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» A behavioral approach to worm detection
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ISI
2007
Springer
13 years 5 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...
INFOCOM
2005
IEEE
13 years 11 months ago
The effect of DNS delays on worm propagation in an IPv6 Internet
— It is a commonly held belief that IPv6 provides greater security against random-scanning worms by virtue of a very sparse address space. We show that an intelligent worm can ex...
Abhinav Kamra, Hanhua Feng, Vishal Misra, Angelos ...
IPCCC
2006
IEEE
13 years 11 months ago
Automatically deducing propagation sequences that circumvent a collaborative worm defense
We present an approach to the question of evaluating worm defenses against future, yet unseen and possibly defense-aware worm behavior. Our scheme employs model checking to produc...
Linda Briesemeister, Phillip A. Porras
INFOCOM
2005
IEEE
13 years 11 months ago
Defending against Internet worms: a signature-based approach
Abstract— With the capability of infecting hundreds of thousands of hosts, worms represent a major threat to the Internet. The defense against Internet worms is largely an open p...
Yong Tang, Shigang Chen
CSDA
2008
147views more  CSDA 2008»
13 years 5 months ago
Detection of unknown computer worms based on behavioral classification of the host
Machine learning techniques are widely used in many fields. One of the applications of machine learning in the field of the information security is classification of a computer be...
Robert Moskovitch, Yuval Elovici, Lior Rokach