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ACSAC
2003
IEEE
15 years 1 months ago
Bayesian Event Classification for Intrusion Detection
Intrusion detection systems (IDSs) attempt to identify attacks by comparing collected data to predefined signatures known to be malicious (misuse-based IDSs) or to a model of lega...
Christopher Krügel, Darren Mutz, William K. R...
JSW
2007
185views more  JSW 2007»
14 years 9 months ago
A Decision Support System base line Flexible Architecture to Intrusion Detection
—Becoming more competitive and more effective in the current scenes of Business and Public Administration, the organizations must be able to approach easily and quickly to the in...
Marcello Castellano, Giuseppe Mastronardi, Angela ...
HICSS
2003
IEEE
118views Biometrics» more  HICSS 2003»
15 years 2 months ago
On-Line Intrusion Detection and Attack Prevention Using Diversity, Generate-and-Test, and Generalization
We have built a system for protecting Internet services to securely connected, known users. It implements a generate-and-test approach for on-line attack identification and uses s...
James C. Reynolds, James E. Just, Larry A. Clough,...
JCP
2006
173views more  JCP 2006»
14 years 9 months ago
Database Intrusion Detection using Weighted Sequence Mining
Data mining is widely used to identify interesting, potentially useful and understandable patterns from a large data repository. With many organizations focusing on webbased on-lin...
Abhinav Srivastava, Shamik Sural, Arun K. Majumdar
KAIS
2007
120views more  KAIS 2007»
14 years 9 months ago
Capabilities of outlier detection schemes in large datasets, framework and methodologies
Abstract. Outlier detection is concerned with discovering exceptional behaviors of objects. Its theoretical principle and practical implementation lay a foundation for some importa...
Jian Tang, Zhixiang Chen, Ada Wai-Chee Fu, David W...