Secure Computation of K-anonymous Distributed Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Secure Computation of K-anonymous Distributed Data write by Bradley Malin. This book was released on 2004. Secure Computation of K-anonymous Distributed Data available in PDF, EPUB and Kindle. Abstract: "In a distributed environment, such as the World Wide Web, an individual leaves behind personal data at many different locations. To protect the privacy of an individual's sensitive information, locations make separate releases of identifiable data (e.g. name or social security number), and sensitive data (e.g. visitor's IP address). To the releasing location the data appears unlinkable, however, links can be established when multiple locations' releases are available. This problem, known as trail re-identification, manifests when an individual's location-visit patterns are reconstructed from, and linked between, sensitive and identifiable releases. In this paper, we present a protocol that enables locations to prevent trail re-identification without revealing identified or sensitive data. Instead, locations communicate encrypted versions of their datasets, such that decrypted data is never revealed until completion of the protocol. Via the protocol, every piece of sensitive data, released from any set of locations, is guaranteed to be equally relatable to at least k identities, or is k-anonymous."
Security Infrastructure Technology for Integrated Utilization of Big Data
Security Infrastructure Technology for Integrated Utilization of Big Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Security Infrastructure Technology for Integrated Utilization of Big Data write by Atsuko Miyaji. This book was released on 2020-10-09. Security Infrastructure Technology for Integrated Utilization of Big Data available in PDF, EPUB and Kindle. This open access book describes the technologies needed to construct a secure big data infrastructure that connects data owners, analytical institutions, and user institutions in a circle of trust. It begins by discussing the most relevant technical issues involved in creating safe and privacy-preserving big data distribution platforms, and especially focuses on cryptographic primitives and privacy-preserving techniques, which are essential prerequisites. The book also covers elliptic curve cryptosystems, which offer compact public key cryptosystems; and LWE-based cryptosystems, which are a type of post-quantum cryptosystem. Since big data distribution platforms require appropriate data handling, the book also describes a privacy-preserving data integration protocol and privacy-preserving classification protocol for secure computation. Furthermore, it introduces an anonymization technique and privacy risk evaluation technique. This book also describes the latest related findings in both the living safety and medical fields. In the living safety field, to prevent injuries occurring in everyday life, it is necessary to analyze injury data, find problems, and implement suitable measures. But most cases don't include enough information for injury prevention because the necessary data is spread across multiple organizations, and data integration is difficult from a security standpoint. This book introduces a system for solving this problem by applying a method for integrating distributed data securely and introduces applications concerning childhood injury at home and school injury. In the medical field, privacy protection and patient consent management are crucial for all research. The book describes a medical test bed for the secure collection and analysis of electronic medical records distributed among various medical institutions. The system promotes big-data analysis of medical data with a cloud infrastructure and includes various security measures developed in our project to avoid privacy violations. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Privacy Preserving Data Mining
Privacy Preserving Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Privacy Preserving Data Mining write by Jaideep Vaidya. This book was released on 2005-11-29. Privacy Preserving Data Mining available in PDF, EPUB and Kindle. 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.
Security, Privacy, and Anonymity in Computation, Communication, and Storage
Security, Privacy, and Anonymity in Computation, Communication, and Storage - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Security, Privacy, and Anonymity in Computation, Communication, and Storage write by Guojun Wang. This book was released on 2019-07-10. Security, Privacy, and Anonymity in Computation, Communication, and Storage available in PDF, EPUB and Kindle. This book constitutes the refereed proceedings of the 12th International Conference on Security, Privacy, and Anonymity in Computation, Communication, and Storage, SpaCCS 2019, held in Atlanta, GA, USA in July 2019. The 37 full papers were carefully reviewed and selected from 109 submissions. The papers cover many dimensions including security algorithms and architectures, privacy-aware policies, regulations and techniques, anonymous computation and communication, encompassing fundamental theoretical approaches, practical experimental projects, and commercial application systems for computation, communication and storage.
Security Infrastructure Technology for Integrated Utilization of Big Data
Security Infrastructure Technology for Integrated Utilization of Big Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Security Infrastructure Technology for Integrated Utilization of Big Data write by Atsuko Miyaji. This book was released on 2020-04-23. Security Infrastructure Technology for Integrated Utilization of Big Data available in PDF, EPUB and Kindle. This open access book describes the technologies needed to construct a secure big data infrastructure that connects data owners, analytical institutions, and user institutions in a circle of trust. It begins by discussing the most relevant technical issues involved in creating safe and privacy-preserving big data distribution platforms, and especially focuses on cryptographic primitives and privacy-preserving techniques, which are essential prerequisites. The book also covers elliptic curve cryptosystems, which offer compact public key cryptosystems; and LWE-based cryptosystems, which are a type of post-quantum cryptosystem. Since big data distribution platforms require appropriate data handling, the book also describes a privacy-preserving data integration protocol and privacy-preserving classification protocol for secure computation. Furthermore, it introduces an anonymization technique and privacy risk evaluation technique. This book also describes the latest related findings in both the living safety and medical fields. In the living safety field, to prevent injuries occurring in everyday life, it is necessary to analyze injury data, find problems, and implement suitable measures. But most cases don’t include enough information for injury prevention because the necessary data is spread across multiple organizations, and data integration is difficult from a security standpoint. This book introduces a system for solving this problem by applying a method for integrating distributed data securely and introduces applications concerning childhood injury at home and school injury. In the medical field, privacy protection and patient consent management are crucial for all research. The book describes a medical test bed for the secure collection and analysis of electronic medical records distributed among various medical institutions. The system promotes big-data analysis of medical data with a cloud infrastructure and includes various security measures developed in our project to avoid privacy violations.
