This book summarizes recent inventions, provides guidelines and recommendations, and demonstrates many practical applications of homomorphic encryption. This collection of papers represents the combined wisdom of the community of leading experts on Homomorphic Encryption. In the past 3 years, a global community consisting of researchers in academia, industry, and government, has been working closely to standardize homomorphic encryption. This is the first publication of whitepapers created by these experts that comprehensively describes the scientific inventions, presents a concrete security analysis, and broadly discusses applicable use scenarios and markets. This book also features a collection of privacy-preserving machine learning applications powered by homomorphic encryption designed by groups of top graduate students worldwide at the Private AI Bootcamp hosted by Microsoft Research. The volume aims to connect non-expert readers with this important new cryptographic technology in an accessible and actionable way. Readers who have heard good things about homomorphic encryption but are not familiar with the details will find this book full of inspiration. Readers who have preconceived biases based on out-of-date knowledge will see the recent progress made by industrial and academic pioneers on optimizing and standardizing this technology. A clear picture of how homomorphic encryption works, how to use it to solve real-world problems, and how to efficiently strengthen privacy protection, will naturally become clear.

With the rapid development of big data, it is necessary to transfer the massive data generated by end devices to the cloud under the traditional cloud computing model. However, the delays caused by massive data transmission no longer meet the requirements of various real-time mobile services. Therefore, the emergence of edge computing has been recently developed as a new computing paradigm that can collect and process data at the edge of the network, which brings significant convenience to solving problems such as delay, bandwidth, and off-loading in the traditional cloud computing paradigm. By extending the functions of the cloud to the edge of the network, edge computing provides effective data access control, computation, processing and storage for end devices. Furthermore, edge computing optimizes the seamless connection from the cloud to devices, which is considered the foundation for realizing the interconnection of everything. However, due to the open features of edge computing, such as content awareness, real-time computing and parallel processing, the existing problems of privacy in the edge computing environment have become more prominent. The access to multiple categories and large numbers of devices in edge computing also creates new privacy issues. In this book, we discuss on the research background and current research process of privacy protection in edge computing. In the first chapter, the state-of-the-art research of edge computing are reviewed. The second chapter discusses the data privacy issue and attack models in edge computing. Three categories of privacy preserving schemes will be further introduced in the following chapters. Chapter three introduces the context-aware privacy preserving scheme. Chapter four further introduces a location-aware differential privacy preserving scheme. Chapter five presents a new blockchain based decentralized privacy preserving in edge computing. Chapter six summarize this monograph and propose future research directions. In summary, this book introduces the following techniques in edge computing: 1) describe an MDP-based privacy-preserving model to solve context-aware data privacy in the hierarchical edge computing paradigm; 2) describe a SDN based clustering methods to solve the location-aware privacy problems in edge computing; 3) describe a novel blockchain based decentralized privacy-preserving scheme in edge computing. These techniques enable the rapid development of privacy-preserving in edge computing.

A Wall Street Journal Bestseller 'IT SHOULD BE READ BY ANYONE TRYING TO MAKE SENSE OF GEOPOLITICS TODAY' FINANCIAL TIMES Three of our most accomplished and deep thinkers come together to explore Artificial Intelligence (AI) and the way it is transforming human society - and what it means for us all. An AI learned to win chess by making moves human grand masters had never conceived. Another AI discovered a new antibiotic by analysing molecular properties human scientists did not understand. Now, AI-powered jets are defeating experienced human pilots in simulated dogfights. AI is coming online in searching, streaming, medicine, education, and many other fields and, in so doing, transforming how humans are experiencing reality. In The Age of AI, three leading thinkers have come together to consider how AI will change our relationships with knowledge, politics, and the societies in which we live. The Age of AI is an essential roadmap to our present and our future, an era unlike any that has come before.

Emerging as an effective alternative to organization-based information systems, cloud computing has been adopted by many businesses around the world. Despite the increased popularity, there remain concerns about the security of data in the cloud since users have become accustomed to having control over their hardware and software. Security, Trust, and Regulatory Aspects of Cloud Computing in Business Environments compiles the research and views of cloud computing from various individuals around the world. Detailing cloud security, regulatory and industry compliance, and trust building in the cloud, this book is an essential reference source for practitioners, professionals, and researchers worldwide, as well as business managers interested in an assembled collection of solutions provided by a variety of cloud users.

This book extends the work from introduction of ubiquitous computing, to the Internet of things to security and to privacy aspects of ubiquitous computing. The uniqueness of this book is the combination of important fields like the Internet of things and ubiquitous computing. It assumes that the readers' goal is to achieve a complete understanding of IoT, smart computing, security issues, challenges and possible solutions. It is not oriented towards any specific use cases and security issues; privacy threats in ubiquitous computing problems are discussed across various domains. This book is motivating to address privacy threats in new inventions for a wide range of stakeholders like layman to educated users, villages to metros and national to global levels. This book contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms and protocols. The main endeavour of this book is threat analysis and activity modelling of attacks in order to give an actual view of the ubiquitous computing applications. The unique approach will help readers for a better understanding.

This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology. The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including: deep learning; artificial intelligence; applications of game theory; mixed modality learning; and multi-agent reinforcement learning. Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.

Data collection allows today's businesses to cater to each customer's individual needs and provides a necessary edge in a competitive market. However, any breach in confidentiality can cause serious consequences for both the consumer and the company. The Handbook of Research on Emerging Developments in Data Privacy brings together new ideas on how to deal with potential leaks of valuable customer information. Highlighting the legal aspects of identity protection, trust and security, and detection techniques, this comprehensive work is a valuable resource for any business, legal, or technology professional looking to improve information security within their organization.

This book addresses one of the most overlooked practical, methodological, and moral questions in the journey to secure and handle the massive amount of data being generated from smart devices interactions: the integration of Blockchain with 5G-enabled IoT. After an overview, this book discusses open issues and challenges, which may hinder the growth of Blockchain technology. Then, this book presents a variety of perspectives on the most pressing questions in the field, such as: how IoT can connect billions of objects together; how the access control mechanisms in 5G-enabled industrial environment works; how to address the real-time and quality-of-service requirements for industrial applications; and how to ensure scalability and computing efficiency. Also, it includes a detailed discussions on the complexity of adoption of Blockchain for 5G-Enabled IoT and presents comparative case studies with respect to various performance evaluation metrics such as scalability, data management, standardization, interoperability and regulations, accessibility, human-factors engineering and interfaces, reliability, heterogeneity, and QoS requirements. This book acts as a professional guide for the practitioners in information security and related topics.

This book introduces the state-of-the-art algorithms for data and computation privacy. It mainly focuses on searchable symmetric encryption algorithms and privacy preserving multi-party computation algorithms. This book also introduces algorithms for breaking privacy, and gives intuition on how to design algorithm to counter privacy attacks. Some well-designed differential privacy algorithms are also included in this book. Driven by lower cost, higher reliability, better performance, and faster deployment, data and computing services are increasingly outsourced to clouds. In this computing paradigm, one often has to store privacy sensitive data at parties, that cannot fully trust and perform privacy sensitive computation with parties that again cannot fully trust. For both scenarios, preserving data privacy and computation privacy is extremely important. After the Facebook-Cambridge Analytical data scandal and the implementation of the General Data Protection Regulation by European Union, users are becoming more privacy aware and more concerned with their privacy in this digital world. This book targets database engineers, cloud computing engineers and researchers working in this field. Advanced-level students studying computer science and electrical engineering will also find this book useful as a reference or secondary text.

Data has cemented itself as a building block of daily life. However, surrounding oneself with great quantities of information heightens risks to one's personal privacy. Additionally, the presence of massive amounts of information prompts researchers into how best to handle and disseminate it. Research is necessary to understand how to cope with the current technological requirements. Large-Scale Data Streaming, Processing, and Blockchain Security is a collection of innovative research that explores the latest methodologies, modeling, and simulations for coping with the generation and management of large-scale data in both scientific and individual applications. Featuring coverage on a wide range of topics including security models, internet of things, and collaborative filtering, this book is ideally designed for entrepreneurs, security analysts, IT consultants, security professionals, programmers, computer technicians, data scientists, technology developers, engineers, researchers, academicians, and students.

Breaches and identity theft involving medical data are on the rise. Data security has become especially critical to the healthcare industry as patient privacy hinges on legal compliance and secure adoption of electronic health records. As cyber criminals see medical data as an easy way to illegally obtain medical goods and services or sell sensitive information, major security flaws can pose serious threats to the health and safety of patients. The Handbook of Research on Medical Data Security for Bioengineers seeks to provide a cross-disciplinary forum on research in privacy preserving healthcare systems and engineering applications in medical data security. The goal of the book is to instigate discussion on these critical issues since the success of electronic healthcare applications depends directly on patient security and privacy for ethical and legal reasons. While highlighting topics including data privacy, encryption strategies, and smart health, this book is ideally designed for IT experts, computer engineers, biomedical engineer practitioners, professionals, researchers, and post-doctoral and graduate students.

This book presents high-quality research papers presented at the International Conference on Smart Computing and Cyber Security: Strategic Foresight, Security Challenges and Innovation (SMARTCYBER 2020) held during July 7-8, 2020, in the Department of Smart Computing, Kyungdong University, Global Campus, South Korea. The book includes selected works from academics and industrial experts in the field of computer science, information technology, and electronics and telecommunication. The content addresses challenges of cyber security.

Terroredia is a newly coined term by the editor, Dr. Mahmoud Eid, to explain the phenomenal, yet under-researched relationship between terrorists and media professionals in which acts of terrorism and media coverage are exchanged, influenced, and fueled by one another. Exchanging Terrorism Oxygen for Media Airwaves: The Age of Terroredia provides a timely and thorough discussion on a wide range of issues surrounding terrorism in relation to both traditional and new media. Comprised of insights and research from leading experts in the fields of terrorism and media studies, this publication presents various topics relating to Terroredia: understanding of terrorism and the role of the media, terrorism manifestations and media representations of terrorism, types of terrorism and media stereotypes of terrorism, terrorism tactics and media strategies, the war on terrorism, the function of terrorism and the employment of the media, new terrorism and new media, contemporary cases of terrorist-media interactions, the rationality behind terrorism and counterterrorism, as well as the responsibility of the media. This publication is of interest to government officials, media professionals, researchers, and upper-level students interested in learning more about the complex relationship between terrorism and the media.

Technology has become profoundly integrated into modern society; however, this increases the risk of vulnerabilities, such as hacking and other system errors, along with other online threats. Security, Privacy, and Anonymization in Social Networks: Emerging Research and Opportunities is a pivotal reference source for the most up-to-date research on edge clustering models and weighted social networks. Presenting widespread coverage across a range of applicable perspectives and topics, such as neighborhood attacks, fast k-degree anonymization (FKDA), and vertex-clustering algorithms, this book is ideally designed for academics, researchers, post-graduates, and practitioners seeking current research on undirected networks and greedy algorithms for social network anonymization.

As data mining is one of the most rapidly changing disciplines with new technologies and concepts continually under development, academicians, researchers, and professionals of the discipline need access to the most current information about the concepts, issues, trends, and technologies in this emerging field.""Social Implications of Data Mining and Information Privacy: Interdisciplinary Frameworks and Solutions"" serves as a critical source of information related to emerging issues and solutions in data mining and the influence of political and socioeconomic factors. An immense breakthrough, this essential reference provides concise coverage of emerging issues and technological solutions in data mining, and covers problems with applicable laws governing such issues.

Secret sharing schemes form one of the most important topic in Cryptography. These protocols are used in many areas, applied mathematics, computer science, electrical engineering. A secret is divided into several pieces called shares. Each share is given to a user of the system. Each user has no information about the secret, but the secret can be retrieved by certain authorized coalition of users.This book is devoted to such schemes inspired by Coding Theory. The classical schemes of Shamir, Blakley, Massey are recalled. Survey is made of research in Combinatorial Coding Theory they triggered, mostly self-dual codes, and minimal codes. Applications to engineering like image processing, and key management of MANETs are highlighted.

This book discusses the main legal and economic challenges to the creation and enforcement of security rights in intellectual property and explores possible avenues of reform, such as more specific rules for security in IP rights and better coordination between intellectual property law and secured transactions law. In the context of business financing, intellectual property rights are still only reluctantly used as collateral, and on a small scale. If they are used at all, it is mostly done in the form of a floating charge or some other "all-asset" security right. The only sector in which security rights in intellectual property play a major role, at least in some jurisdictions, is the financing of movies. On the other hand, it is virtually undisputed that security rights in intellectual property could be economically valuable, or even crucial, for small and medium-sized enterprises - especially for start-ups, which are often very innovative and creative, but have limited access to corporate financing and must rely on capital markets (securitization, capital market). Therefore, they need to secure bank loans, yet lack their own traditional collateral, such as land.

Personal Data Privacy and Protection in a Surveillance Era: Technologies and Practices spans a number of interdependent and emerging topics in the area of legal protection of privacy and technology. This book explores the new threats that cyberspace poses to the privacy of individuals, as well as the threats that surveillance technologies generate in public spaces and in digital communication. It examines media practices and privacy frameworks in the fields of copyright, digital management and genetic information. New models of data protection are proposed along with their advantages and disadvantages.

Information security is moving much higher up the agenda of corporate concerns. The pitfalls lying in wait of corporate information are legion. If information is our most important asset, then we must fortify ourselves for the task of protecting it properly. This book is a compilation of contributed chapters by researches and practitioners addressing issues, trends and challenges facing the management of information security in this new millennium. Information Security Management: Global Challenges in the New Millennium focuses on aspects of information security planning, evaluation, design and implementation.

This book addresses privacy in dynamical systems, with applications to smart metering, traffic estimation, and building management. In the first part, the book explores statistical methods for privacy preservation from the areas of differential privacy and information-theoretic privacy (e.g., using privacy metrics motivated by mutual information, relative entropy, and Fisher information) with provable guarantees. In the second part, it investigates the use of homomorphic encryption for the implementation of control laws over encrypted numbers to support the development of fully secure remote estimation and control. Chiefly intended for graduate students and researchers, the book provides an essential overview of the latest developments in privacy-aware design for dynamical systems.

With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals.