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| An Anomaly Detection Algorithm Based on Artificial Immune Intelligence |
| LIU Li-ping |
| Jiangsu College of Safety technology |
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Abstract Network anomaly detection model can be used to detect unknown attacks, which has good scalability and it is the hot spot of intrusion detection system research. However, the existing anomaly detection methods have some problems such as high false positive rate and low detection efficiency, which can not meet the needs of high-speed network real-time detection. Combining artificial immune algorithm with network anomaly technology, an anomaly network detection algorithm based on artificial immune network (AIAIK) is proposed. Theoretical analysis and experimental results show that the algorithm has good characteristics such as immune network, nonlinear, immune memory and clonal selection of natural immune system, and the experimental detection effect is good.
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