A Collaborative, Secure and Energy Efficient Intrusion Detection Method for Homogeneous WSN

Mubarak, T. Mohamed; Sattar, Syed Abdul; Rao, Appa; Sajitha, M

doi:10.1007/978-3-642-22720-2_10

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…On the other hand, it has a considerable high detection rate for known attacks [18]. The reliable performance of specification-based detection is at the cost of computation, that is, a set of specification and constraints need to be defined [19][20][21][22][23][24][25][26][27][28]. For example, Le et al [27] proposed a specification-based IDS for attacks targeting routing protocols for low power and lossy networks (RPL).…”

Section: Specification-based Detectionmentioning

confidence: 99%

A Lightweight Intrusion Detection Method Based on Fuzzy Clustering Algorithm for Wireless Sensor Networks

Lei

Tang

et al. 2018

Advances in Fuzzy Systems

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For resource-constrained wireless sensor networks (WSNs), designing a lightweight intrusion detection technology has been a hot and difficult issue. In this paper, we proposed a lightweight intrusion detection method that was able to directly map the network status into sensor monitoring data received by base station, so that base station can sense the abnormal changes in the network. Our method is highlighted by the fusion of fuzzy c-means algorithm, one-class SVM, and sliding window procedure to effectively differentiate network attacks from abnormal data. Finally, the proposed method was tested on the wireless sensor network simulation software EXata and in real applications. The results showed that the intrusion detection method in this paper could effectively identify whether the abnormal data came from a network attack or just a noise. In addition, extra energy consumption can be avoided in all sensor monitoring nodes of the sensor network where our method has been deployed.

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