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» Detecting worm variants using machine learning
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ANCS
2006
ACM
13 years 10 months ago
WormTerminator: an effective containment of unknown and polymorphic fast spreading worms
The fast spreading worm is becoming one of the most serious threats to today’s networked information systems. A fast spreading worm could infect hundreds of thousands of hosts w...
Songqing Chen, Xinyuan Wang, Lei Liu, Xinwen Zhang
MOBISYS
2008
ACM
14 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
IDEAL
2004
Springer
13 years 10 months ago
Detecting Worm Propagation Using Traffic Concentration Analysis and Inductive Learning
As a vast number of services have been flooding into the Internet, it is more likely for the Internet resources to be exposed to various hacking activities such as Code Red and SQL...
Sanguk Noh, Cheolho Lee, Keywon Ryu, Kyunghee Choi...
ICAC
2006
IEEE
13 years 10 months ago
Fast and Effective Worm Fingerprinting via Machine Learning
— As Internet worms become ever faster and more sophisticated, it is important to be able to extract worm signatures in an accurate and timely manner. In this paper, we apply mac...
Stewart M. Yang, Jianping Song, Harish Rajamani, T...
IEICET
2007
142views more  IEICET 2007»
13 years 4 months ago
Detecting Unknown Worms Using Randomness Check
From the appearance of CodeRed and SQL Slammer worm, we have learned that the early detection of worm epidemics is important to reduce the damage caused by their outbreak. One prom...
Hyundo Park, Heejo Lee, Hyogon Kim