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Improving attack detection in self-organizing networks: A trust-based approach toward alert satisfaction

机译:改进自组织网络中的攻击检测:一种基于信任的警报满意度方法

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Cyber security has become a major challenge when detecting and preventing attacks on any self-organizing network. Defining a trust and reputation mechanism is a required feature in these networks to assess whether the alerts shared by their Intrusion Detection Systems (IDS) actually report a true incident. This paper presents a way of measuring the trustworthiness of the alerts issued by the IDSs of a collaborative intrusion detection network, considering the detection skills configured in each IDS to calculate the satisfaction on each interaction (alert sharing) and, consequently, to update the reputation of the alert issuer. Without alert satisfaction, collaborative attack detection cannot be a reality in front of ill-intended IDSs. Conducted experiments demonstrate a better accuracy when detecting attacks.
机译:在检测和防止对任何自组织网络的攻击时,网络安全已成为一项主要挑战。定义信任和信誉机制是这些网络中的一项必需功能,以评估其入侵检测系统(IDS)共享的警报是否实际报告了真实事件。本文提出了一种测量协作入侵检测网络的IDS发出的警报的可信赖度的方法,其中考虑了每个IDS中配置的检测技能,以计算每个交互(警报共享)的满意度,从而更新信誉。警报发布者。没有警报的满意度,在恶意IDS面前,协作攻击检测就不可能成为现实。进行的实验表明,检测攻击时具有更高的准确性。

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