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On the Detectability of Weak DoS Attacks in Wireless Sensor Networks

机译:关于无线传感器网络弱DOS攻击的可检测性

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Anomaly detection can be used to detect malicious attacks in wireless sensor networks. Because of the autonomous nature of many sensor network scenarios, it is desirable to use an auto-configuring anomaly detector. To accomodate the indeterministic wireless environment, the anomaly detection must also be able to adapt to changing conditions. This work presents a dynamic learning extension for a pre-exisiting, autoconfiguring anomaly detection system for WSNs. Adaptability always results in possibilities for an attacker to exploit the adapting system; however, no quantitative analysis of this has been yet performed in a WSN scenario. This paper explores the trade-off between adaptability and exploitability of the system. The paper also shows that adaptability does not guarantee better false positive error rates for all attacks.
机译:异常检测可用于检测无线传感器网络中的恶意攻击。由于许多传感器网络场景的自主性质,期望使用自动配置异常检测器。为了满足不确定的无线环境,异常检测还必须能够适应变化的条件。这项工作提出了用于WSN的预测,自动配置异常检测系统的动态学习扩展。适应性始终导致攻击者利用适应系统的可能性;但是,在WSN场景中没有对此进行定量分析。本文探讨了系统适应性与利用之间的权衡。本文还表明,适应性不保证所有攻击的更好的误报率。

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