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2012
ACM

A quantitative study of accuracy in system call-based malware detection

8 years 5 months ago
A quantitative study of accuracy in system call-based malware detection
Over the last decade, there has been a significant increase in the number and sophistication of malware-related attacks and infections. Many detection techniques have been proposed to mitigate the malware threat. A running theme among existing detection techniques is the similar promises of high detection rates, in spite of the wildly different models (or specification classes) of malicious activity used. In addition, the lack of a common testing methodology and the limited datasets used in the experiments make difficult to compare these models in order to determine which ones yield the best detection accuracy. In this paper, we present a systematic approach to measure how the choice of behavioral models influences the quality of a malware detector. We tackle this problem by executing a large number of testing experiments, in which we explored the parameter space of over 200 different models, corresponding to more than 220 million of signatures. Our results suggest that commonly ...
Davide Canali, Andrea Lanzi, Davide Balzarotti, Ch
Added 28 Sep 2012
Updated 28 Sep 2012
Type Journal
Year 2012
Where ISSTA
Authors Davide Canali, Andrea Lanzi, Davide Balzarotti, Christopher Kruegel, Mihai Christodorescu, Engin Kirda
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