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» Semantics-Aware Malware Detection
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GECCO
2009
Springer
161views Optimization» more  GECCO 2009»
15 years 11 months ago
Are evolutionary rule learning algorithms appropriate for malware detection?
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classiï...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 9 months ago
On the appropriateness of evolutionary rule learning algorithms for malware detection
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classiï...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...
MOBISYS
2008
ACM
16 years 4 months ago
Behavioral detection of malware on mobile handsets
A novel behavioral detection framework is proposed to detect mobile worms, viruses and Trojans, instead of the signature-based solutions currently available for use in mobile devi...
Abhijit Bose, Xin Hu, Kang G. Shin, Taejoon Park
ICPR
2010
IEEE
15 years 7 months ago
Malware Detection on Mobile Devices Using Distributed Machine Learning
This paper presents a distributed Support Vector Machine (SVM) algorithm in order to detect malicious software (malware) on a network of mobile devices. The light-weight system mo...
Ashkan Sharifi Shamili, Christian Bauckhage, Tansu...
POPL
2007
ACM
16 years 4 months ago
A semantics-based approach to malware detection
Mila Dalla Preda, Mihai Christodorescu, Somesh Jha...