Name
Abstract | ||
|---|---|---|
We propose an adaptive cyber security monitoring system that integrates a number of component techniques to collect time-series situation information, perform intrusion detection, and characterize and identify security events so corresponding defense actions can be taken in a timely and effective manner. We employ a decision fusion algorithm with analytically proven performance guarantee for intrusion detection 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 identification illustrate the efficacy of the proposed system. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1558607.1558661 | CSIIRW |
Keywords | Field | DocType |
effective manner,integrated correlation-based technique,analytically proven performance guarantee,adaptive cyber security monitoring,component technique,monitoring security event,security event,proposed system,correlation network,corresponding defense action,decision fusion algorithm,intrusion detection,event correlation,time series,random matrix theory,cyber security | Data mining,Decision fusion,Monitoring system,Computer security,Computer science,Performance guarantee,Event correlation,Real-time computing,Correlation,Intrusion detection system,Computation,Random matrix | Conference |
Citations | PageRank | References |
5 | 0.69 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qishi Wu | 1 | 734 | 62.01 |
| Denise Ferebee | 2 | 16 | 3.59 |
| Yunyue Lin | 3 | 86 | 9.04 |
| Dipankar Dasgupta | 4 | 1226 | 121.74 |