DocumentCode
2300638
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
fYear
2009
fDate
19-21 Oct. 2009
Firstpage
431
Lastpage
436
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/NSS.2009.20
Filename
5319327
Link To Document