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An Immune Inspired Network Intrusion Detection System Utilising Correlation Context

机译:利用相关上下文的免疫激发网络入侵检测系统

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Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.
机译:网络入侵检测系统(NIDS)是计算机系统,其监视网络,其目的是从该网络上辨别恶意的目标。虽然各种方法都达到了不同的成功水平,但大多数IDS依赖于访问由安全专家编写的已知攻击签名数据库。如今,为了解决虚假积极警报的问题,使用相关算法将额外的结构添加到ID警报的序列中。然而,这些技术在发现新的攻击或已知攻击的变化方面没有帮助,人类免疫系统(他)能够在自己的专业领域中进行。本文提出了一种用于IDS问题的新型免疫算法。目标是发现包含现有签名基础所涵盖的攻击的新型攻击的数据包。

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