This book constitutes the refereed proceedings of the 25th IFIP WG 11.3 International Conference on Data and Applications Security and Privacy, DBSec 2011, held in Richmond, VA, USA, in July 2011. The 14 revised full papers and 9 short papers presented together with 3 invited lectures were carefully reviewed and selected from 37 submissions. The topics of these papers include access control, privacy-preserving data applications, data confidentiality and query verification, query and data privacy, authentication and secret sharing.

This book constitutes the refereed proceedings of the 34th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2020, held in Regensburg, Germany, in June 2020.* The 14 full papers and 8 short papers presented were carefully reviewed and selected from 39 submissions. The papers present high-quality original research from academia, industry, and government on theoretical and practical aspects of information security. They are organized in topical sections named network and cyber-physical systems security; information flow and access control; privacy-preserving computation; visualization and analytics for security; spatial systems and crowdsourcing security; and secure outsourcing and privacy. *The conference was held virtually due to the COVID-19 pandemic.

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 refereed proceedings of the 9th International Workshop on Security and Trust Management, STM 2013, held in Egham, UK, in September 2013 - in conjunction with the 18th European Symposium Research in Computer Security (ESORICS 2013). The 15 revised full papers including two invited talks were carefully reviewed and selected from 47 submissions. The papers are organized into topical sections on policy enforcement and monitoring; access control; trust, reputation, and privacy; distributed systems and physical security; authentication and security policies.

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 36th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2022, held in Newark, NJ, USA, in July 2022. The 12 full papers and 6 short papers presented were carefully reviewed and selected from 33 submissions. The conference covers research in data and applications security and privacy.

This book constitutes the refereed proceedings of the 22nd Annual IFIP WG 11.3 Working Conference on Data and Applications Security held in London, UK, in July 2008. The 22 revised full papers presented together with 1 keynote lecture and 1 invited talk were carefully reviewed and selected from 56 submissions. The papers are organized in topical sections on access control, audit and logging, privacy, systems security, certificate management, trusted computing platforms, security policies and metrics, as well as Web and pervasive systems.

As Information Technology becomes a vital part of our everyday activities, ranging from personal use to government and defense applications, the need to develop high-assurance systems increases. Data and applications security and privacy are crucial elements in developing such systems. Research Directions in Data and Applications Security XVIII presents original unpublished research results, practical experiences, and innovative ideas in the field of data and applications security and privacy. Topics presented in this volume include: -Database theory; -Inference control; -Data protection techniques; -Distributed systems; -Access control models; -Security policy; -Design and management; -Privacy; -Network security. This book is the eighteenth volume in the series produced by the International Federation for Information Processing (IFIP) Working Group 11.3 on Data and Applications Security. It contains twenty-three papers and two invited talks that were presented at the Eighteenth Annual IFIP WG 11.3 Conference on Data and Applications Security, which was sponsored by IFIP and held in Sitges, Catalonia, Spain in July 2004. Research Directions in Data and Applications Security XVIII is a high-quality reference volume that addresses several aspects of information protection, and is aimed at researchers, educators, students, and developers.

New technology is always evolving and companies must have appropriate security for their businesses to be able to keep up to date with the changes. With the rapid growth of the internet and the world wide web, data and applications security will always be a key topic in industry as well as in the public sector, and has implications for the whole of society. Data and Applications Security covers issues related to security and privacy of information in a wide range of applications, including: Electronic Commerce, XML and Web Security; Workflow Security and Role-based Access Control; Distributed Objects and Component Security; Inference Problem, Data Mining and Intrusion Detection; Language and SQL Security; Security Architectures and Frameworks; Federated and Distributed Systems Security; Encryption, Authentication and Security Policies. This book contains papers and panel discussions from the Fourteenth Annual Working Conference on Database Security, which is part of the Database Security: Status and Prospects conference series sponsored by the International Federation for Information Processing (IFIP). The conference was held in Schoorl, The Netherlands in August 2000.

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.