. The approach is based on the definition of k-anonymity. A table provides k-anonymity if attempts to link explicitly identifying information to its content map the information to at least k entities. We illustrate how k-anonymity can be provided without compromising the integrity (or truthfulness

This document is a revision of the public working draft dated 1998-08-19 incorporating suggestions received in review comments and further deliberations of the W3C RDF Model and Syntax Working Group. With the publication of this draft, the RDF Model and Syntax Specification enters "last call." The last call period will end on October 23, 1998. Comments on this specification may be sent to www-rdf-comments@w3.org. The archive of public comments is available at http://www.w3.org/Archives/Public/www-rdf-comments. Significant changes from the previous draft are highlighted in Appendix E. While we do not anticipate substantial changes, we still caution that further changes are possible. Therefore while we encourage active implementation to test this specification we also recommend that only software that can be easily field-upgraded be implemented to this specification at this time. This is a W3C Working Draft for review by W3C members and other interested parties. Publication as a working draft does not imply endorsement by the W3C membership. The RDF Model and Syntax Working Group will not allow early implementation to constrain their ability to make changes to this specification prior to final release. This is a draft document and may be updated, replaced or obsoleted by other documents at any time. It is inappropriate to cite W3C Working Drafts as other than "work in progress". This work is part of the W3C Metadata Activity.

Copyright c ○ 2005 by Cambridge University Press. This material is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University

be stolen and used to impersonate the users elsewhere. It is therefore important to develop privacy preserving voice authentication techniques that enable a system to authenticate users by their voice, while simulta-neously obscuring the user’s voice and voice patterns from the system. Prior work

Constraint Handling Rules (CHR) are our proposal to allow more flexibility and application-oriented customization of constraint systems. CHR are a declarative language extension especially designed for writing user-defined constraints. CHR are essentially a committed-choice language consisting of multi-headed guarded rules that rewrite constraints into simpler ones until they are solved. In this broad survey we aim at covering all aspects of CHR as they currently present themselves. Going from theory to practice, we will define syntax and semantics for CHR, introduce an important decidable property, confluence, of CHR programs and define a tight integration of CHR with constraint logic programming languages. This survey then describes implementations of the language before we review several constraint solvers - both traditional and non- standard ones - written in the CHR language. Finally we introduce two innovative applications that benefited from using CHR.

Unwanted traffic is a major concern in the Internet today. Unwanted traffic includes Denial of Service attacks, worms, and spam. Identifying and mitigating unwanted traffic costs businesses many billions of USD every year. The process of identifying this traffic is called anomaly detection, and Intrusion Detection Systems (IDS’es) are among the most prevalent techniques. IDS’es, such as Snort, allow users to write “rules ” that specify the properties of traffic that should be detected and the corrective action to be taken in response. Unfortunately, applying these rules in an online setting can be prohibitively expensive for large networks, such as Tier-1 ISPs, which may have tens of thousands of links and many Gbps of traffic. In the first chapter of this thesis we present a system that leverages machine learning algorithms to detect the same type of unwanted traffic as Snort, but on summarized data for faster processing. Our results demonstrate that this system can effectively learn to classify many Snort rules with a high degree of accuracy. Unfortunately, distinguishing good traffic from unwanted traffic is challenging even in an offline setting because many types of unwanted traffic traffic, such as

We study the dynamics of information propagation in environments of low-overhead personal publishing, using a large collection of weblogs over time as our example domain. We characterize and model this collection at two levels. First, we present a macroscopic characterization of topic propagation through our corpus, formalizing the notion of long-running "chatter" topics consisting recursively of "spike" topics generated by outside world events, or more rarely, by resonances within the community. Second, we present a microscopic characterization of propagation from individual to individual, drawing on the theory of infectious diseases to model the flow. We propose, validate, and employ an algorithm to induce the underlying propagation network from a sequence of posts, and report on the results.

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Distributed computer architectures labeled “peer-to-peer ” are designed for the sharing of computer resources (content, storage, CPU cycles) by direct exchange, rather than requiring the intermediation or support of a centralized server or authority. Peer-to-peer architectures are characterized by their ability to adapt to failures and accommodate transient populations of nodes while maintaining acceptable connectivity and performance. Content distribution is an important peer-to-peer application on the Internet that has received considerable research attention. Content distribution applications typically allow personal computers to function in a coordinated manner as a distributed storage medium by contributing, searching, and obtaining digital content. In this survey, we propose a framework for analyzing peer-to-peer content distribution technologies. Our approach focuses on nonfunctional characteristics such as security, scalability, performance, fairness, and resource management potential, and examines the way in which these characteristics are reflected in—and affected by—the architectural design decisions adopted by current peer-to-peer systems. We study current peer-to-peer systems and infrastructure technologies in terms of their distributed object location and routing mechanisms, their approach to content replication, caching and migration, their support for encryption, access control, authentication and identity, anonymity, deniability, accountability and reputation, and their use of resource trading and management schemes.