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Privacy Preserving Computing
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Book Synopsis Algorithms for Data and Computation Privacy by : Alex X. Liu
Download or read book Algorithms for Data and Computation Privacy written by Alex X. Liu and published by Springer Nature. This book was released on 2020-11-28 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Privacy Technologies and Policy by : Bart Preneel
Download or read book Privacy Technologies and Policy written by Bart Preneel and published by Springer. This book was released on 2014-01-23 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised selected papers from the First Annual Privacy Forum, APF 2012, held in Limassol, Cyprus, in October 2012. The 13 revised papers presented in this volume were carefully reviewed and selected from 26 submissions. They are organized in topical sections named: modelling; privacy by design; identity management and case studies.
Book Synopsis The Ethics of Cybersecurity by : Markus Christen
Download or read book The Ethics of Cybersecurity written by Markus Christen and published by Springer Nature. This book was released on 2020-02-10 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides the first comprehensive collection of papers that provide an integrative view on cybersecurity. It discusses theories, problems and solutions on the relevant ethical issues involved. This work is sorely needed in a world where cybersecurity has become indispensable to protect trust and confidence in the digital infrastructure whilst respecting fundamental values like equality, fairness, freedom, or privacy. The book has a strong practical focus as it includes case studies outlining ethical issues in cybersecurity and presenting guidelines and other measures to tackle those issues. It is thus not only relevant for academics but also for practitioners in cybersecurity such as providers of security software, governmental CERTs or Chief Security Officers in companies.
Book Synopsis Privacy Preserving Data Mining by : Jaideep Vaidya
Download or read book Privacy Preserving Data Mining written by Jaideep Vaidya and published by Springer Science & Business Media. This book was released on 2006-09-28 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Privacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area. Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference.
Book Synopsis Privacy-Preserving Data Mining by : Charu C. Aggarwal
Download or read book Privacy-Preserving Data Mining written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2008-06-10 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in hardware technology have increased the capability to store and record personal data. This has caused concerns that personal data may be abused. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy. The book is designed for researchers, professors, and advanced-level students in computer science, but is also suitable for practitioners in industry.
Book Synopsis Security and Privacy Preserving for IoT and 5G Networks by : Ahmed A. Abd El-Latif
Download or read book Security and Privacy Preserving for IoT and 5G Networks written by Ahmed A. Abd El-Latif and published by Springer Nature. This book was released on 2021-10-09 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art research on security and privacy- preserving for IoT and 5G networks and applications. The accepted book chapters covered many themes, including traceability and tamper detection in IoT enabled waste management networks, secure Healthcare IoT Systems, data transfer accomplished by trustworthy nodes in cognitive radio, DDoS Attack Detection in Vehicular Ad-hoc Network (VANET) for 5G Networks, Mobile Edge-Cloud Computing, biometric authentication systems for IoT applications, and many other applications It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this particular area or those interested in grasping its diverse facets and exploring the latest advances on security and privacy- preserving for IoT and 5G networks.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309465370 Total Pages :195 pages Book Rating :4.3/5 (94 download)
Book Synopsis Federal Statistics, Multiple Data Sources, and Privacy Protection by : National Academies of Sciences, Engineering, and Medicine
Download or read book Federal Statistics, Multiple Data Sources, and Privacy Protection written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-01-27 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.
Book Synopsis Privacy-preserving Computing by : Kai Chen
Download or read book Privacy-preserving Computing written by Kai Chen and published by Cambridge University Press. This book was released on 2023-11-16 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Privacy-preserving computing aims to protect the personal information of users while capitalizing on the possibilities unlocked by big data. This practical introduction for students, researchers, and industry practitioners is the first cohesive and systematic presentation of the field's advances over four decades. The book shows how to use privacy-preserving computing in real-world problems in data analytics and AI, and includes applications in statistics, database queries, and machine learning. The book begins by introducing cryptographic techniques such as secret sharing, homomorphic encryption, and oblivious transfer, and then broadens its focus to more widely applicable techniques such as differential privacy, trusted execution environment, and federated learning. The book ends with privacy-preserving computing in practice in areas like finance, online advertising, and healthcare, and finally offers a vision for the future of the field.
Book Synopsis Introduction to Privacy-Preserving Data Publishing by : Benjamin C.M. Fung
Download or read book Introduction to Privacy-Preserving Data Publishing written by Benjamin C.M. Fung and published by CRC Press. This book was released on 2010-08-02 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gaining access to high-quality data is a vital necessity in knowledge-based decision making. But data in its raw form often contains sensitive information about individuals. Providing solutions to this problem, the methods and tools of privacy-preserving data publishing enable the publication of useful information while protecting data privacy. Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques presents state-of-the-art information sharing and data integration methods that take into account privacy and data mining requirements. The first part of the book discusses the fundamentals of the field. In the second part, the authors present anonymization methods for preserving information utility for specific data mining tasks. The third part examines the privacy issues, privacy models, and anonymization methods for realistic and challenging data publishing scenarios. While the first three parts focus on anonymizing relational data, the last part studies the privacy threats, privacy models, and anonymization methods for complex data, including transaction, trajectory, social network, and textual data. This book not only explores privacy and information utility issues but also efficiency and scalability challenges. In many chapters, the authors highlight efficient and scalable methods and provide an analytical discussion to compare the strengths and weaknesses of different solutions.
Book Synopsis Cryptography for Security and Privacy in Cloud Computing by : Stefan Rass
Download or read book Cryptography for Security and Privacy in Cloud Computing written by Stefan Rass and published by Artech House. This book was released on 2013-11-01 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: As is common practice in research, many new cryptographic techniques have been developed to tackle either a theoretical question or foreseeing a soon to become reality application. Cloud computing is one of these new areas, where cryptography is expected to unveil its power by bringing striking new features to the cloud. Cloud computing is an evolving paradigm, whose basic attempt is to shift computing and storage capabilities to external service providers. This resource offers an overview of the possibilities of cryptography for protecting data and identity information, much beyond well-known cryptographic primitives such as encryption or digital signatures. This book represents a compilation of various recent cryptographic primitives, providing readers with the features and limitations of each.
Book Synopsis Applied Cryptography and Network Security by : Feng Bao
Download or read book Applied Cryptography and Network Security written by Feng Bao and published by Springer. This book was released on 2012-06-14 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Applied Cryptography and Network Security, ACNS 2012, held in Singapore, in June 2012. The 33 revised full papers included in this volume were carefully reviewed and selected from 192 submissions. They are organized in topical sessions on authentication, key management, block ciphers, identity-based cryptography, cryptographic primitives, cryptanalysis, side channel attacks, network security, Web security, security and privacy in social networks, security and privacy in RFID systems, security and privacy in cloud systems, and security and privacy in smart grids.
Book Synopsis Privacy-Preserving Machine Learning by : J. Morris Chang
Download or read book Privacy-Preserving Machine Learning written by J. Morris Chang and published by Simon and Schuster. This book was released on 2023-05-02 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models. In Privacy Preserving Machine Learning, you will learn: Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthetic data generation Privacy-enhancing technologies for data mining and database applications Compressive privacy for machine learning Privacy-Preserving Machine Learning is a comprehensive guide to avoiding data breaches in your machine learning projects. You’ll get to grips with modern privacy-enhancing techniques such as differential privacy, compressive privacy, and synthetic data generation. Based on years of DARPA-funded cybersecurity research, ML engineers of all skill levels will benefit from incorporating these privacy-preserving practices into their model development. By the time you’re done reading, you’ll be able to create machine learning systems that preserve user privacy without sacrificing data quality and model performance. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning applications need massive amounts of data. It’s up to you to keep the sensitive information in those data sets private and secure. Privacy preservation happens at every point in the ML process, from data collection and ingestion to model development and deployment. This practical book teaches you the skills you’ll need to secure your data pipelines end to end. About the Book Privacy-Preserving Machine Learning explores privacy preservation techniques through real-world use cases in facial recognition, cloud data storage, and more. You’ll learn about practical implementations you can deploy now, future privacy challenges, and how to adapt existing technologies to your needs. Your new skills build towards a complete security data platform project you’ll develop in the final chapter. What’s Inside Differential and compressive privacy techniques Privacy for frequency or mean estimation, naive Bayes classifier, and deep learning Privacy-preserving synthetic data generation Enhanced privacy for data mining and database applications About the Reader For machine learning engineers and developers. Examples in Python and Java. About the Author J. Morris Chang is a professor at the University of South Florida. His research projects have been funded by DARPA and the DoD. Di Zhuang is a security engineer at Snap Inc. Dumindu Samaraweera is an assistant research professor at the University of South Florida. The technical editor for this book, Wilko Henecka, is a senior software engineer at Ambiata where he builds privacy-preserving software. Table of Contents PART 1 - BASICS OF PRIVACY-PRESERVING MACHINE LEARNING WITH DIFFERENTIAL PRIVACY 1 Privacy considerations in machine learning 2 Differential privacy for machine learning 3 Advanced concepts of differential privacy for machine learning PART 2 - LOCAL DIFFERENTIAL PRIVACY AND SYNTHETIC DATA GENERATION 4 Local differential privacy for machine learning 5 Advanced LDP mechanisms for machine learning 6 Privacy-preserving synthetic data generation PART 3 - BUILDING PRIVACY-ASSURED MACHINE LEARNING APPLICATIONS 7 Privacy-preserving data mining techniques 8 Privacy-preserving data management and operations 9 Compressive privacy for machine learning 10 Putting it all together: Designing a privacy-enhanced platform (DataHub)
Book Synopsis Mobile Cloud Computing by : Meikang Qiu
Download or read book Mobile Cloud Computing written by Meikang Qiu and published by CRC Press. This book was released on 2017-05-12 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mobile Cloud Computing: Models, Implementation, and Security provides a comprehensive introduction to mobile cloud computing, including key concepts, models, and relevant applications. The book focuses on novel and advanced algorithms, as well as mobile app development. The book begins with an overview of mobile cloud computing concepts, models, and service deployments, as well as specific cloud service models. It continues with the basic mechanisms and principles of mobile computing, as well as virtualization techniques. The book also introduces mobile cloud computing architecture, design, key techniques, and challenges. The second part of the book covers optimizations of data processing and storage in mobile clouds, including performance and green clouds. The crucial optimization algorithm in mobile cloud computing is also explored, along with big data and service computing. Security issues in mobile cloud computing are covered in-depth, including a brief introduction to security and privacy issues and threats, as well as privacy protection techniques in mobile systems. The last part of the book features the integration of service-oriented architecture with mobile cloud computing. It discusses web service specifications related to implementations of mobile cloud computing. The book not only presents critical concepts in mobile cloud systems, but also drives readers to deeper research, through open discussion questions. Practical case studies are also included. Suitable for graduate students and professionals, this book provides a detailed and timely overview of mobile cloud computing for a broad range of readers.
Book Synopsis Privacy-Preserving in Edge Computing by : Longxiang Gao
Download or read book Privacy-Preserving in Edge Computing written by Longxiang Gao and published by Springer Nature. This book was released on 2021-06-01 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Foundations of Secure Computation by : Friedrich L. Bauer
Download or read book Foundations of Secure Computation written by Friedrich L. Bauer and published by IOS Press. This book was released on 2000 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: The final quarter of the 20th century has seen the establishment of a global computational infrastructure. This and the advent of programming languages such as Java, supporting mobile distributed computing, has posed a significant challenge to computer sciences. The infrastructure can support commerce, medicine and government, but only if communications and computing can be secured against catastrophic failure and malicious interference.
Book Synopsis Advances in Cryptology - CRYPTO 2000 by : Mihir Bellare
Download or read book Advances in Cryptology - CRYPTO 2000 written by Mihir Bellare and published by Springer. This book was released on 2003-06-26 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 20th Annual International Cryptology Conference, CRYPTO 2000, held in Santa Barbara, CA, USA in August 2000. The 32 revised full papers presented together with one invited contribution were carefully reviewed and selected from 120 submissions. The papers are organized in topical sections on XTR and NTRU, privacy for databases, secure distributed computation, algebraic cryptosystems, message authentication, digital signatures, cryptanalysis, traitor tracing and broadcast encryption, symmetric encryption, to commit or not to commit, protocols, and stream ciphers and Boolean functions.
Book Synopsis Privacy-Preserving Data Publishing by : Bee-Chung Chen
Download or read book Privacy-Preserving Data Publishing written by Bee-Chung Chen and published by Now Publishers Inc. This book was released on 2009-10-14 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is dedicated to those who have something to hide. It is a book about "privacy preserving data publishing" -- the art of publishing sensitive personal data, collected from a group of individuals, in a form that does not violate their privacy. This problem has numerous and diverse areas of application, including releasing Census data, search logs, medical records, and interactions on a social network. The purpose of this book is to provide a detailed overview of the current state of the art as well as open challenges, focusing particular attention on four key themes: RIGOROUS PRIVACY POLICIES Repeated and highly-publicized attacks on published data have demonstrated that simplistic approaches to data publishing do not work. Significant recent advances have exposed the shortcomings of naive (and not-so-naive) techniques. They have also led to the development of mathematically rigorous definitions of privacy that publishing techniques must satisfy; METRICS FOR DATA UTILITY While it is necessary to enforce stringent privacy policies, it is equally important to ensure that the published version of the data is useful for its intended purpose. The authors provide an overview of diverse approaches to measuring data utility; ENFORCEMENT MECHANISMS This book describes in detail various key data publishing mechanisms that guarantee privacy and utility; EMERGING APPLICATIONS The problem of privacy-preserving data publishing arises in diverse application domains with unique privacy and utility requirements. The authors elaborate on the merits and limitations of existing solutions, based on which we expect to see many advances in years to come.
