Article

Self-Nonself Discrimination in a Computer

Authors:

Stephanie Forrest,

Alan S. Perelson,

Lawrence Allen,

Rajesh CherukuriAuthors Info & Claims

SP '94: Proceedings of the 1994 IEEE Symposium on Security and Privacy

Page 202

Published: 16 May 1994 Publication History

Publisher Site

Abstract

The problem of protecting computer systems can be viewed generally as the problem of learning to distinguish self from other. We describe a method for change detection which is based on the generation of T cells in the immune system. Mathematical analysis reveals computational costs of the system, and preliminary experiments illustrate how the method might be applied to the problem of computer viruses.

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Lakhotia PDwivedi RSharma DSharma N(2023)Intrusion Detection System for IoE-Based Medical NetworksJournal of Database Management10.4018/JDM.32146534:2(1-18)Online publication date: 14-Apr-2023
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Chen XPang J(2019)A Novelty Network Attack Detection Model based on ImmunologyProceedings of the 2019 2nd International Conference on Data Science and Information Technology10.1145/3352411.3352441(187-196)Online publication date: 19-Jul-2019
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Perkins PHeber SShi XBuck MMa JVeltri P(2019)Using a Novel Negative Selection Inspired Anomaly Detection Algorithm to Identify Corrupted Ribo-seq and RNA-seq SamplesProceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics10.1145/3307339.3342169(457-465)Online publication date: 4-Sep-2019
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Information

Published In

SP '94: Proceedings of the 1994 IEEE Symposium on Security and Privacy

May 1994

Publisher

IEEE Computer Society

United States

Publication History

Published: 16 May 1994

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Lakhotia PDwivedi RSharma DSharma N(2023)Intrusion Detection System for IoE-Based Medical NetworksJournal of Database Management10.4018/JDM.32146534:2(1-18)Online publication date: 14-Apr-2023
https://dl.acm.org/doi/10.4018/JDM.321465
Chen XPang J(2019)A Novelty Network Attack Detection Model based on ImmunologyProceedings of the 2019 2nd International Conference on Data Science and Information Technology10.1145/3352411.3352441(187-196)Online publication date: 19-Jul-2019
https://dl.acm.org/doi/10.1145/3352411.3352441
Perkins PHeber SShi XBuck MMa JVeltri P(2019)Using a Novel Negative Selection Inspired Anomaly Detection Algorithm to Identify Corrupted Ribo-seq and RNA-seq SamplesProceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics10.1145/3307339.3342169(457-465)Online publication date: 4-Sep-2019
https://dl.acm.org/doi/10.1145/3307339.3342169
Dasgupta DNag AFerebee DSaha SSubedi KRoy AMadero ASanchez AWilliams J(2019)Design and implementation of Negative Authentication SystemInternational Journal of Information Security10.1007/s10207-017-0395-818:1(23-48)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s10207-017-0395-8
Sobral dos Santos SWanderley HNeto F(2018)Automatic Selector Between Cardiogenic Oscillation and Airway Secretion in Mechanical Ventilation Flow Signals Using Artificial Immune SystemInternational Journal of Swarm Intelligence Research10.4018/IJSIR.20181001049:4(65-78)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.4018/IJSIR.2018100104
Jevtic SLotfalizadeh HKim D(2018)Toward Network-based DDoS Detection in Software-defined NetworksProceedings of the 12th International Conference on Ubiquitous Information Management and Communication10.1145/3164541.3164562(1-8)Online publication date: 5-Jan-2018
https://dl.acm.org/doi/10.1145/3164541.3164562
Karpov PSquillero GTonda A(2018)VALISGenetic Programming and Evolvable Machines10.1007/s10710-018-9331-619:3(453-471)Online publication date: 1-Sep-2018
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Dudek G(2017)Artificial Immune System With Local Feature Selection for Short-Term Load ForecastingIEEE Transactions on Evolutionary Computation10.1109/TEVC.2016.258604921:1(116-130)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1109/TEVC.2016.2586049
Dong LLIU SZHANG H(2017)A method of anomaly detection and fault diagnosis with online adaptive learning under small training samplesPattern Recognition10.1016/j.patcog.2016.11.02664:C(374-385)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1016/j.patcog.2016.11.026
Fouladvand SOsareh AShadgar BPavone MSharafi S(2017)DENSAEngineering Applications of Artificial Intelligence10.1016/j.engappai.2016.08.01462:C(359-372)Online publication date: 1-Jun-2017
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