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PERCOM
2007
ACM
14 years 8 months ago
Macro Programming through Bayesian Networks: Distributed Inference and Anomaly Detection
Macro programming a distributed system, such as a sensor network, is the ability to specify application tasks at a global level while relying on compiler-like software to translat...
Marco Mamei, Radhika Nagpal
ICANNGA
2009
Springer
201views Algorithms» more  ICANNGA 2009»
14 years 3 months ago
A Novel Signal-Based Approach to Anomaly Detection in IDS Systems
In this paper we present our original methodology, in which Matching Pursuit is used for networks anomaly and intrusion detection. The architecture of anomaly-based IDS based on si...
Lukasz Saganowski, Michal Choras, Rafal Renk, Wito...
IPPS
2007
IEEE
14 years 3 months ago
An Approach to Detect Executable Content for Anomaly Based Network Intrusion Detection
Since current internet threats contain not only malicious codes like Trojan or worms, but also spyware and adware which do not have explicit illegal content, it is necessary to hav...
Like Zhang, Gregory B. White
TR
2010
204views Hardware» more  TR 2010»
13 years 3 months ago
Anomaly Detection Through a Bayesian Support Vector Machine
This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
Vasilis A. Sotiris, Peter W. Tse, Michael Pecht
ICC
2009
IEEE
123views Communications» more  ICC 2009»
14 years 3 months ago
Combining Hidden Markov Models for Improved Anomaly Detection
—In host-based intrusion detection systems (HIDS), anomaly detection involves monitoring for significant deviations from normal system behavior. Hidden Markov Models (HMMs) have...
Wael Khreich, Eric Granger, Robert Sabourin, Ali M...