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Inferring the Stealthy Bridges Between Enterprise Network Islands in Cloud Using Cross-Layer Bayesian Networks Read chapter Read first chapter

2015 | OriginalPaper | Chapter

RAMSES: Revealing Android Malware Through String Extraction and Selection

Authors : Lautaro Dolberg, Quentin Jérôme, Jérôme François, Radu State, Thomas Engel

Published in: International Conference on Security and Privacy in Communication Networks

Publisher: Springer International Publishing

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Abstract

The relevance of malicious software targeting mobile devices has been increasing in recent years. Smartphones, tablet computers or embedded devices in general represent one of the most spread computing platform worldwide and an unsecure usage can cause unprecedented damage to private users, companies and public institutions. To help in identifying malicious software on mobile platforms, we propose RAMSES, an approach based on the static content stored as strings within an application. First we extract the contents of strings, transforming applications into documents, then using information retrieval techniques, we select the most relevant features based on frequency metrics, and finally we classify applications using machine learning algorithms relying on such features. We evaluate our methods using real datasets of Android applications and show promising results for detection.

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Footnotes
Literature
1.
Batyuk, L., Herpich, M., Camtepe, S.A., Raddatz, K., Schmidt, A.D., Albayrak, S.: Using static analysis for automatic assessment and mitigation of unwanted and malicious activities within android applications. In: International Conference on Malicious and Unwanted Software, pp. 66–72 (2011)
2.
3.
Bremer, J.: Automated analysis and deobfuscation of android apps & malware. In: AthCON (2013)
4.
Felt, A.P., Ha, E., Egelman, S., Haney, A., Chin, E., Wagner, D.: Android permissions: user attention, comprehension, and behavior. Technical report, EECS Department, University of California, Berkeley, February 2012
5.
Grace, M., Zhou, Y., Zhang, Q., Zou, S., Jiang, X.: Riskranker: scalable and accurate zero-day android malware detection. In: Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services, MobiSys (2012)
6.
Kilinc, C., Booth, T., Andersson, K.: Walldroid: Cloud assisted virtualized application specific firewalls for the android os. In: Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE (2012)
7.
Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)CrossRefMATH
8.
Sahs, J., Khan, L.: A machine learning approach to android malware detection. In: Intelligence and Security Informatics Conference (EISIC). IEEE (2012)
9.
Sanz, B., Santos, I., Laorden, C., Ugarte-Pedrero, X., Bringas, P.: On the automatic categorisation of android applications. In: 2012 IEEE Consumer Communications and Networking Conference (CCNC). IEEE (2012)
10.
Shabtai, A., Kanonov, U., Elovici, Y., Glezer, C., Weiss, Y.: Andromaly: a behavioral malware detection framework for android devices. J. Intell. Inf. Syst. 38(1), 161–190 (2011)CrossRef
11.
Wang, R., Xing, L., Wang, X., Chen, S.: Conference on computer and communications security (ccs). In: Unauthorized Origin Crossing on Mobile Platforms: Threats and Mitigation. ACM (2013)
12.
Witten, I.H., Frank, E., Hall, M.A.: Data Mining: Practical Machine Learning Tools and Techniques, 3 edn. Morgan Kaufmann, San Francisco
13.
Zhou, Y., Jiang, X.: Dissecting android malware: characterization and evolution. In: Symposium on Security and Privacy. IEEE (2012)
Metadata
Title
RAMSES: Revealing Android Malware Through String Extraction and Selection
Authors
Lautaro Dolberg
Quentin Jérôme
Jérôme François
Radu State
Thomas Engel
Copyright Year
2015
Book
International Conference on Security and Privacy in Communication Networks

Print ISBN: 978-3-319-23828-9

Electronic ISBN: 978-3-319-23829-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-23829-6_34

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