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A hidden Markov model based intrusion detection system for wireless sensor networks

机译:基于隐马尔可夫模型的无线传感器网络入侵检测系统

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摘要

Wireless sensor network (WSN) technology is being increasingly used for data collection in critical infrastructures (CIs). This paper presents an intrusion detection system (IDS), which is able to protect a CI from attacks directed to its WSN-based parts. By providing accurate and timely detection of malicious activities, the proposed IDS solution ultimately results in a dramatic improvement in terms of protection, since opportunities are given for performing proper remediation/reconfiguration actions, which counter the attack and/or allow the system to tolerate it. The proposed solution has the important advantage of exploiting the high accuracy of hidden Markov models as an effective means of detecting malicious activities. We present the basic ideas, discuss the main implementation issues, and perform a preliminary experimental campaign, with respect to sinkhole attacks, one of the most serious attacks to WSNs.
机译:无线传感器网络(WSN)技术正越来越多地用于关键基础架构(CI)中的数据收集。本文提出了一种入侵检测系统(IDS),它能够保护CI免受针对其基于WSN的部件的攻击。通过提供准确,及时的恶意活动检测,所提议的IDS解决方案最终会在保护方面取得显着改善,因为有机会执行适当的补救/重新配置操作,从而应对攻击并/或允许系统对其进行容忍。 。所提出的解决方案具有利用隐马尔可夫模型的高精度作为检测恶意活动的有效手段的重要优势。我们提出基本思想,讨论主要的实现问题,并针对污水坑攻击(这是对WSN的最严重的攻击之一)进行初步的实验性活动。

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