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An integrated static detection and analysis framework for android

Lookup NU author(s): Professor Raj Ranjan


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The security and privacy issues of android system have attracted a lot of attention from both industry and academia in recent years. Static detection is one typical method to analyze malicious code. However, existing single static detection method can introduce high false alarm rate and is only appropriate for a limited scope. In this paper, we propose an integrated static detection framework, which consists of four layers of filtering mechanisms, that is, the message digest (MD5) values, the combination of malicious permissions, the dangerous permissions, and the dangerous intention, respectively. An intuitive threat-degree model is proposed especially on dangerous permissions detection. Furthermore, we implement a prototype system ASE and validate its feasibility, performance and scalability. A comprehensive evaluation shows that the proposed framework has obvious advantages especially in efficiency, granularity, layers, and correctness. (C) 2016 Elsevier B.V. All rights reserved.

Publication metadata

Author(s): Song J, Han CL, Wang KX, Zhao J, Ranjan RJ, Wang LZ

Publication type: Article

Publication status: Published

Journal: Pervasive and Mobile Computing

Year: 2016

Volume: 32

Pages: 15-25

Print publication date: 01/10/2016

Online publication date: 24/03/2016

Acceptance date: 01/01/1900

ISSN (print): 1574-1192

ISSN (electronic): 1873-1589

Publisher: Elsevier


DOI: 10.1016/j.pmcj.2016.03.003


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Funder referenceFunder name
2014CFB192Hubei Provincial Natural Science Foundation of China
61303212National Natural Science Foundation of China
61332019National Natural Science Foundation of China
U1135004National Natural Science Foundation of China