This book provides an opportunity for investigators, government officials, systems scientists, strategists, assurance researchers, owners, operators and maintainers of large, complex and advanced systems and infrastructures to update their knowledge with the state of best practice in the challenging domains whilst networking with the leading representatives, researchers and solution providers. Drawing on 12 years of successful events on information security, digital forensics and cyber-crime, the 13th ICGS3-20 conference aims to provide attendees with an information-packed agenda with representatives from across the industry and the globe. The challenges of complexity, rapid pace of change and risk/opportunity issues associated with modern products, systems, special events and infrastructures. In an era of unprecedented volatile, political and economic environment across the world, computer-based systems face ever more increasing challenges, disputes and responsibilities, and whilst the Internet has created a global platform for the exchange of ideas, goods and services, it has also created boundless opportunities for cyber-crime. As an increasing number of large organizations and individuals use the Internet and its satellite mobile technologies, they are increasingly vulnerable to cyber-crime threats. It is therefore paramount that the security industry raises its game to combat these threats. Whilst there is a huge adoption of technology and smart home devices, comparably, there is a rise of threat vector in the abuse of the technology in domestic violence inflicted through IoT too. All these are an issue of global importance as law enforcement agencies all over the world are struggling to cope.

This book provides extensive insights on blockchain systems, starting from a historical perspective and moving towards building foundational knowledge, with focus on communication networks. It covers blockchain applications, algorithms, architectures, design and implementation, and security and privacy issues, providing the reader with a comprehensive overview. Further, it discusses blockchain systems and its integration to communication networks. The book includes hands-on, practical tutorials, self-assessment exercises, and review questions; tips and sample programs are also provided throughout. Complementary supporting material for instructors, including open source programming code for practical tutorials and exercises, is also available. The target audience includes graduate students, professionals, and researchers working in the areas of blockchain systems, distributed ledger technology, computer networks and communications, artificial intelligence, and cybersecurity.

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.

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 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.

Shortly after it was first introduced in 2006, differential privacy became the flagship data privacy definition. Since then, numerous variants and extensions were proposed to adapt it to different scenarios and attacker models. In this work, we propose a systematic taxonomy of these variants and extensions. We list all data privacy definitions based on differential privacy, and partition them into seven categories, depending on which aspect of the original definition is modified. These categories act like dimensions: Variants from the same category cannot be combined, but variants from different categories can be combined to form new definitions. We also establish a partial ordering of relative strength between these notions by summarizing existing results. Furthermore, we list which of these definitions satisfy some desirable properties, like composition, post-processing, and convexity by either providing a novel proof or collecting existing ones.

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.

This book constitutes the proceedings of the 28th International Conference on Web Services, ICWS 2021, held virtually as part of SCF 2021, during December 10-14, 2021. The 7 full papers presented in this volume were carefully reviewed and selected from numerous submissions. The papers cover aspects of services computing and applications. Centered around services computing, it covers various systems and networking research pertaining to cloud, edge and Internet-of-Things (IoT), as well as technologies for intelligent computing, learning, big data and blockchain applications.

Tools and technologies have long complemented and extended our physical abilities: from pre-historic spearheads to steam-propelled ploughs and high-tech prosthetics. While the development of lenses granted us insights into the micro and macrocosms, new sensors and technologies increasingly augment our cognitive abilities, including memory and perception. This book integrates current research efforts, results, and visions from the fields of computer science, neuroscience, and psychology. It provides a comprehensive overview of the state-of-the-art and future applications of how technologies assist and augment human perception and cognition. Experts in the field share their research and findings on: Working memory enhancements Digitization of memories through lifelog archives The consequences of technology-induced disruptions and forgetting The creation and utilization of new human senses Ethical and security concerns that arise with augmentation technologies. As technology weaves itself ever deeper into our lives, careful examination of its capabilities, risks and benefits is warranted. While this book focuses on the complementation and augmentation of human capabilities, it serves as a foundation for students, researchers and designers of technologies that push the boundaries of perception and cognition.

This book constitutes the thoroughly refereed post conference papers of the Third International Conference on Blockchain and Trustworthy Systems, Blocksys 2021, held in Guangzhou, China, in August 2021.*The 38 full papers and the 12 short papers were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections: Contents Blockchain and Data Mining; Performance Optimization of Blockchain; Blockchain Security and Privacy; Theories and Algorithms for Blockchain; Blockchain and Internet of Things; Blockchain and Smart Contracts; Blockchain Services and Applications; Trustworthy System Development.*

This open access book aims to set an agenda for research and action in the field of Digital Humanism through short essays written by selected thinkers from a variety of disciplines, including computer science, philosophy, education, law, economics, history, anthropology, political science, and sociology. This initiative emerged from the Vienna Manifesto on Digital Humanism and the associated lecture series. Digital Humanism deals with the complex relationships between people and machines in digital times. It acknowledges the potential of information technology. At the same time, it points to societal threats such as privacy violations and ethical concerns around artificial intelligence, automation and loss of jobs, ongoing monopolization on the Web, and sovereignty. Digital Humanism aims to address these topics with a sense of urgency but with a constructive mindset. The book argues for a Digital Humanism that analyses and, most importantly, influences the complex interplay of technology and humankind toward a better society and life while fully respecting universal human rights. It is a call to shaping technologies in accordance with human values and needs.

This book revises the strategic objectives of Information Warfare, interpreting them according to the modern canons of information age, focusing on the fabric of society, the economy, and critical Infrastructures. The authors build plausible detailed real-world scenarios for each entity, showing the related possible threats from the Information Warfare point of view. In addition, the authors dive into the description of the still open problems, especially when it comes to critical infrastructures, and the countermeasures that can be implemented, possibly inspiring further research in the domain. This book intends to provide a conceptual framework and a methodological guide, enriched with vivid and compelling use cases for the readers (e.g. technologists, academicians, military, government) interested in what Information Warfare really means, when its lenses are applied to current technology. Without sacrificing accuracy, rigor and, most importantly, the big picture of Information Warfare, this book dives into several relevant and up-to-date critical domains. The authors illustrate how finance (an always green target of Information Warfare) is intertwined with Social Media, and how an opponent could exploit these latter ones to reach its objectives. Also, how cryptocurrencies are going to reshape the economy, and the risks involved by this paradigm shift. Even more compelling is how the very fabric of society is going to be reshaped by technology, for instance how our democratic elections are exposed to risks that are even greater than what appears in the current public discussions. Not to mention how our Critical Infrastructure is becoming exposed to a series of novel threats, ranging from state-supported malware to drones. A detailed discussion of possible countermeasures and what the open issues are for each of the highlighted threats complete this book. This book targets a widespread audience that includes researchers and advanced level students studying and working in computer science with a focus on security. Military officers, government officials and professionals working in this field will also find this book useful as a reference.

This book provides the state-of-the-art development on security and privacy for fog/edge computing, together with their system architectural support and applications. This book is organized into five parts with a total of 15 chapters. Each area corresponds to an important snapshot. The first part of this book presents an overview of fog/edge computing, focusing on its relationship with cloud technology and the future with the use of 5G communication. Several applications of edge computing are discussed. The second part of this book considers several security issues in fog/edge computing, including the secure storage and search services, collaborative intrusion detection method on IoT-fog computing, and the feasibility of deploying Byzantine agreement protocols in untrusted environments. The third part of this book studies the privacy issues in fog/edge computing. It first investigates the unique privacy challenges in fog/edge computing, and then discusses a privacy-preserving framework for the edge-based video analysis, a popular machine learning application on fog/edge. This book also covers the security architectural design of fog/edge computing, including a comprehensive overview of vulnerabilities in fog/edge computing within multiple architectural levels, the security and intelligent management, the implementation of network-function-virtualization-enabled multicasting in part four. It explains how to use the blockchain to realize security services. The last part of this book surveys applications of fog/edge computing, including the fog/edge computing in Industrial IoT, edge-based augmented reality, data streaming in fog/edge computing, and the blockchain-based application for edge-IoT. This book is designed for academics, researchers and government officials, working in the field of fog/edge computing and cloud computing. Practitioners, and business organizations (e.g., executives, system designers, and marketing professionals), who conduct teaching, research, decision making, and designing fog/edge technology will also benefit from this book The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, and information systems, but also applies to students in business, education, and economics, who would benefit from the information, models, and case studies therein.

This textbook provides a unique lens through which the myriad of existing Privacy Enhancing Technologies (PETs) can be easily comprehended and appreciated. It answers key privacy-centered questions with clear and detailed explanations. Why is privacy important? How and why is your privacy being eroded and what risks can this pose for you? What are some tools for protecting your privacy in online environments? How can these tools be understood, compared, and evaluated? What steps can you take to gain more control over your personal data? This book addresses the above questions by focusing on three fundamental elements: It introduces a simple classification of PETs that allows their similarities and differences to be highlighted and analyzed; It describes several specific PETs in each class, including both foundational technologies and important recent additions to the field; It explains how to use this classification to determine which privacy goals are actually achievable in a given real-world environment. Once the goals are known, this allows the most appropriate PETs to be selected in order to add the desired privacy protection to the target environment. To illustrate, the book examines the use of PETs in conjunction with various security technologies, with the legal infrastructure, and with communication and computing technologies such as Software Defined Networking (SDN) and Machine Learning (ML). Designed as an introductory textbook on PETs, this book is essential reading for graduate-level students in computer science and related fields, prospective PETs researchers, privacy advocates, and anyone interested in technologies to protect privacy in online environments.

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.

This book outlines the legal powers of a major Western nation - Australia - to collect and use location information. Mobile service and social media service providers now have the ability to track, record and store more precise location information. Unlike 4G, 5G mobile communications require that cell towers and antennas be in much closer proximity; as a result, the location data can reveal more personal and sensitive information about individual citizens. Despite this aspect, service providers are required to disclose the data to the authorities, without the need for a judicial warrant. This book was written from the perspective of big location data software analytics, a capability that makes it possible to combine various location data points to create a profile on a given individual's movements, habits, and political, religious and ideological orientation. In this regard, privacy is poorly protected. The rationale used to justify the powers was enforcing serious crimes - terrorism offences. Location data can now be retained for at least two years and be collected to investigate even minor offences. This can be done without the person being reasonably suspected of a criminal offence - when the individual is simply determined to be a person of interest. This poses legal risks to vulnerable communities. And yet, such investigative techniques are deemed lawful and reasonable. At a time when national security is so broadly defined to include economic issues, which in turn overlap with climate change and environmental protection, these legal powers should be reassessed. The book clarifies the complex rules that every citizen must know in order to have agency. Further, it calls upon authorities to reflect and to self-regulate, by making the conscious decision to surrender some of their powers to review by the independent judiciary. Without the requirement for a judicial warrant or judicial review, the powers are unfairly broad. The book pursues an interdisciplinary approach to assess the functionality of mobile telecommunications in direct relation to law enforcement powers and existing judicial precedents. Further, it offers a unifying techno-legal perspective on a complex issue touching on modern privacy law and communications technologies.

This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques. This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https://dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases. The Book describes how linkage methods work and how to evaluate their performance. It covers all the major concepts and methods and also discusses practical matters such as computational efficiency, which are critical if the methods are to be used in practice - and it does all this in a highly accessible way!David J. Hand, Imperial College, London

The successes and failures of an industry that claims to protect and promote our online identities What does privacy mean in the digital era? As technology increasingly blurs the boundary between public and private, questions about who controls our data become harder and harder to answer. Our every web view, click, and online purchase can be sold to anyone to store and use as they wish. At the same time, our online reputation has become an important part of our identity-a form of cultural currency. The Identity Trade examines the relationship between online visibility and privacy, and the politics of identity and self-presentation in the digital age. In doing so, Nora Draper looks at the revealing two-decade history of efforts by the consumer privacy industry to give individuals control over their digital image through the sale of privacy protection and reputation management as a service. Through in-depth interviews with industry experts, as well as analysis of media coverage, promotional materials, and government policies, Draper examines how companies have turned the protection and promotion of digital information into a business. Along the way, she also provides insight into how these companies have responded to and shaped the ways we think about image and reputation in the digital age. Tracking the successes and failures of companies claiming to control our digital ephemera, Draper takes us inside an industry that has commodified strategies of information control. This book is a discerning overview of the debate around who controls our data, who buys and sells it, and the consequences of treating privacy as a consumer good.

This book discusses the state-of-the-art in privacy-preserving deep learning (PPDL), especially as a tool for machine learning as a service (MLaaS), which serves as an enabling technology by combining classical privacy-preserving and cryptographic protocols with deep learning. Google and Microsoft announced a major investment in PPDL in early 2019. This was followed by Google's infamous announcement of "Private Join and Compute," an open source PPDL tools based on secure multi-party computation (secure MPC) and homomorphic encryption (HE) in June of that year. One of the challenging issues concerning PPDL is selecting its practical applicability despite the gap between the theory and practice. In order to solve this problem, it has recently been proposed that in addition to classical privacy-preserving methods (HE, secure MPC, differential privacy, secure enclaves), new federated or split learning for PPDL should also be applied. This concept involves building a cloud framework that enables collaborative learning while keeping training data on client devices. This successfully preserves privacy and while allowing the framework to be implemented in the real world. This book provides fundamental insights into privacy-preserving and deep learning, offering a comprehensive overview of the state-of-the-art in PPDL methods. It discusses practical issues, and leveraging federated or split-learning-based PPDL. Covering the fundamental theory of PPDL, the pros and cons of current PPDL methods, and addressing the gap between theory and practice in the most recent approaches, it is a valuable reference resource for a general audience, undergraduate and graduate students, as well as practitioners interested learning about PPDL from the scratch, and researchers wanting to explore PPDL for their applications.

This book features selected research papers presented at the Second International Conference on Computing, Communications, and Cyber-Security (IC4S 2020), organized in Krishna Engineering College (KEC), Ghaziabad, India, along with Academic Associates; Southern Federal University, Russia; IAC Educational, India; and ITS Mohan Nagar, Ghaziabad, India during 3-4 October 2020. It includes innovative work from researchers, leading innovators, and professionals in the area of communication and network technologies, advanced computing technologies, data analytics and intelligent learning, the latest electrical and electronics trends, and security and privacy issues.

An increasing number of countries develop capabilities for cyber-espionage and sabotage. The sheer number of reported network compromises suggests that some of these countries view cyber-means as integral and well-established elements of their strategical toolbox. At the same time the relevance of such attacks for society and politics is also increasing. Digital means were used to influence the US presidential election in 2016, repeatedly led to power outages in Ukraine, and caused economic losses of hundreds of millions of dollars with a malfunctioning ransomware. In all these cases the question who was behind the attacks is not only relevant from a legal perspective, but also has a political and social dimension. Attribution is the process of tracking and identifying the actors behind these cyber-attacks. Often it is considered an art, not a science. This book systematically analyses how hackers operate, which mistakes they make, and which traces they leave behind. Using examples from real cases the author explains the analytic methods used to ascertain the origin of Advanced Persistent Threats.

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.

This work aims at understanding behavior around location information, including why users share such information, why they protect the data, and what kind of other factors influence the decision to behave in a certain way. This book explores privacy in the context of location data, and answers questions such as what are the privacy related behaviors in this context, and what are the factors influencing such behaviors. The book gives an overview to what privacy means for users in terms of understandings, attitudes and valuations. This book discusses reasons for why research around this topic is challenging, and presents various methods for diving into the topic through empirical studies. The work is relevant for professionals, researchers, and users of technology.

This handbook provides comprehensive knowledge and includes an overview of the current state-of-the-art of Big Data Privacy, with chapters written by international world leaders from academia and industry working in this field. The first part of this book offers a review of security challenges in critical infrastructure and offers methods that utilize acritical intelligence (AI) techniques to overcome those issues. It then focuses on big data security and privacy issues in relation to developments in the Industry 4.0. Internet of Things (IoT) devices are becoming a major source of security and privacy concern in big data platforms. Multiple solutions that leverage machine learning for addressing security and privacy issues in IoT environments are also discussed this handbook. The second part of this handbook is focused on privacy and security issues in different layers of big data systems. It discusses about methods for evaluating security and privacy of big data systems on network, application and physical layers. This handbook elaborates on existing methods to use data analytic and AI techniques at different layers of big data platforms to identify privacy and security attacks. The final part of this handbook is focused on analyzing cyber threats applicable to the big data environments. It offers an in-depth review of attacks applicable to big data platforms in smart grids, smart farming, FinTech, and health sectors. Multiple solutions are presented to detect, prevent and analyze cyber-attacks and assess the impact of malicious payloads to those environments. This handbook provides information for security and privacy experts in most areas of big data including; FinTech, Industry 4.0, Internet of Things, Smart Grids, Smart Farming and more. Experts working in big data, privacy, security, forensics, malware analysis, machine learning and data analysts will find this handbook useful as a reference. Researchers and advanced-level computer science students focused on computer systems, Internet of Things, Smart Grid, Smart Farming, Industry 4.0 and network analysts will also find this handbook useful as a reference.

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.