IDS false alarm filtering using KNN classifier

Lecture Notes in Computer Science

Volumn 3325, Issue , 2005, Pages 114-121

  Law, Kwok Ho ^a   Kwok, Lam For ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

ALARM SYSTEMS; CLASSIFIERS; MATHEMATICAL MODELS; PROBLEM SOLVING; WORK-REST SCHEDULES;

FALSE ALARM RATE; INTRUSION DETECTION SYSTEMS (IDE); SECURITY OFFICERS; WORKLOADS;

SECURITY OF DATA;

EID: 23944484457     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-31815-6_10     Document Type: Conference Paper

References (10)

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4. A. Seleznyov and S. Puuronen: HIDSUR: a hybrid intrusion detection system based on real-time user recognition, Proceedings of 11th International Workshop on Database and Expert Systems Applications, 2000, pp. 41-45.
5. S. Manganaris, M. Christensen, D. Zerkle and K. Hermiz: A data mining analysis of RTID alarms, Computer Networks, Vol. 34, Issue 4, 2000, pp. 571-577.
6. K. Julisch: Mining Alarm Clusters to Improve Alarm Handling Efficiency, Proceedings of the 17th Annual Conference on Computer Security Applications, 2001, pp. 12-21.
7. K. Julisch and M. Dacier: Mining Intrusion Detection Alarms for Actionable Knowledge, Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002, pp. 266-375.
8. Y. Liao and V. R. Vemuri: Use of K-Nearest Neighbor classifier for intrusion detection, Computers and Security, Vol. 21, Issue 5, 2002, pp. 439-448.
9. DARPA Intrusion Detection Evaluation, MIT Lincoln Laboratory, http://www.ll.mit.edu/IST/ideval/
10. Snort, http://www.snort.org/