A Novel Time-to-Response Based Attack Mitigation Technique for Internet of Things-Integrated Wireless Sensor Networks

Abstract

Various heterogeneous devices, including wireless sensor network (WSN) nodes, constitute the Internet of Things (IoT). WSNs are affected by the resource constraints of the connected devices and face frequent security breaches and data transmission loss through node-level compromises. This study proposes a connected ledger-based authenticated node-detection technique to mitigate compromising and man-in-middle attacks. The proposed method uses blockchain technology to update the response natures of the nodes to the IoT platform. Heterogeneous node operations are validated periodically and randomly through their time-to-response metric. Neighbor-to-neighbor verification relies on periodic blockchain updates, whereas node-to-IoT verification is performed arbitrarily for global validation. The validation is performed using classification learning, to prevent the intervention of malicious neighbors in the time-to-response sequences. Compromises and man-in-middle attacks are detected sequentially and randomly using classification and blockchain updates. For the maximum request variant, the proposed technique improves detection ratio by 11.18% and responses by 12.54% whereas it reduces data loss by 11.17%. The above results are obtained in comparison with the existing MNIM-CT [31], DADF [36], and APTAD [29] methods described in the related works section.