A Malicious Anchor Detection Algorithm Based on Isolation Forest and Sequential Probability Ratio Testing (SPRT)

Abstract

Many applications ask for information of nodes in wireless sensor networks (WSNs), among which the node location is an important type of information. In WSNs, localization of target node is often obtained with aid of anchors with providing distance-related information in many algorithms. However some anchors may be attacked in real environments. In order to guarantee the accuracy of localization, it is necessary to identify the malicious anchors under attack. In this paper, we propose a localization detection algorithm with malicious anchors existing in WSNs. The algorithm firstly utilizes Isolation Forest to confirm the reference anchors. After obtaining the initial position estimate of the target nodes, we establish a detection model using the consistency of the measuring distance and the Euclidean distance to the initial position estimate. Finally sequential probability ratio testing (SPRT) is carried out on the remained anchors. The simulation results demonstrate the proposed algorithm can efficiently identify the malicious anchors and outperforms other existing algorithms.

Supported by the National Natural Science Foundation of China under Grant 61572534 and Grant 61873290, by the Special Project of Promoting Economic Development in Guangdong Province under Grant GDME-2018D004, and by the Opening Project of Guangdong Province Key Laboratory of Information Security Technology under Grant 2017B030314131.