The Experts below are selected from a list of 66 Experts worldwide ranked by ideXlab platform
Chungen Xu - One of the best experts on this subject based on the ideXlab platform.
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INFOCOM - Hardening Database Padding for Searchable Encryption
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Lei Xu, Xingliang Yuan, Cong Wang, Qian Wang, Chungen XuAbstract:Searchable encryption (SE) is a practical crypto-Graphic Primitive to build encrypted databases. Recently there has been much attention in leakage-abuse attacks against SE. Among others, attacks based on inference of keyword frequency can easily identify query keywords from the access pattern, i.e., query results. To mitigate these attacks, database padding is considered as a conceptually simple yet effective counter-measure. Unfortunately, none of the existing studies formally understand the relationship between padding security strength and its overhead. Also, how to craft padding is not restricted in current countermeasures, where bogus files are likely to be distinguishable from real ones. In this paper, we propose an information theory based framework to analyse the security strength under certain padding overhead. First, we leverage relative entropy to measure the “closeness” between the distributions of the original dataset and padded dataset. Second, we quantity the attack efforts against padding countermeasures by entropy analysis. Apart from theoretical findings, we further devise an algorithm via outlier detection for padding generation, which considers both the padded dataset distribution and the similarity between real and bogus files. Evaluations on a real-world dataset confirm our theoretical results and demonstrate the efficiency and effectiveness of our proposed padding generation algorithm.
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Hardening Database Padding for Searchable Encryption
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Lei Xu, Xingliang Yuan, Cong Wang, Qian Wang, Chungen XuAbstract:Searchable encryption (SE) is a practical crypto-Graphic Primitive to build encrypted databases. Recently there has been much attention in leakage-abuse attacks against SE. Among others, attacks based on inference of keyword frequency can easily identify query keywords from the access pattern, i.e., query results. To mitigate these attacks, database padding is considered as a conceptually simple yet effective counter-measure. Unfortunately, none of the existing studies formally understand the relationship between padding security strength and its overhead. Also, how to craft padding is not restricted in current countermeasures, where bogus files are likely to be distinguishable from real ones. In this paper, we propose an information theory based framework to analyse the security strength under certain padding overhead. First, we leverage relative entropy to measure the “closeness” between the distributions of the original dataset and padded dataset. Second, we quantity the attack efforts against padding countermeasures by entropy analysis. Apart from theoretical findings, we further devise an algorithm via outlier detection for padding generation, which considers both the padded dataset distribution and the similarity between real and bogus files. Evaluations on a real-world dataset confirm our theoretical results and demonstrate the efficiency and effectiveness of our proposed padding generation algorithm.
Lei Xu - One of the best experts on this subject based on the ideXlab platform.
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INFOCOM - Hardening Database Padding for Searchable Encryption
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Lei Xu, Xingliang Yuan, Cong Wang, Qian Wang, Chungen XuAbstract:Searchable encryption (SE) is a practical crypto-Graphic Primitive to build encrypted databases. Recently there has been much attention in leakage-abuse attacks against SE. Among others, attacks based on inference of keyword frequency can easily identify query keywords from the access pattern, i.e., query results. To mitigate these attacks, database padding is considered as a conceptually simple yet effective counter-measure. Unfortunately, none of the existing studies formally understand the relationship between padding security strength and its overhead. Also, how to craft padding is not restricted in current countermeasures, where bogus files are likely to be distinguishable from real ones. In this paper, we propose an information theory based framework to analyse the security strength under certain padding overhead. First, we leverage relative entropy to measure the “closeness” between the distributions of the original dataset and padded dataset. Second, we quantity the attack efforts against padding countermeasures by entropy analysis. Apart from theoretical findings, we further devise an algorithm via outlier detection for padding generation, which considers both the padded dataset distribution and the similarity between real and bogus files. Evaluations on a real-world dataset confirm our theoretical results and demonstrate the efficiency and effectiveness of our proposed padding generation algorithm.
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Hardening Database Padding for Searchable Encryption
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Lei Xu, Xingliang Yuan, Cong Wang, Qian Wang, Chungen XuAbstract:Searchable encryption (SE) is a practical crypto-Graphic Primitive to build encrypted databases. Recently there has been much attention in leakage-abuse attacks against SE. Among others, attacks based on inference of keyword frequency can easily identify query keywords from the access pattern, i.e., query results. To mitigate these attacks, database padding is considered as a conceptually simple yet effective counter-measure. Unfortunately, none of the existing studies formally understand the relationship between padding security strength and its overhead. Also, how to craft padding is not restricted in current countermeasures, where bogus files are likely to be distinguishable from real ones. In this paper, we propose an information theory based framework to analyse the security strength under certain padding overhead. First, we leverage relative entropy to measure the “closeness” between the distributions of the original dataset and padded dataset. Second, we quantity the attack efforts against padding countermeasures by entropy analysis. Apart from theoretical findings, we further devise an algorithm via outlier detection for padding generation, which considers both the padded dataset distribution and the similarity between real and bogus files. Evaluations on a real-world dataset confirm our theoretical results and demonstrate the efficiency and effectiveness of our proposed padding generation algorithm.
David Pinkney - One of the best experts on this subject based on the ideXlab platform.
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dimensional anchors a Graphic Primitive for multidimensional multivariate information visualizations
Conference on Information and Knowledge Management, 1999Co-Authors: Patrick Hoffman, Georges Grinstein, David PinkneyAbstract:We introduce a Graphic Primitive, called a dimensional anchor (DA), which facilitates the creation of new visualizations and provides insight into the analysis of information visualizations. The DA represents an attempt to provide a unified framework or model for a variety of visualizations, including Parallel Coordinates, scatter plot matrices, Radviz, Survey Plots and Circle Segments A dimensional anchor is constructed by assigning values to parameters associated with various geometric Graphic elements that encode the basics of the above visualizations. We define a visualization vector space in which all of the above visualizations and many new ones are represented by vectors. These encodings make it possible to perform a Grand Tour traveling from Parallel Coordinates to Survey Plot, and visiting many other visualizations in between
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Workshop on New Paradigms in Information Visualization and Manipulation - Dimensional anchors: a Graphic Primitive for multidimensional multivariate information visualizations
Proceedings of the 1999 workshop on new paradigms in information visualization and manipulation in conjunction with the eighth ACM internation confere, 1999Co-Authors: Patrick Hoffman, Georges Grinstein, David PinkneyAbstract:We introduce a Graphic Primitive, called a dimensional anchor (DA), which facilitates the creation of new visualizations and provides insight into the analysis of information visualizations. The DA represents an attempt to provide a unified framework or model for a variety of visualizations, including Parallel Coordinates, scatter plot matrices, Radviz, Survey Plots and Circle Segments A dimensional anchor is constructed by assigning values to parameters associated with various geometric Graphic elements that encode the basics of the above visualizations. We define a visualization vector space in which all of the above visualizations and many new ones are represented by vectors. These encodings make it possible to perform a Grand Tour traveling from Parallel Coordinates to Survey Plot, and visiting many other visualizations in between
Cong Wang - One of the best experts on this subject based on the ideXlab platform.
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INFOCOM - Hardening Database Padding for Searchable Encryption
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Lei Xu, Xingliang Yuan, Cong Wang, Qian Wang, Chungen XuAbstract:Searchable encryption (SE) is a practical crypto-Graphic Primitive to build encrypted databases. Recently there has been much attention in leakage-abuse attacks against SE. Among others, attacks based on inference of keyword frequency can easily identify query keywords from the access pattern, i.e., query results. To mitigate these attacks, database padding is considered as a conceptually simple yet effective counter-measure. Unfortunately, none of the existing studies formally understand the relationship between padding security strength and its overhead. Also, how to craft padding is not restricted in current countermeasures, where bogus files are likely to be distinguishable from real ones. In this paper, we propose an information theory based framework to analyse the security strength under certain padding overhead. First, we leverage relative entropy to measure the “closeness” between the distributions of the original dataset and padded dataset. Second, we quantity the attack efforts against padding countermeasures by entropy analysis. Apart from theoretical findings, we further devise an algorithm via outlier detection for padding generation, which considers both the padded dataset distribution and the similarity between real and bogus files. Evaluations on a real-world dataset confirm our theoretical results and demonstrate the efficiency and effectiveness of our proposed padding generation algorithm.
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Hardening Database Padding for Searchable Encryption
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Lei Xu, Xingliang Yuan, Cong Wang, Qian Wang, Chungen XuAbstract:Searchable encryption (SE) is a practical crypto-Graphic Primitive to build encrypted databases. Recently there has been much attention in leakage-abuse attacks against SE. Among others, attacks based on inference of keyword frequency can easily identify query keywords from the access pattern, i.e., query results. To mitigate these attacks, database padding is considered as a conceptually simple yet effective counter-measure. Unfortunately, none of the existing studies formally understand the relationship between padding security strength and its overhead. Also, how to craft padding is not restricted in current countermeasures, where bogus files are likely to be distinguishable from real ones. In this paper, we propose an information theory based framework to analyse the security strength under certain padding overhead. First, we leverage relative entropy to measure the “closeness” between the distributions of the original dataset and padded dataset. Second, we quantity the attack efforts against padding countermeasures by entropy analysis. Apart from theoretical findings, we further devise an algorithm via outlier detection for padding generation, which considers both the padded dataset distribution and the similarity between real and bogus files. Evaluations on a real-world dataset confirm our theoretical results and demonstrate the efficiency and effectiveness of our proposed padding generation algorithm.
Xingliang Yuan - One of the best experts on this subject based on the ideXlab platform.
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INFOCOM - Hardening Database Padding for Searchable Encryption
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Lei Xu, Xingliang Yuan, Cong Wang, Qian Wang, Chungen XuAbstract:Searchable encryption (SE) is a practical crypto-Graphic Primitive to build encrypted databases. Recently there has been much attention in leakage-abuse attacks against SE. Among others, attacks based on inference of keyword frequency can easily identify query keywords from the access pattern, i.e., query results. To mitigate these attacks, database padding is considered as a conceptually simple yet effective counter-measure. Unfortunately, none of the existing studies formally understand the relationship between padding security strength and its overhead. Also, how to craft padding is not restricted in current countermeasures, where bogus files are likely to be distinguishable from real ones. In this paper, we propose an information theory based framework to analyse the security strength under certain padding overhead. First, we leverage relative entropy to measure the “closeness” between the distributions of the original dataset and padded dataset. Second, we quantity the attack efforts against padding countermeasures by entropy analysis. Apart from theoretical findings, we further devise an algorithm via outlier detection for padding generation, which considers both the padded dataset distribution and the similarity between real and bogus files. Evaluations on a real-world dataset confirm our theoretical results and demonstrate the efficiency and effectiveness of our proposed padding generation algorithm.
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Hardening Database Padding for Searchable Encryption
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Lei Xu, Xingliang Yuan, Cong Wang, Qian Wang, Chungen XuAbstract:Searchable encryption (SE) is a practical crypto-Graphic Primitive to build encrypted databases. Recently there has been much attention in leakage-abuse attacks against SE. Among others, attacks based on inference of keyword frequency can easily identify query keywords from the access pattern, i.e., query results. To mitigate these attacks, database padding is considered as a conceptually simple yet effective counter-measure. Unfortunately, none of the existing studies formally understand the relationship between padding security strength and its overhead. Also, how to craft padding is not restricted in current countermeasures, where bogus files are likely to be distinguishable from real ones. In this paper, we propose an information theory based framework to analyse the security strength under certain padding overhead. First, we leverage relative entropy to measure the “closeness” between the distributions of the original dataset and padded dataset. Second, we quantity the attack efforts against padding countermeasures by entropy analysis. Apart from theoretical findings, we further devise an algorithm via outlier detection for padding generation, which considers both the padded dataset distribution and the similarity between real and bogus files. Evaluations on a real-world dataset confirm our theoretical results and demonstrate the efficiency and effectiveness of our proposed padding generation algorithm.
