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» Semantics-Aware Malware Detection
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GECCO
2009
Springer
161views Optimization» more  GECCO 2009»
15 years 6 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 4 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
15 years 11 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 3 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 1 days ago
A semantics-based approach to malware detection
Mila Dalla Preda, Mihai Christodorescu, Somesh Jha...