Sequestration of Malevolent Anchor Nodes in Wireless Sensor Networks using Mahalanobis Distance

TL;DR

This paper presents a method combining trilateration and Mahalanobis distance to accurately detect and localize malicious anchor nodes in wireless sensor networks, reducing localization errors.

Contribution

It introduces a novel approach integrating Mahalanobis distance with trilateration for improved detection of cheating anchor nodes in WSNs.

Findings

Significant reduction in localization error.

Effective detection of malicious anchor nodes.

Validated through ns3 simulations.

Abstract

Discovering the malicious or vulnerable anchor node is an essential problem in wireless sensor networks (WSNs). In wireless sensor networks, anchor nodes are the nodes that know its current location. Neighbouring nodes or non-anchor nodes calculate its location coordinate (or location reference) with the help of anchor nodes. Ingenuous localization is not possible in the presence of a cheating anchor node or a cheating node. Nowadays, its a challenging task to identify the cheating anchor node or cheating node in a network. Even after finding out the location of the cheating anchor node, there is no assurance, that the identified node is legitimate or not. This paper aims to localize the cheating anchor nodes using trilateration algorithm and later associate it with Mahalanobis distance to obtain maximum accuracy in detecting malicious or cheating anchor nodes during localization. We were able to attain a considerable reduction in the error achieved during localization. For implementation purpose, we simulated our scheme using ns3 network simulator.