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CONEXT
2007
ACM
14 years 11 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
BIBE
2007
IEEE
162views Bioinformatics» more  BIBE 2007»
15 years 4 months ago
An Investigation into the Feasibility of Detecting Microscopic Disease Using Machine Learning
— The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. We are investigating the possibility of de...
Mary Qu Yang, Jack Y. Yang
ICPR
2010
IEEE
15 years 1 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...
ISI
2007
Springer
14 years 9 months ago
Host Based Intrusion Detection using Machine Learning
—Detecting unknown malicious code (malcode) is a challenging task. Current common solutions, such as anti-virus tools, rely heavily on prior explicit knowledge of specific instan...
Robert Moskovitch, Shay Pluderman, Ido Gus, Dima S...
CLEF
2011
Springer
13 years 9 months ago
Detecting Wikipedia Vandalism using Machine Learning - Notebook for PAN at CLEF 2011
Wikipedia vandalism identification is a very complex issue, which is now mostly solved manually by volunteers. This paper presents the main components of a system built by our grou...
Cristian-Alexandru Dragusanu, Marina Cufliuc, Adri...