Title :
A New Similarity Measure for the Anomaly Intrusion Detection
Author :
Belkhirat, Ahmed ; Bouras, Abdelghani ; Belkhir, Abdelkader
Author_Institution :
Inf. Syst. Dept., King Saud Univ., Riyadh, Saudi Arabia
Abstract :
This paper introduces a new similarity measure that can be applied for the anomaly intrusion detection by using weighted complete bipartite graphs. The first set of nodes represents users, while the second set depicts the characteristics defining his profile. The weight on each edge is computed from the frequency of appearances of characteristics for a given user. We demonstrate the validity of our measure by fulfilling the set of rules defined for any similarity measure.
Keywords :
graph theory; security of data; anomaly intrusion detection; similarity measure; weighted complete bipartite graphs; Bipartite graph; Communication system security; Computer networks; Computer security; Educational institutions; Industrial engineering; Information security; Information systems; Intrusion detection; Neural networks; anomaly detection; similarity measure; weighted bipartite graph;
Conference_Titel :
Network and System Security, 2009. NSS '09. Third International Conference on
Conference_Location :
Gold Coast, QLD
Print_ISBN :
978-1-4244-5087-9
Electronic_ISBN :
978-0-7695-3838-9
DOI :
10.1109/NSS.2009.20
