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WISA
2004
Springer
13 years 10 months ago
A Probabilistic Method for Detecting Anomalous Program Behavior
In this paper, we, as well as Eskin, Lee, Stolfo [7] propose a method of prediction model. In their method, the program was characterized with both the order and the kind of system...
Kohei Tatara, Toshihiro Tabata, Kouichi Sakurai
ACSAC
1998
IEEE
13 years 9 months ago
Detecting Anomalous and Unknown Intrusions Against Programs
The ubiquity of the Internet connection to desktops has been both boon to business as well as cause for concern for the security of digital assets that may be unknowingly exposed....
Anup K. Gosh, James Wanken, Frank Charron
CASES
2005
ACM
13 years 6 months ago
Anomalous path detection with hardware support
Embedded systems are being deployed as a part of critical infrastructures and are vulnerable to malicious attacks due to internet accessibility. Intrusion detection systems have b...
Tao Zhang, Xiaotong Zhuang, Santosh Pande, Wenke L...
SDM
2008
SIAM
206views Data Mining» more  SDM 2008»
13 years 6 months ago
Latent Variable Mining with Its Applications to Anomalous Behavior Detection
In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
Shunsuke Hirose, Kenji Yamanishi
OOPSLA
2007
Springer
13 years 11 months ago
Probabilistic calling context
Calling context enhances program understanding and dynamic analyses by providing a rich representation of program location. Compared to imperative programs, objectoriented program...
Michael D. Bond, Kathryn S. McKinley