use cases (ISO/IEC 24030 AI use cases)
❑Guidance for security
❑Guidance for privacy
❑Study impact of AI on an ICT domain (ISO TC215)
❑Impact of AI on health ICT
❑Impact of AI on health ICT systems
❑Study impact of AI on architecture (ISO/IEC AG8)
❑For instance alignment of IoT reference architecture with Knowledge
engineering reference architecture
26 March 2021 Long-term security evolution of AI and data protection 4
5. Long term security evolution of AI and
data protection
❑Background
❑Characterisation of AI-based systems
❑Long term security evolution
❑Using models
26 March 2021 Long-term security evolution of AI and data protection Slide 5
6. AI based applications
❑Current wave
❑Automatic speech recognition
❑Machine translation
❑Spam filters
❑Search engines
❑…
❑Upcoming wave
❑Autonomous cars
❑Robots for elderly people
❑Autonomous drones
❑…
26 March 2021 Long-term security evolution of AI and data protection 6
7. Ecosystem Perspective
Example of cooperative ITS
26 March 2021 Long-term security evolution of AI and data protection 7
Pseudonymization authority
Road side unit
Sending vehicle
Receiving vehicle
8. Ecosystem Perspective
Example of cooperative ITS
26 March 2021 Long-term security evolution of AI and data protection 8
PKI operator
Vehicle
operator
Use case
operator
AI capability
(e.g. autonomous
driving)
AI capability
(e.g. autonomous
driving)
9. Lifecycle Perspective
26 March 2021 Long-term security evolution of AI and data protection Slide 9
AI system design &
implementation
AI system training
AI system
integration into
SoS
SoS operation
Training data Application data
Continuous improvement
10. Governance Perspective
26 March 2021 Long-term security evolution of AI and data protection 10
to
on
Governance body
Governed subject Policies
follows
Monitors Establishes
11. Governance Perspective
26 March 2021 Long-term security evolution of AI and data protection 11
to
on
Governance body
AI-based
Autonomous
System
Policies
follows
Monitors Establishes
12. Long term security evolution of AI and
data protection
❑Background
❑Characterisation of AI-based systems
❑Long term security evolution
❑Using models
26 March 2021 Long-term security evolution of AI and data protection Slide 12
13. Ecosystem Perspective
Example of cooperative ITS
26 March 2021 Long-term security evolution of AI and data protection 13
PKI operator
Vehicle
operator
Use case
operator
AI capability
(e.g. autonomous
driving)
AI capability
(e.g. autonomous
driving)
14. Lifecycle Perspective
26 March 2021 Long-term security evolution of AI and data protection Slide 14
AI system design &
implementation
AI system training
AI system
integration into
SoS
SoS operation
Training data Application data
Continuous improvement
15. Governance Perspective
26 March 2021 Long-term security evolution of AI and data protection 15
Governance body
AI-based
Autonomous
System
Policies
follows
Monitors Establishes
17. Long term security evolution of AI and
data protection
❑Background
❑Characterisation of AI-based systems
❑Long term security evolution
❑Using models
26 March 2021 Long-term security evolution of AI and data protection Slide 17
18. Using Models
26 March 2021 Long-term security evolution of AI and data protection Slide 18
Model engineering
constructing proportionally-scaled
miniature working representations
of full-sized machines
Model driven engineering
expressing specifications
through processable models.
Diagram orientation (e.g. UML diagrams)
Source wikipedia
20. Community of BAMs
❑Best Available protection Models (BAM)
❑most effective and advanced capabilities
❑suitable in practice for privacy compliance
❑designed to address risks on privacy and security.
❑Analogy with best available techniques
26 March 2021 Long-term security evolution of AI and data protection Slide 20
21. There is a need for many BAMs
26 March 2021 Long-term security evolution of AI and data protection Slide 21
Consumer applications
Protection models
AI in
Health
AI in Social
network
AI in
Mobility
AI in Smart
home
AI in
Fintech
…
IoT applications
Protection models
AI in
Connected
vehicles
AI in E-
mobility
AI in Smart
energy
AI in
Assisted
Living
AI in
Security
…
Data processing
Protection models
22. Application developer
reuses a BAM and its implementation
26 March 2021 Long-term security evolution of AI and data protection Slide 22
Reuses
Application developer
Open community
repository
Open
source
Guidance
BAM
23. Application developer
develop a BAM
26 March 2021 Long-term security evolution of AI and data protection Slide 23
Submits
Open community
repository
Open
source
Modelling tools
Uses
Privacy
engineering tools
Application developer
Guidance
BAM
24. Eclipse Privacy-by-model Community
26 March 2021 Long-term security evolution of AI and data protection Slide 24
Stakeholders
Privacy model expert
PbM Steering committee
(1) Provides
Guidance for models
(3) Provides
model
(3) Provides
model
Stakeholders
Application privacy protection
Project Task force
Stakeholders
Privacy engineering project
Task force
(2) Uses
(2) Uses
Stakeholders
Privacy model expert
PbM Validation committee
(4)Validates
model
(4) Validates
model
Best
Available
Models
(5) Publishes
model
25. Join the future Privacy-by-model
community!
Philippe Krief: philippe.krief@eclipse-foundation.org
Antonio Kung: antonio.kung@trialog.com
Samuel Martin: ys.martin@upm.es
26 March 2021 Long-term security evolution of AI and data protection Slide 25
This project has received funding from the European
Union’s Horizon 2020 research and innovation
programme under grant agreement No 787034