Bøger af Josep Domingo-Ferrer

The current social and economic context increasingly demands open data to improve scientific research and decision making. However, when published data refer to individual respondents, disclosure risk limitation techniques must be implemented to anonymize the data and guarantee by design the fundamental right to privacy of the subjects the data refer to. Disclosure risk limitation has a long record in the statistical and computer science research communities, who have developed a variety of privacy-preserving solutions for data releases. This Synthesis Lecture provides a comprehensive overview of the fundamentals of privacy in data releases focusing on the computer science perspective. Specifically, we detail the privacy models, anonymization methods, and utility and risk metrics that have been proposed so far in the literature. Besides, as a more advanced topic, we identify and discuss in detail connections between several privacy models (i.e., how to accumulate the privacy guarantees they offer to achieve more robust protection and when such guarantees are equivalent or complementary); we also explore the links between anonymization methods and privacy models (how anonymization methods can be used to enforce privacy models and thereby offer ex ante privacy guarantees). These latter topics are relevant to researchers and advanced practitioners, who will gain a deeper understanding on the available data anonymization solutions and the privacy guarantees they can offer.

Inference control in statistical databases, also known as statistical disclosure limitation or statistical confidentiality, is about finding tradeoffs to the tension between the increasing societal need for accurate statistical data and the legal and ethical obligation to protect privacy of individuals and enterprises which are the source of data for producing statistics. Techniques used by intruders to make inferences compromising privacy increasingly draw on data mining, record linkage, knowledge discovery, and data analysis and thus statistical inference control becomes an integral part of computer science.This coherent state-of-the-art survey presents some of the most recent work in the field. The papers presented together with an introduction are organized in topical sections on tabular data protection, microdata protection, and software and user case studies.

Smart cards or IC cards offer a huge potential for information processing purposes. The portability and processing power of IC cards allow for highly secure conditional access and reliable distributed information processing. IC cards that can perform highly sophisticated cryptographic computations are already available. Their application in the financial services and telecom industries are well known. But the potential of IC cards go well beyond that. Their applicability in mainstream Information Technology and the Networked Economy is limited mainly by our imagination; the information processing power that can be gained by using IC cards remains as yet mostly untapped and is not well understood. Here lies a vast uncovered research area which we are only beginning to assess, and which will have a great impact on the eventual success of the technology. The research challenges range from electrical engineering on the hardware side to tailor-made cryptographic applications on the software side, and their synergies. This volume comprises the proceedings of the Fourth Working Conference on Smart Card Research and Advanced Applications (CARDIS 2000), which was sponsored by the International Federation for Information Processing (IFIP) and held at the Hewlett-Packard Labs in the United Kingdom in September 2000. CARDIS conferences are unique in that they bring together researchers who are active in all aspects of design of IC cards and related devices and environments, thus stimulating synergy between different research communities from both academia and industry. This volume presents the latest advances in smart card research and applications, and will be essential reading for smart card developers, smart card application developers, and computer science researchers involved in computer architecture, computer security, and cryptography.