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Comprehensive Quantitative Analysis on Privacy Leak Behavior
Privacy information is prone to be leaked by illegal software providers with various motivations. Privacy leak behavior has thus become an important research issue of cyber security. However, existing approaches can only qualitatively analyze privacy leak behavior of software applications. No quanti...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3774722/ https://www.ncbi.nlm.nih.gov/pubmed/24066046 http://dx.doi.org/10.1371/journal.pone.0073410 |
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author | Fan, Lejun Wang, Yuanzhuo Jin, Xiaolong Li, Jingyuan Cheng, Xueqi Jin, Shuyuan |
author_facet | Fan, Lejun Wang, Yuanzhuo Jin, Xiaolong Li, Jingyuan Cheng, Xueqi Jin, Shuyuan |
author_sort | Fan, Lejun |
collection | PubMed |
description | Privacy information is prone to be leaked by illegal software providers with various motivations. Privacy leak behavior has thus become an important research issue of cyber security. However, existing approaches can only qualitatively analyze privacy leak behavior of software applications. No quantitative approach, to the best of our knowledge, has been developed in the open literature. To fill this gap, in this paper we propose for the first time four quantitative metrics, namely, possibility, severity, crypticity, and manipulability, for privacy leak behavior analysis based on Privacy Petri Net (PPN). In order to compare the privacy leak behavior among different software, we further propose a comprehensive metric, namely, overall leak degree, based on these four metrics. Finally, we validate the effectiveness of the proposed approach using real-world software applications. The experimental results demonstrate that our approach can quantitatively analyze the privacy leak behaviors of various software types and reveal their characteristics from different aspects. |
format | Online Article Text |
id | pubmed-3774722 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37747222013-09-24 Comprehensive Quantitative Analysis on Privacy Leak Behavior Fan, Lejun Wang, Yuanzhuo Jin, Xiaolong Li, Jingyuan Cheng, Xueqi Jin, Shuyuan PLoS One Research Article Privacy information is prone to be leaked by illegal software providers with various motivations. Privacy leak behavior has thus become an important research issue of cyber security. However, existing approaches can only qualitatively analyze privacy leak behavior of software applications. No quantitative approach, to the best of our knowledge, has been developed in the open literature. To fill this gap, in this paper we propose for the first time four quantitative metrics, namely, possibility, severity, crypticity, and manipulability, for privacy leak behavior analysis based on Privacy Petri Net (PPN). In order to compare the privacy leak behavior among different software, we further propose a comprehensive metric, namely, overall leak degree, based on these four metrics. Finally, we validate the effectiveness of the proposed approach using real-world software applications. The experimental results demonstrate that our approach can quantitatively analyze the privacy leak behaviors of various software types and reveal their characteristics from different aspects. Public Library of Science 2013-09-16 /pmc/articles/PMC3774722/ /pubmed/24066046 http://dx.doi.org/10.1371/journal.pone.0073410 Text en © 2013 Fan et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Fan, Lejun Wang, Yuanzhuo Jin, Xiaolong Li, Jingyuan Cheng, Xueqi Jin, Shuyuan Comprehensive Quantitative Analysis on Privacy Leak Behavior |
title | Comprehensive Quantitative Analysis on Privacy Leak Behavior |
title_full | Comprehensive Quantitative Analysis on Privacy Leak Behavior |
title_fullStr | Comprehensive Quantitative Analysis on Privacy Leak Behavior |
title_full_unstemmed | Comprehensive Quantitative Analysis on Privacy Leak Behavior |
title_short | Comprehensive Quantitative Analysis on Privacy Leak Behavior |
title_sort | comprehensive quantitative analysis on privacy leak behavior |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3774722/ https://www.ncbi.nlm.nih.gov/pubmed/24066046 http://dx.doi.org/10.1371/journal.pone.0073410 |
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