Anonymity - Explore the Science & Experts | ideXlab

Scan Science and Technology

Contact Leading Edge Experts & Companies

Anonymity

The Experts below are selected from a list of 82134 Experts worldwide ranked by ideXlab platform

Anonymity – Free Register to Access Experts & Abstracts

Riccardo Bettati – One of the best experts on this subject based on the ideXlab platform.

  • Information Leakage as a Model for Quality of Anonymity Networks
    IEEE Transactions on Parallel and Distributed Systems, 2009
    Co-Authors: Ye Zhu, Riccardo Bettati

    Abstract:

    Measures for Anonymity in systems must be on one hand simple and concise, and on the other hand reflect the realities of real systems. Such systems are heterogeneous, as are the ways they are used, the deployed Anonymity measures, and finally the possible attack methods. Implementation quality and topologies of the Anonymity measures must be considered as well. We therefore propose a new measure for the Anonymity degree, that takes into account these various. We model the effectiveness of single mixes or of mix networks in terms of information leakage, and we measure it in terms of covert channel capacity. The relationship between the Anonymity degree and information leakage is described, and an example is shown.

  • ICDCS – Anonymity vs. Information Leakage in Anonymity Systems
    25th IEEE International Conference on Distributed Computing Systems (ICDCS'05), 2005
    Co-Authors: Ye Zhu, Riccardo Bettati

    Abstract:

    Measures for Anonymity in systems must be on one hand simple and concise, and on the other hand reflect the realities of real systems. Such systems are heterogeneous, as are the ways they are used, the deployed Anonymity measures, and finally the possible attack methods. Implementation quality and topologies of the Anonymity measures must be considered as well. We therefore propose a new measure for the Anonymity degree, which takes into account possible heterogeneity. We model the effectiveness of single mixes or of mix networks in terms of information leakage and measure it in terms of covert channel capacity. The relationship between the Anonymity degree and information leakage is described, and an example is shown

  • Anonymity v.s. Information Leakage in a Anonymity Systems
    , 2004
    Co-Authors: Ye Zhu, Riccardo Bettati

    Abstract:

    Measures for Anonymity in systems must be on one hand simple and concise, and on the other hand reflect the realities of real systems. Such systems are heterogeneous, as are the ways they are used, the deployed Anonymity measures, and finally the possible attack methods. Implementation quality and topologies of the Anonymity measures must be considered as well. We therefore propose a new measure for the Anonymity degree, which takes into account possible heterogeneity. We model the effectiveness of single mixes or of mix networks in terms of information leakage and measure it in terms of covert channel capacity. The relationship between the Anonymity degree and information leakage is described, and an example is shown.

Ye Zhu – One of the best experts on this subject based on the ideXlab platform.

  • Information Leakage as a Model for Quality of Anonymity Networks
    IEEE Transactions on Parallel and Distributed Systems, 2009
    Co-Authors: Ye Zhu, Riccardo Bettati

    Abstract:

    Measures for Anonymity in systems must be on one hand simple and concise, and on the other hand reflect the realities of real systems. Such systems are heterogeneous, as are the ways they are used, the deployed Anonymity measures, and finally the possible attack methods. Implementation quality and topologies of the Anonymity measures must be considered as well. We therefore propose a new measure for the Anonymity degree, that takes into account these various. We model the effectiveness of single mixes or of mix networks in terms of information leakage, and we measure it in terms of covert channel capacity. The relationship between the Anonymity degree and information leakage is described, and an example is shown.

  • ICDCS – Anonymity vs. Information Leakage in Anonymity Systems
    25th IEEE International Conference on Distributed Computing Systems (ICDCS'05), 2005
    Co-Authors: Ye Zhu, Riccardo Bettati

    Abstract:

    Measures for Anonymity in systems must be on one hand simple and concise, and on the other hand reflect the realities of real systems. Such systems are heterogeneous, as are the ways they are used, the deployed Anonymity measures, and finally the possible attack methods. Implementation quality and topologies of the Anonymity measures must be considered as well. We therefore propose a new measure for the Anonymity degree, which takes into account possible heterogeneity. We model the effectiveness of single mixes or of mix networks in terms of information leakage and measure it in terms of covert channel capacity. The relationship between the Anonymity degree and information leakage is described, and an example is shown

  • Anonymity v.s. Information Leakage in a Anonymity Systems
    , 2004
    Co-Authors: Ye Zhu, Riccardo Bettati

    Abstract:

    Measures for Anonymity in systems must be on one hand simple and concise, and on the other hand reflect the realities of real systems. Such systems are heterogeneous, as are the ways they are used, the deployed Anonymity measures, and finally the possible attack methods. Implementation quality and topologies of the Anonymity measures must be considered as well. We therefore propose a new measure for the Anonymity degree, which takes into account possible heterogeneity. We model the effectiveness of single mixes or of mix networks in terms of information leakage and measure it in terms of covert channel capacity. The relationship between the Anonymity degree and information leakage is described, and an example is shown.

Traian Marius Truta – One of the best experts on this subject based on the ideXlab platform.

  • avoiding attribute disclosure with the extended p sensitive k Anonymity model
    Data Mining, 2010
    Co-Authors: Traian Marius Truta, Alina Campan

    Abstract:

    Existing privacy regulations together with large amounts of available data created a huge interest in data privacy research. A main research direction is built around the k-Anonymity property. Several shortcomings of the k-Anonymity model were addressed by new privacy models such as p-sensitive k-Anonymity, l-diversity, (α,k)-Anonymity, t-closeness. In this chapter we describe two algorithms (GreedyPKClustering and EnhancedPKClustering) for generating (extended) p-sensitive k-anonymous microdata. In our experiments, we compare the quality of generated microdata obtained with the mentioned algorithms and with another existing anonymization algorithm (Incognito). Also, we present two new branches of p-sensitive k-Anonymity, the constrained p-sensitive k-Anonymity model and the p-sensitive k-Anonymity model for social networks.

  • Secure Data Management – Generating microdata with p-sensitive k-Anonymity property
    Lecture Notes in Computer Science, 2007
    Co-Authors: Traian Marius Truta, Alina Campan, Paul Meyer

    Abstract:

    Existing privacy regulations together with large amounts of available data have created a huge interest in data privacy research. A main research direction is built around the k-Anonymity property. Several shortcomings of the k-Anonymity model have been fixed by new privacy models such as p-sensitive k-Anonymity, l-diversity, (α, k)-Anonymity, and t-closeness. In this paper we introduce the Enhanced PK Clustering algorithm for generating p-sensitive k- anonymous microdata based on frequency distribution of sensitive attribute values. The p-sensitive k-Anonymity model and its enhancement, extended p- sensitive k-Anonymity, are described, their properties are presented, and two diversity measures are introduced. Our experiments have shown that the proposed algorithm improves several cost measures over existing algorithms.

  • privacy protection p sensitive k Anonymity property
    International Conference on Data Engineering, 2006
    Co-Authors: Traian Marius Truta, B Vinay

    Abstract:

    In this paper, we introduce a new privacy protection property called p-sensitive k-Anonymity. The existing kAnonymity property protects against identity disclosure, but it fails to protect against attribute disclosure. The new introduced privacy model avoids this shortcoming. Two necessary conditions to achieve p-sensitive kAnonymity property are presented, and used in developing algorithms to create masked microdata with p-sensitive k-Anonymity property using generalization and suppression.