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Volume 30 Issue 6
November  2015
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Le-Jun Fan, Yuan-Zhuo Wang, Jing-Yuan Li, Xue-Qi Cheng, Chuang Lin. Privacy Petri Net and Privacy Leak Software[J]. Journal of Computer Science and Technology, 2015, 30(6): 1318-1343. DOI: 10.1007/s11390-015-1601-7
Citation: Le-Jun Fan, Yuan-Zhuo Wang, Jing-Yuan Li, Xue-Qi Cheng, Chuang Lin. Privacy Petri Net and Privacy Leak Software[J]. Journal of Computer Science and Technology, 2015, 30(6): 1318-1343. DOI: 10.1007/s11390-015-1601-7
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Privacy Petri Net and Privacy Leak Software

  • 1 National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100029, China;
    2 Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;
    3 Department of Computer Science and Technology, Tsinghua University, Beijing 100083, China

Funds: This work is supported by the National Natural Science Foundation of China under Grant Nos. 61402124, 61402022, 61173008, 60933005, and 61572469, the National Key Technology Research and Development Program of China under Grant No. 2012BAH39B02, the 242 Projects of China under Grant No. 2011F45, and Beijing Nova Program under Grant No. Z121101002512063.
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  • Author Bio:

    Le-Jun Fan received his B.S. and M.S. degrees in circuit and system from the University of Science and Technology of China, Hefei, in 2004 and 2007 respectively. He received his Ph.D. degree in information security in 2013 from the Research Center of Web Data Science & Engineering of the Institute of Computing Technology, Chinese Academy of Sciences, Beijing. His research interests include software malicious behavior analysis, data privacy and Petri nets. He is a member of IEEE. He is now working at National Computer Network Emergency Response Technical Team/Coordination Center of China.

  • Corresponding author:

    Yuan-Zhuo Wang E-mail: wangyuanzhuo@ict.ac.cn

  • Received Date: March 26, 2014
  • Revised Date: June 01, 2015
  • Published Date: November 04, 2015
    Abstract
  • Private information leak behavior has been widely discovered in malware and suspicious applications. We refer to such software as privacy leak software (PLS). Nowadays, PLS has become a serious and challenging problem to cyber security. Previous methodologies are of two categories: one focuses on the outbound network traffic of the applications; the other dives into the inside information flow of the applications. We present an abstract model called Privacy Petri Net (PPN) which is more applicable to various applications and more intuitive and vivid to users. We apply our approach to both malware and suspicious applications in real world. The experimental result shows that our approach can effectively find categories, content, procedure, destination and severity of the private information leaks for the target software.
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