Article

Revisiting LISYS: parameters and normal behavior

Authors:

J. Balthrop,

S. Forrest,

M. R. GlickmanAuthors Info & Claims

CEC '02: Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02

Pages 1045 - 1050

Published: 12 May 2002 Publication History

Publisher Site

Abstract

This paper studies a simplified form of LISYS, an artificial immune system for network intrusion detection. The paper describes results based on a new, more controlled data set than that used for earlier studies. The paper also looks at which parameters appear most important for minimizing false positives, as well as the trade-offs and relationships among parameter settings.

Cited By

View all

Idris ISelamat AOmatu S(2014)Hybrid email spam detection model with negative selection algorithm and differential evolutionEngineering Applications of Artificial Intelligence10.1016/j.engappai.2013.12.00128(97-110)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1016/j.engappai.2013.12.001
Wu SBanzhaf W(2010)ReviewApplied Soft Computing10.1016/j.asoc.2009.06.01910:1(1-35)Online publication date: 1-Jan-2010
https://dl.acm.org/doi/10.1016/j.asoc.2009.06.019
Stibor T(2009)Foundations of r-contiguous matching in negative selection for anomaly detectionNatural Computing: an international journal10.1007/s11047-008-9097-58:3(613-641)Online publication date: 1-Sep-2009
https://dl.acm.org/doi/10.1007/s11047-008-9097-5
Show More Cited By

Recommendations

Revisiting the central and peripheral immune system
ICARIS'07: Proceedings of the 6th international conference on Artificial immune systems

The idiotypic network has a long and chequered history in both theoretical immunology and Artificial Immune Systems. In terms of the latter, the drive for engineering applications has led to a diluted interpretation of the immunological models. Research ...
Revisiting the Foundations of Artificial Immune Systems for Data Mining

This paper advocates a problem-oriented approach for the design of artificial immune systems (AIS) for data mining. By problem-oriented approach we mean that, in real-world data mining applications the design of an AIS should take into account the ...
POSTER: Revisiting anomaly detection system design philosophy
CCS '13: Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security

The inherent design of anomaly detection systems (ADSs) make them highly susceptible to evasion attacks and hence their wide-spread commercial deployment has not been witnessed. There are two main reasons for this: 1) ADSs incur high false positives; 2) ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

CEC '02: Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02

May 2002

1034 pages

ISBN:0780372824

Publisher

IEEE Computer Society

United States

Publication History

Published: 12 May 2002

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

14
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 23 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Idris ISelamat AOmatu S(2014)Hybrid email spam detection model with negative selection algorithm and differential evolutionEngineering Applications of Artificial Intelligence10.1016/j.engappai.2013.12.00128(97-110)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1016/j.engappai.2013.12.001
Wu SBanzhaf W(2010)ReviewApplied Soft Computing10.1016/j.asoc.2009.06.01910:1(1-35)Online publication date: 1-Jan-2010
https://dl.acm.org/doi/10.1016/j.asoc.2009.06.019
Stibor T(2009)Foundations of r-contiguous matching in negative selection for anomaly detectionNatural Computing: an international journal10.1007/s11047-008-9097-58:3(613-641)Online publication date: 1-Sep-2009
https://dl.acm.org/doi/10.1007/s11047-008-9097-5
Powers SHe J(2008)A hybrid artificial immune system and Self Organising Map for network intrusion detectionInformation Sciences: an International Journal10.1016/j.ins.2007.11.028178:15(3024-3042)Online publication date: 1-Aug-2008
https://dl.acm.org/doi/10.1016/j.ins.2007.11.028
Drozda MSchaust SSzczerbicka H(2007)Is AIS Based Misbehavior Detection Suitable for Wireless Sensor Networks?Proceedings of the 2007 IEEE Wireless Communications and Networking Conference10.1109/WCNC.2007.578(3128-3133)Online publication date: 1-Mar-2007
https://dl.acm.org/doi/10.1109/WCNC.2007.578
Ingham KSomayaji ABurge JForrest S(2007)Learning DFA representations of HTTP for protecting web applicationsComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2006.09.01651:5(1239-1255)Online publication date: 1-Apr-2007
https://dl.acm.org/doi/10.1016/j.comnet.2006.09.016
Dozier GBrown DHou HHurley J(2007)Vulnerability analysis of immunity-based intrusion detection systems using genetic and evolutionary hackersApplied Soft Computing10.1016/j.asoc.2006.05.0017:2(547-553)Online publication date: 1-Mar-2007
https://dl.acm.org/doi/10.1016/j.asoc.2006.05.001
Hou HDozier GMenezes R(2006)An evaluation of negative selection algorithm with constraint-based detectorsProceedings of the 44th annual ACM Southeast Conference10.1145/1185448.1185479(134-139)Online publication date: 10-Mar-2006
https://dl.acm.org/doi/10.1145/1185448.1185479
Pasek R(2006)Theoretical basis of novelty detection in time series using negative selection algorithmsProceedings of the 5th international conference on Artificial Immune Systems10.1007/11823940_29(376-389)Online publication date: 4-Sep-2006
https://dl.acm.org/doi/10.1007/11823940_29
Glickman MBalthrop JForrest S(2005)A Machine Learning Evaluation of an Artificial Immune SystemEvolutionary Computation10.1162/106365605408850313:2(179-212)Online publication date: 1-Jun-2005
https://dl.acm.org/doi/10.1162/1063656054088503
Show More Cited By

Abstract

Cited By

Recommendations

Revisiting the central and peripheral immune system

Revisiting the Foundations of Artificial Immune Systems for Data Mining

POSTER: Revisiting anomaly detection system design philosophy

Comments

Information

Published In

Publisher

Publication History

Qualifiers

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations