Runtime-Based Behavior Dynamic Analysis System for Android Malware Detection

Luo Xu Min; Qing Hua  Cao

doi:10.4028/www.scientific.net/AMR.756-759.2220

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 756-759Runtime-Based Behavior Dynamic Analysis System for...

Runtime-Based Behavior Dynamic Analysis System for Android Malware Detection

Abstract:

The most serious threats for Android users is come from application, However, the market lack a mechanism to validate whether these applications are malware or not. So, malware maybe leak users private information, malicious deductions for send premium SMS, get root privilege of the Android system and so on. In the traditional method of malware detection, signature is the only basis. It is far enough. In this paper, we propose a runtime-based behavior dynamic analysis for Android malware detection. The new scheme can be implemented as a system. We analyze 350 applications come from third-party Android market, the result show that our system can effectively detect unknown malware and the malicious behavior of malware.

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Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

2220-2225

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.756-759.2220

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Online since:

September 2013

Authors:

Luo Xu Min, Qing Hua Cao

Keywords:

Android, Android Security, Dynamic Detection, Malwares

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References

[1] Gartner Inc. Android, Apple to spark surge in smart device sales http: /www. gartner. com/it/ page. jsp?id=1622614.

Google Scholar

[2] Symantec Inc. Android. Geinimi http: /www. symantec. com/security_response/writeup. jsp? docid=2011-010111-5403-99.

Google Scholar

[3] Update: Android Malware DroidDream: How it Works https: /blog. lookout. com/blog/2011/03/02/Android-malware-droiddream-how-it-works.

Google Scholar

[4] ENCK,W.W. ONGTANG., and mcdaniel,P. On lightweight Mobile Phone Application certification. In Procees-ings of the 16th ACM Conference on Computer and Communications Security.

DOI: 10.1145/1653662.1653691

Google Scholar

[5] Android . https: /www. Android. com.

Google Scholar

[6] AndroidOS. FakePlayer http: /www. symantec. com/security_response/writeup. jsp?docid=2010-081100-1646-99.

Google Scholar

[7] Yajin Zhou , Zhi Wang, Wu Zhou, Xuxian Jiang. hey, You Get Off of My Market: Detecting Malicious Apps in Offical and Alternative Android Market. the 19th Network and Distributed System Security Symposium (NDSS 2012), San Diego, CA, February (2012).

Google Scholar

[8] Smali https: /code. google. com/p/smali.

Google Scholar

[9] De Goyeneche, J. -M.; De Sousa, E.A.F. Loadable kernel modules Volume: 16, Issue: 1 Digital Object Identifier: 10. 1109/52. 744571 Publication Year: 1999 , Page(s): 65- 71.

DOI: 10.1109/52.744571

Google Scholar