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Erschienen in:
2023 | OriginalPaper | Buchkapitel
Modeling and Detection of Denial-of-Sleep Attacks on Autonomous IoT Devices in Wireless Sensor Networks
verfasst von : Vasily Desnitsky
Erschienen in: Security, Trust and Privacy Models, and Architectures in IoT Environments
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Abstract
The chapter encompasses issues of modeling and detection of Denial-of-Sleep attacks in wireless sensor networks. Such attacks are applicable to IoT devices functioning autonomously and switching between two operating modes, namely, the normal and energy-efficient sleep mode, depending on the business rules of the devices. While being generally quite effective, such attacks are quite stealthy and can significantly reduce and even completely deplete a device’s battery life, thereby leading the device to a disabled state. In this work, source data is analyzed, and artificial intelligence methods are applied to detect Denial-of-Sleep attack. The detection model is constructed with the use of particular machine learning methods. The model is validated on real data collected on a testbed with ZigBee wireless modules presenting both normal wireless sensor nodes and attacking one. The detection quality indicators prove the effectiveness and applicability of the proposed ML-based detection techniques in practice.