Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Fan, Lejun, Wang, Yuanzhuo, Jin, Xiaolong, Li, Jingyuan, Cheng, Xueqi, Jin, Shuyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
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
_version_ 1782284504447057920
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
work_keys_str_mv AT fanlejun comprehensivequantitativeanalysisonprivacyleakbehavior
AT wangyuanzhuo comprehensivequantitativeanalysisonprivacyleakbehavior
AT jinxiaolong comprehensivequantitativeanalysisonprivacyleakbehavior
AT lijingyuan comprehensivequantitativeanalysisonprivacyleakbehavior
AT chengxueqi comprehensivequantitativeanalysisonprivacyleakbehavior
AT jinshuyuan comprehensivequantitativeanalysisonprivacyleakbehavior