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» Anomaly Detection Through a Bayesian Support Vector Machine
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TR
2010
204views Hardware» more  TR 2010»
12 years 11 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
ICMLA
2003
13 years 5 months ago
Robust Support Vector Machines for Anomaly Detection in Computer Security
— Using the 1998 DARPA BSM data set collected at MIT’s Lincoln Labs to study intrusion detection systems, the performance of robust support vector machines (RVSMs) was compared...
Wenjie Hu, Yihua Liao, V. Rao Vemuri
CNSM
2010
13 years 1 months ago
Risk management in VoIP infrastructures using support vector machines
Telephony over IP is exposed to multiple security threats. Conventional protection mechanisms do not fit into the highly dynamic, open and large-scale settings of VoIP infrastructu...
Mohamed Nassar, Oussema Dabbebi, Remi Badonnel, Ol...
VLDB
2007
ACM
164views Database» more  VLDB 2007»
14 years 4 months ago
A new intrusion detection system using support vector machines and hierarchical clustering
Whenever an intrusion occurs, the security and value of a computer system is compromised. Network-based attacks make it difficult for legitimate users to access various network ser...
Latifur Khan, Mamoun Awad, Bhavani M. Thuraisingha...
NIPS
2004
13 years 5 months ago
Density Level Detection is Classification
We show that anomaly detection can be interpreted as a binary classification problem. Using this interpretation we propose a support vector machine (SVM) for anomaly detection. We...
Ingo Steinwart, Don R. Hush, Clint Scovel