Monitoring security events using integrated Correlation-based techniques


We propose an adaptive cyber security monitoring system that integrates a number of component techniques to collect time-series situation information, perform intrusion detec- tion, and characterize and identify security events so corre- sponding defense actions can be taken in a timely and effec- tive manner. We employ a decision fusion algorithm with analytically proven performance guarantee for intrusion de- tection based on local votes from distributed sensors. The security events in the proposed system are represented as forms of correlation networks using random matrix theory and identified through the computation of network similarity measurement. Extensive simulation results on event identi- fication illustrate the efficacy of the proposed system.Copyright 2009 ACM.

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ACM International Conference Proceeding Series