基于危险理论的多智能体人工免疫系统异常检测

Haidong Fu, Xiguo Yuan, Na Wang
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引用次数: 18

摘要

受危险理论(DT)潜在的有趣想法的启发,人工免疫系统(AIS)的研究得到了前所未有的发展。嵌入AIS的DT的基本作用是,当某些细胞遭受损伤、应激或“坏细胞死亡”时,通过专业抗原呈递细胞提供t细胞应该做出的反应。然而,在基于als的网络安全系统背景下,如何通过减少病毒感染来减少损害是解决现实问题的关键步骤。本文提出了一种基于DT的多智能体异常检测系统的设计方案,称为MAAIS,该系统可以在评估接收到的危险信号的程度过程中通过配置参数来动态适应各种类型的免疫反应。此外,还采用了一种合适的agent间通信机制来保证系统的良好性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-agents Artificial Immune System (MAAIS) Inspired by Danger Theory for Anomaly Detection
Inspired by the potential interesting ideas of the danger theory (DT), the research into artificial immune system (AIS) has been developing faster then ever. The basic role of DT embedded in AIS is to provide what T-cells should respond through the professional antigen-presenting cells when there are some cells undergoing injury, or stress or 'bad cell death'. However, in the context of AlS-based network security systems, how to minimize damage by mitigating virus infection is a key step to solve real-world problems. In this paper we present the blueprint of a DT inspired multi-agents AIS for anomaly detection, it is called MAAIS, which can dynamically adapt to various types of immune responses by configuring parameters during the course of evaluating the degree of danger signals received. Additionally, a suitable mechanism of communication between agents is employed to stipulate the better performance of the novel system.
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