Abstract
In this paper, we propose an automated, scalable, and dynamic analysis framework incorporating static anti anti-analysis techniques to detect the analysis environment aware Android malware and Resource Hogger apps. The proposed framework can automatically trigger malicious execution by sending simulated User-Interface (UI) events and Intent broadcasts. The Proposed approach is scalable and platform invarient for different Android OS versions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Android tools: Adb, emulator, avd manager, android, mksdcard, monkey, logcat. http://developer.android.com/tools/help
Android Security Overview. http://source.android.com/devices/tech/security (Online last accesed on 24 April 2014)
Blasing, T., Batyuk, L., Schmidt, A.-D., Camtepe, S.A., Albayrak, S.: An android application sandbox system for suspicious software detection. In: 5th International Conference on Malicious and Unwanted Software (MALWARE), 2010, pp. 55–62. IEEE (2010)
G. Inc., Android Smartphone Sales Report (2013). http://www.gartner.com/newsroom/id/2665715 (online last accessed 17 March 2014)
Lindorfer, M.: Andrubis: a tool for analyzing unknown android applications. http://blog.iseclab.org/2012/06/04/andrubis-a-tool-for-analyzing-unknown-android-applications-2/
Mulliner, C.: Dalvik dynamic instrumentation, October 2013. http://www.mulliner.org/android/feed/mulliner_dbi_hitb_kul2013.pdf
Rastogi, V., Chen, Y., Enck, W.: Appsplayground: automatic security analysis of smartphone applications. In: Proceedings of the Third ACM Conference on Data and Application Security and Privacy, CODASPY 2013, pp. 209–220. ACM, New York (2013)
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 (2012)
Suarez-Tangil, G., Conti, M., Tapiador, J.E., Peris-Lopez, P.: Detecting targeted smartphone malware with behavior-triggering stochastic models. In: Kutyłowski, M., Vaidya, J. (eds.) ICAIS 2014, Part I. LNCS, vol. 8712, pp. 183–201. Springer, Heidelberg (2014)
Yan, L.K., Yin, H.: Droidscope: Seamlessly reconstructing the os and dalvik semantic views for dynamic android malware analysis. In: Proceedings of the 21st USENIX Conference on Security Symposium, Security 2012, pp. 29–29. USENIX Association, Berkeley (2012)
Zheng, M., Lee, P.P.C., Lui, J.C.S.: ADAM: an automatic and extensible platform to stress test android anti-virus systems. In: Flegel, U., Markatos, E., Robertson, W. (eds.) DIMVA 2012. LNCS, vol. 7591, pp. 82–101. Springer, Heidelberg (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Faruki, P., Kumar, V., B., A., Gaur, M.S., Laxmi, V., Conti, M. (2015). Platform Neutral Sandbox for Analyzing Malware and Resource Hogger Apps. In: Tian, J., Jing, J., Srivatsa, M. (eds) International Conference on Security and Privacy in Communication Networks. SecureComm 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 152. Springer, Cham. https://doi.org/10.1007/978-3-319-23829-6_43
Download citation
DOI: https://doi.org/10.1007/978-3-319-23829-6_43
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23828-9
Online ISBN: 978-3-319-23829-6
eBook Packages: Computer ScienceComputer Science (R0)