Abstract

Jelena Milosevic, Andreas Dittrich, Miroslaw Malek, Alberto Ferrante,
A Resource-Optimized Approach to Efficient Early Detection of Mobile Malware,
In: 3rd International Workshop on Security of Mobile Applications (IWSMA), pp. 333-340, Fribourg, Switzerland: IEEE Computer Society, 2014.
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Abstract: With explosive growth in the number of mobile devices, the mobile malware is rapidly spreading. Existing solutions, which are mainly based on binary signatures, are no longer effective, making security one of the key issues. The main contribution of this paper is a novel methodology to design and implement secure mobile devices by offering a resource-optimized method that combines efficient, light-weight malware detection on the device with high precision detection methods on cloud servers. We focus on early detection of behavioral patterns of malware families rather than the detection of malware binary signatures. Together with the alarm about the device being attacked, damage that detected type of malware can cause is estimated. Furthermore, the database with behavioral patterns is continuously updated, thus keeping a device resistant to new malware families.

Keywords: mobile malware; information security; distributed detection; machine learning; behavioral patterns

 


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