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The Algorithmic Foundations of Differential Privacy
The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the ...
Tutorials on the Foundations of Cryptography
This is a graduate textbook of advanced tutorials on the theory of cryptography and computational complexity. In particular, the chapters explain aspects of garbled circuits, public-key cryptography, pseudorandom functions, one-way functions, homomorphic encryption, the simulation proof technique, and the complexity of differential privacy. Most chapters progress methodically through motivations, foundations, definitions, major results, issues surrounding feasibility, surveys of recent developments, and suggestions for further study. This book honors Professor Oded Goldreich, a pioneering scientist, educator, and mentor. Oded was instrumental in laying down the foundations of cryptography, and he inspired the contributing authors, Benny Applebaum, Boaz Barak, Andrej Bogdanov, Iftach Haitner, Shai Halevi, Yehuda Lindell, Alon Rosen, and Salil Vadhan, themselves leading researchers on the theory of cryptography and computational complexity. The book is appropriate for graduate tutorials and seminars, and for self-study by experienced researchers, assuming prior knowledge of the theory of cryptography.
Differential Privacy
Over the last decade, differential privacy (DP) has emerged as the de facto standard privacy notion for research in privacy-preserving data analysis and publishing. The DP notion offers strong privacy guarantee and has been applied to many data analysis tasks. This Synthesis Lecture is the first of two volumes on differential privacy. This lecture differs from the existing books and surveys on differential privacy in that we take an approach balancing theory and practice. We focus on empirical accuracy performances of algorithms rather than asymptotic accuracy guarantees. At the same time, we try to explain why these algorithms have those empirical accuracy performances. We also take a balan...
Distributed Algorithms
In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers. Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others. The...
Theory of Cryptography
This book constitutes the refereed proceedings of the Third Theory of Cryptography Conference, TCC 2006, held in March 2006. The 31 revised full papers presented were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on zero-knowledge, primitives, assumptions and models, the bounded-retrieval model, privacy, secret sharing and multi-party computation, universally-composible security, one-way functions and friends, and pseudo-random functions and encryption.
Handbook of Sharing Confidential Data
Statistical agencies, research organizations, companies, and other data stewards that seek to share data with the public face a challenging dilemma. They need to protect the privacy and confidentiality of data subjects and their attributes while providing data products that are useful for their intended purposes. In an age when information on data subjects is available from a wide range of data sources, as are the computational resources to obtain that information, this challenge is increasingly difficult. The Handbook of Sharing Confidential Data helps data stewards understand how tools from the data confidentiality literature—specifically, synthetic data, formal privacy, and secure compu...
Distributed Algorithms
Microsystem technology (MST) integrates very small (up to a few nanometers) mechanical, electronic, optical, and other components on a substrate to construct functional devices. These devices are used as intelligent sensors, actuators, and controllers for medical, automotive, household and many other purposes. This book is a basic introduction to MST for students, engineers, and scientists. It is the first of its kind to cover MST in its entirety. It gives a comprehensive treatment of all important parts of MST such as microfabrication technologies, microactuators, microsensors, development and testing of microsystems, and information processing in microsystems. It surveys products built to date and experimental products and gives a comprehensive view of all developments leading to MST devices and robots.
Privacy Enhancing Technologies
This book constitutes the refereed proceedings of the 10th International Symposium, PETS 2010, held in Berlin, Germany in July 2010. The 16 revised full papers were carefully reviewed and selected from 57 submissions for inclusion in the book. The papers handle topics such as access control, privacy of web based search, anonymus webs of trust, security attacks, active timing attacks in lo-latency anonymus communication, network topology and web search with malicious adversaries
