Information fusion for anomaly detection with the dendritic cell algorithm

被引：68
作者：
Greensmith, Julie [1 ]
Aickelin, Uwe [1 ]
Tedesco, Gianni [1 ]
机构：
[1] Univ Nottingham, Sch Comp Sci, Nottingham NG8 1BB, England
来源：
INFORMATION FUSION | 2010年 / 11卷 / 01期
基金：
英国工程与自然科学研究理事会;
关键词：
Dendritic cells; Data fusion; Immune system; Anomaly detection; Port scans; DANGER; APOPTOSIS; SENSE;
D O I：
10.1016/j.inffus.2009.04.006
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system, providing the initial detection of pathogenic invaders. Research into this family of cells has revealed that they perform information fusion which directs immune responses. We have derived a dendritic cell algorithm based on the functionality of these cells, by modelling the biological signals and differentiation pathways to build a control mechanism for an artificial immune system. We present algorithmic details in addition to experimental results, when the algorithm was applied to anomaly detection for the detection of port scans. The results show the dendritic cell algorithm is successful at detecting port scans. (C) 2009 Elsevier B.V. All rights reserved.
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收藏
页码：21 / 34
页数：14
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