The National Security Agency (NSA) -- PRISM Surveillance System _Not a Surprise to Technology Experts
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The National Security Agency's (NSA) surveillance system known as “PRISM” is not a surprise to most Information Technology Experts. In fact, many experts such as the companies (AOL Inc., Apple Inc., Facebook Inc., Google Inc., Microsoft Corp., Yahoo Inc., Skype, YouTube and Paltalk) who shared the information with NSA are trying very hard to mitigate the risks in securing this technology;
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What is the communion act of worship? How does the bread and the wine fit into the symbolism of communion?
Matematica III
La Unión Europea ha acordado un embargo petrolero contra Rusia en respuesta a la invasión de Ucrania. El embargo prohibirá las importaciones marítimas de petróleo ruso a la UE y pondrá fin a las entregas a través de oleoductos dentro de seis meses. Esta medida forma parte de un sexto paquete de sanciones de la UE destinadas a aumentar la presión económica sobre Moscú y privar al Kremlin de fondos para financiar su guerra.
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Are Cloud Applications and Data more Vulnerable to Attacks?
Are Cloud Applications and Data more Vulnerable to Attacks?
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Similar to The National Security Agency (NSA) -- PRISM Surveillance System _Not a Surprise to Technology Experts
Big Data: Privacy and Security Aspects
This document summarizes 10 research papers related to privacy and security aspects of big data. It discusses the key challenges around big data privacy including how large amounts of consumer data collected by companies may be misused and how securely storing and analyzing this information is critical. Various papers propose mechanisms for encrypting data and complying with data privacy laws. Overall, the review finds that big data brings important security and privacy issues given its scale, and continued research is needed to develop solutions that balance data needs with individual privacy.
Fundamentals of data mining and its applications
Data mining involves applying intelligent methods to extract patterns from large data sets. It is used to discover useful knowledge from a variety of data sources. The overall goal is to extract human-understandable knowledge that can be used for decision-making.
The document discusses the data mining process, which typically involves problem definition, data exploration, data preparation, modeling, evaluation, and deployment. It also covers data mining software tools and techniques for ensuring privacy, such as randomization and k-anonymity. Finally, it outlines several applications of data mining in fields like industry, science, music, and more.
Privacy preserving computing and secure multi-party computation ISACA Atlanta
A major challenge that many organizations faces, is how to address data privacy regulations such as CCPA, GDPR and other emerging regulations around the world, including data residency controls as well as enable data sharing in a secure and private fashion. We will present solutions that can reduce and remove the legal, risk and compliance processes normally associated with data sharing projects by allowing organizations to collaborate across divisions, with other organizations and across jurisdictions where data cannot be relocated or shared.
We will discuss secure multi-party computation where organizations want to securely share sensitive data without revealing their private inputs. We will review solutions that are driving faster time to insight by the use of different techniques for privacy-preserving computing including homomorphic encryption, k-anonymity and differential privacy. We will present best practices and how to control privacy and security throughout the data life cycle. We will also review industry standards, implementations, policy management and case studies for hybrid cloud and on-premises.
IABE Big Data information paper - An actuarial perspective
We look closely on the insurance value chain and assess the impact of Big Data on underwriting, pricing and claims reserving. We examine the ethics of Big Data including data privacy, customer identification, data ownership and the legal aspects. We also discuss new frontiers for insurance and its impact on the actuarial profession. Will actuaries will be able to leverage Big Data, create sophisticated risk models and more personalized insurance offers, and bring new wave of innovation to the market?
Appinions Information Technology Influence Study_August 2013
This report explores the companies and executives who are shaping influential conversations in enterprise software.
The study is based on 60 days of data taken between June 4 and August 2, 2013. The scope of this report is based on the most compelling issues around IT, exploring the most influential topics as defined by the upcoming Interop New York conference: Cloud Computing, Big Data, SaaS, Network Infrastructure, Information Security and BYOD.
Data trawling and security strategies
The amount of data in the world seems increasing and computers make it easy to save the data. Companies offer data storage by providing cloud services and the amount of data being stored in these servers is increasing rapidly. In data mining, the data is stored electronically and the search is automated or at least augmented by computer. As the volume of data increases, inexorably, the proportion of it that people understand decreases alarmingly. This paper presents the data leakage problem arises because the services like Facebook and Google store all your data unencrypted on their servers, making it easy for them, or governments and hackers, to monitor the data.
Protecting data privacy in analytics and machine learning ISACA London UK
This document discusses privacy-preserving techniques for machine learning and analytics such as homomorphic encryption, secure multi-party computation, differential privacy, and trusted execution environments. It provides examples of how these techniques can be applied, including allowing sensitive financial and healthcare data to be analyzed while preserving privacy. The document also outlines regulatory requirements around data privacy and international standards that techniques must comply with to protect sensitive information.
Protecting data privacy in analytics and machine learning - ISACA
In this session, we will discuss a range of new emerging technologies for privacy and confidentiality in machine learning and data analytics. We will discuss how to put these technologies to work for databases and other data sources.
When we think about developing AI responsibly, there’s many different activities that we need to think about.
This session also discusses international standards and emerging privacy-enhanced computation techniques, secure multiparty computation, zero trust, cloud and trusted execution environments. We will discuss the “why, what, and how” of techniques for privacy preserving computing.
We will review how different industries are taking opportunity of these privacy preserving techniques. A retail company used secure multi-party computation to be able to respect user privacy and specific regulations and allow the retailer to gain insights while protecting the organization’s IP. Secure data-sharing is used by a healthcare organization to protect the privacy of individuals and they also store and search on encrypted medical data in cloud.
We will also review the benefits of secure data-sharing for financial institutions including a large bank that wanted to broaden access to its data lake without compromising data privacy but preserving the data’s analytical quality for machine learning purposes.
Global Data Management: Governance, Security and Usefulness in a Hybrid World
With Global Data Management methodology and tools, all of your data can be accessed and used no matter where it is or where it is from: on-premises, private cloud, public cloud(s), hybrid cloud, open source, third-party data and any combination of the these, with security, privacy and governance applied as if they were a single entity. Ingenious software products and the economics of computing make it economical to do this. Not free, but feasible.
Putting data science into perspective
What should organizations be concerned about when using Machine Learning for Predictive Modeling techniques? Divergence Academy and Divergence.AI are leading efforts to bring Algorithmic Accountability awareness to masses.
Complete-SRS.doc
The software development process is complete for computer project analysis, and it is important to the evaluation of the random project. These practice guidelines are for those who manage big-data and big-data analytics projects or are responsible for the use of data analytics solutions. They are also intended for business leaders and program leaders that are responsible for developing agency capability in the area of big data and big data analytics .
For those agencies currently not using big data or big data analytics, this document may assist strategic planners, business teams and data analysts to consider the value of big data to the current and future programs.
This document is also of relevance to those in industry, research and academia who can work as partners with government on big data analytics projects.
Technical APS personnel who manage big data and/or do big data analytics are invited to join the Data Analytics Centre of Excellence Community of Practice to share information of technical aspects of big data and big data analytics, including achieving best practice with modeling and related requirements. To join the community, send an email to the Data Analytics Centre of Excellence
UNIT 1 -BIG DATA ANALYTICS Full.pdf
The document discusses the course objectives and topics for CCS334 - Big Data Analytics. The course aims to teach students about big data, NoSQL databases, Hadoop, and related tools for big data management and analytics. It covers understanding big data and its characteristics, unstructured data, industry examples of big data applications, web analytics, and key tools used for big data including Hadoop, Spark, and NoSQL databases.
Big data security
The document discusses three key challenges for data governance and security with big data: 1) ethics and compliance as personally identifiable data is widespread and regulations are increasing, 2) poor data management when there is no clear ownership or lifecycle management of data, and 3) insecure infrastructure as many devices and systems generating data were not designed with security in mind. Effective data governance is important for security, and requires defining responsibilities, auditing data use, and protecting data during collection, storage, and analysis. Technologies can help automate and scale governance, but it is ultimately a combination of people, processes, and tools.
Big data security
There are three key challenges to effective data governance and security in the big data era: 1) ethics and compliance as personally identifiable data is widespread and regulations are increasing, 2) poor data management when there is no clear ownership or lifecycle management of data, and 3) insecure infrastructure as many IoT and other devices were not designed with security in mind. Effective data governance requires a combination of people, processes, and technology to classify, secure, and manage data throughout its lifecycle.
Internet of Things With Privacy in Mind
This document discusses privacy considerations for Internet of Things devices. It notes that IoT devices collect personal data that, even when fragmented, can reveal sensitive information when aggregated and analyzed. Many IoT manufacturers do not adequately explain how they collect, use, store, and allow deletion of personal information. The document advocates adopting privacy by design principles to build privacy protections into IoT technologies from the early stages of development through privacy impact assessments and data protection impact assessments. This helps understand privacy needs, shape better policies, and improve transparency while demonstrating adherence to high data protection standards.
Sqrrl Enterprise: Big Data Security Analytics Use Case
Organizations are utilizing Sqrrl Enterprise to securely integrate vast amounts of multi-structured data (e.g., tens of petabytes) onto a single Big Data platform and then are building real-time applications using this data and Sqrrl Enterprise’s analytical interfaces. The secure integration is enabled by Accumulo’s innovative cell-level security capabilities and Sqrrl Enterprise’s security extensions, such as encryption.
IOT-2016 7-9 Septermber, 2016, Stuttgart, Germany
Charith Perera, Ciaran Mccormick, Arosha Bandara, Blaine A. Price, Bashar Nuseibeh, Privacy-by-Design Framework for Assessing Internet of Things Applications and Platforms, Proceedings of the 6th ACM International Conference on Internet of Things (IoT), Stuttgart, Germany, November, 2016, Pages 83-92
FINAL presentationMay2016
This document summarizes a presentation on privacy, security and ethics related to big data analytics. It discusses several key points:
1. Big data promises new opportunities but also new privacy and surveillance risks due to the vast amount of personal data being collected and analyzed.
2. Privacy risks are best managed proactively through techniques like Privacy by Design which embeds privacy protections from the start of a project.
3. Innovation and privacy are not mutually exclusive; it is possible to gain insights from big data analytics while also protecting privacy through approaches like Privacy by Design.
Data centric security key to digital business success - ulf mattsson - bright...
The document discusses the need for data-centric security strategies to protect sensitive data in digital business systems. As data generation grows exponentially due to technologies like cloud computing, big data, and IoT, cybercriminals have more opportunities. A data-centric approach is needed to merge data security with productivity by controlling access, classifying data, and techniques like encryption, tokenization, and monitoring across structured and unstructured data silos. Solutions that provide centralized security policies and audit/protection of data throughout its entire flow can safely unlock the power of digital business.
A practical data privacy and security approach to ffiec, gdpr and ccpa
With sensitive data residing everywhere, organizations becoming more mobile, and the breach epidemic growing, the need for advanced data privacy and security solutions has become even more critical. French regulators cited GDPR in fining Google $57 million and the U.K.'s Information Commissioner's Office is seeking a $230 million fine against British Airways and seeking $124 million from Marriott. Facebook is setting aside $3 billion to cover the costs of a privacy investigation launched by US regulators.
This session will take a practical approach to address guidance and standards from the Federal Financial Institutions Examination Council (FFIEC), EU GDPR, California CCPA, NIST Risk Management Framework, COBIT and the ISO 31000 Risk management Principles and Guidelines.
Learn how new data privacy and security techniques can help with compliance and data breaches, on-premises, and in public and private clouds.
Similar to The National Security Agency (NSA) -- PRISM Surveillance System _Not a Surprise to Technology Experts (20)
Privacy preserving computing and secure multi-party computation ISACA Atlanta
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IABE Big Data information paper - An actuarial perspective
IABE Big Data information paper - An actuarial perspective
Appinions Information Technology Influence Study_August 2013
Appinions Information Technology Influence Study_August 2013
Protecting data privacy in analytics and machine learning ISACA London UK
Protecting data privacy in analytics and machine learning ISACA London UK
Protecting data privacy in analytics and machine learning - ISACA
Protecting data privacy in analytics and machine learning - ISACA
Global Data Management: Governance, Security and Usefulness in a Hybrid World
Global Data Management: Governance, Security and Usefulness in a Hybrid World
Sqrrl Enterprise: Big Data Security Analytics Use Case
Sqrrl Enterprise: Big Data Security Analytics Use Case
Data centric security key to digital business success - ulf mattsson - bright...
Data centric security key to digital business success - ulf mattsson - bright...
A practical data privacy and security approach to ffiec, gdpr and ccpa
A practical data privacy and security approach to ffiec, gdpr and ccpa
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Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
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Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Choosing The Best AWS Service For Your Website + API.pptx
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
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zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
GNSS spoofing via SDR (Criptored Talks 2024)
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
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Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Inconsistent user experience and siloed data, high costs, and changing customer expectations – Citizens Bank was experiencing these challenges while it was attempting to deliver a superior digital banking experience for its clients. Its core banking applications run on the mainframe and Citizens was using legacy utilities to get the critical mainframe data to feed customer-facing channels, like call centers, web, and mobile. Ultimately, this led to higher operating costs (MIPS), delayed response times, and longer time to market.
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5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
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AppSec PNW: Android and iOS Application Security with MobSF
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HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
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DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
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“How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-eff...
“How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-eff...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
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In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.Main news related to the CCS TSI 2023 (2023/1695)
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The National Security Agency (NSA) -- PRISM Surveillance System _Not a Surprise to Technology Experts
- 1. The National Security Agency (NSA) == PRISM Create Value in Projects The National Security Agency's (NSA) surveillance system known as “PRISM” is not a surprise to most Information Technology Experts. In fact, many experts such as the companies (AOL Inc., Apple Inc., Facebook Inc., Google Inc., Microsoft Corp., Yahoo Inc., Skype, YouTube and Paltalk) who shared the information with NSA are trying very hard to mitigate the risks in securing this technology; however, in order for organizations to protect the people and or consumers within their databases the major stakeholders have to understand, analyze, and define the complexity and the corruption of this technology within different environments and thereby apply the necessary compliance measures and governance. 1) Know your rules and regulations for privacy and sharing of data and the politic and policies behind the regulations. 2) Study the “white papers” such as Gartner “Market Scope for Enterprise File Synchronization and Sharing” published February 12, 2013 and many other white papers on innovative research on technologies. 3) Utilize the Project Management processes for planning your organization compliance implementation 4) Utilize Secure Data Warehousing via Cloud Computing 5) Be Transparent to the public. PRISM’s data sharing should have not been a secret. Core Stakeholders should disclose data sharing networks, companies and or organizations for security surveillance in order to Create Value for their public stakeholders. 6) Create Value Process Environmental Model from “Create Value in Projects” 6.0 Information Environment 6.1 Information Strategy 6.2 Strategy dialogue Among decision makers 6.3 Strategy Survey 6.4 Information Politics 6.5 Information Behavior and Culture 6.6 Management Information Behavior 6.7 Sharing Information 6.8 Handle Information Inspiration (Overload) 6.9 Information Staff 6.10 Information Process 6.10.1 Process Model 6.11 Information Architecture 6.11.1 Other Methods of Information Architecture 7.0 Organizational Environment NSA –PRISM by Sonia Usih June 5, 2013
- 2. The National Security Agency (NSA) == PRISM Create Value in Projects 7.1 Business Situation 7.2 Business Situation Survey 7.3 Technology Investment 7.4 Physical Arrangement 8.0 External Environment 8.1 Business Market 8.2 Technology Market 8.3 Information Market 9.0 Implementation 10.0 Benefits NSA –PRISM by Sonia Usih June 5, 2013