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ML
2010
ACM
155views Machine Learning» more  ML 2010»
13 years 3 months ago
On the infeasibility of modeling polymorphic shellcode - Re-thinking the role of learning in intrusion detection systems
Current trends demonstrate an increasing use of polymorphism by attackers to disguise their exploits. The ability for malicious code to be easily, and automatically, transformed in...
Yingbo Song, Michael E. Locasto, Angelos Stavrou, ...
ICIAP
2005
ACM
14 years 5 months ago
Learning Intrusion Detection: Supervised or Unsupervised?
Abstract. Application and development of specialized machine learning techniques is gaining increasing attention in the intrusion detection community. A variety of learning techniq...
Pavel Laskov, Patrick Düssel, Christin Sch&au...
RAID
2005
Springer
13 years 10 months ago
Environment-Sensitive Intrusion Detection
We perform host-based intrusion detection by constructing a model from a program’s binary code and then restricting the program’s execution by the model. We improve the effecti...
Jonathon T. Giffin, David Dagon, Somesh Jha, Wenke...
INFOCOM
2012
IEEE
11 years 7 months ago
Stochastic analysis of horizontal IP scanning
—Intrusion Detection Systems (IDS) have become ubiquitous in the defense against virus outbreaks, malicious exploits of OS vulnerabilities, and botnet proliferation. As attackers...
Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri...
KBSE
2005
IEEE
13 years 10 months ago
Designing and implementing a family of intrusion detection systems
Intrusion detection systems are distributed applications that analyze the events in a networked system to identify malicious behavior. The analysis is performed using a number of ...
Richard A. Kemmerer