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An alert fusion model inspired by artificial immune system

机译:受人工免疫系统启发的预警融合模型

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摘要

In the recent years one of the most focused topics in the field of network security and more specifically intrusion detection systems was to find a solution to reduce the overwhelming alerts generated by IDSs in the network. Inspired by human defence system and danger theory we propose a complementary subsystem for IDS which can be integrated into any existing IDS models to aggregate the alerts in order to reduce them, and subsequently reduce false alarms among the alerts. After evaluation using different datasets and attack scenarios, our model managed to aggregate the alerts by the average rate of 97.5 percent.
机译:近年来,网络安全领域(尤其是入侵检测系统)最关注的主题之一是找到一种解决方案,以减少网络中IDS产生的压倒性警报。受人防系统和危险理论的启发,我们提出了一个IDS补充子系统,可以将其集成到任何现有IDS模型中以汇总警报,以减少警报,并随后减少警报之间的虚假警报。在使用不同的数据集和攻击场景进行评估之后,我们的模型设法以平均97.5%的比率汇总警报。

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