Data And Applications Security And Privacy Xxvii

This book constitutes the refereed proceedings of the 27th IFIP WG 11.3 International Conference on Data and Applications Security and Privacy, DBSec 2013, held in Newark, NJ, USA in July 2013. The 16 revised full and 6 short papers presented were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on privacy, access control, cloud computing, data outsourcing, and mobile computing.

This book constitutes the refereed proceedings of the 26th IFIP WG 11.3 International Conference on Data and Applications Security and Privacy, DBSec 2012, held in Paris, France in July 2012. The 17 revised full and 15 short papers presented together with 1 invited paper were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on access control, confidentiality and privacy, smart cards security, privacy-preserving technologies, data management, intrusion and malware, probabilistic attacks and protection, and cloud computing.

With the growing popularity of “big data”, the potential value of personal data has attracted more and more attention. Applications built on personal data can create tremendous social and economic benefits. Meanwhile, they bring serious threats to individual privacy. The extensive collection, analysis and transaction of personal data make it difficult for an individual to keep the privacy safe. People now show more concerns about privacy than ever before. How to make a balance between the exploitation of personal information and the protection of individual privacy has become an urgent issue. In this book, the authors use methodologies from economics, especially game theory, to investigate solutions to the balance issue. They investigate the strategies of stakeholders involved in the use of personal data, and try to find the equilibrium. The book proposes a user-role based methodology to investigate the privacy issues in data mining, identifying four different types of users, i.e. four user roles, involved in data mining applications. For each user role, the authors discuss its privacy concerns and the strategies that it can adopt to solve the privacy problems. The book also proposes a simple game model to analyze the interactions among data provider, data collector and data miner. By solving the equilibria of the proposed game, readers can get useful guidance on how to deal with the trade-off between privacy and data utility. Moreover, to elaborate the analysis on data collector’s strategies, the authors propose a contract model and a multi-armed bandit model respectively. The authors discuss how the owners of data (e.g. an individual or a data miner) deal with the trade-off between privacy and utility in data mining. Specifically, they study users’ strategies in collaborative filtering based recommendation system and distributed classification system. They built game models to formulate the interactions among data owners, and propose learning algorithms to find the equilibria.

This book constitutes the proceedings of the 24th Annual IFIP WG 11.3 Working Conference on Data and Applications Security, held in Rome Italy in June 2010. The 18 full and 11 short papers presented in this volume were carefully reviewed and selected from 61 submissions. The topics covered are query and data privacy; data protection; access control; data confidentiality and query verification; policy definition and enforcement; and trust and identity management.

The book covers different aspects of real-world applications of optimization algorithms. It provides insights from the Fourth International Conference on Harmony Search, Soft Computing and Applications held at BML Munjal University, Gurgaon, India on February 7–9, 2018. It consists of research articles on novel and newly proposed optimization algorithms; the theoretical study of nature-inspired optimization algorithms; numerically established results of nature-inspired optimization algorithms; and real-world applications of optimization algorithms and synthetic benchmarking of optimization algorithms.

This book constitutes the thoroughly refereed post-conference proceedings of the 20th International Conference on Financial Cryptography and Data Security, FC 2016, held in Christ church, Barbados, in February 2016. The 27 revised full papers and 9 short papers were carefully selected and reviewed from 137 full papers submissions. The papers are grouped in the following topical sections: fraud and deception; payments, auctions, and e-voting; multiparty computation; mobile malware; social interaction and policy; cryptanalysis; surveillance and anonymity; Web security and data privacy; Bitcoin mining; cryptographic protocols; payment use and abuse.

This book presents a comprehensive approach to protecting sensitive information when large data collections are released by their owners. It addresses three key requirements of data privacy: the protection of data explicitly released, the protection of information not explicitly released but potentially vulnerable due to a release of other data, and the enforcement of owner-defined access restrictions to the released data. It is also the first book with a complete examination of how to enforce dynamic read and write access authorizations on released data, applicable to the emerging data outsourcing and cloud computing situations. Private companies, public organizations and final users are releasing, sharing, and disseminating their data to take reciprocal advantage of the great benefits of making their data available to others. This book weighs these benefits against the potential privacy risks. A detailed analysis of recent techniques for privacy protection in data release and case studies illustrate crucial scenarios. Protecting Privacy in Data Release targets researchers, professionals and government employees working in security and privacy. Advanced-level students in computer science and electrical engineering will also find this book useful as a secondary text or reference.