Wormhole Detection Based on Z-Score And Neighbor Table Comparison

TL;DR

This paper introduces a novel, cost-effective statistical method using Z-Score and neighbor table comparison to detect wormhole attacks in disaster rescue networks without relying on auxiliary equipment.

Contribution

It proposes a new pure data statistical analysis approach for wormhole detection that is practical and economical for disaster relief scenarios.

Findings

Effective detection of wormholes demonstrated through simulations

Method does not require GPS or timers, reducing costs

Suitable for resource-constrained disaster rescue networks

Abstract

Wormhole attacks can cause serious disruptions to the network topology in disaster rescue opportunity networks. By establishing false Wormhole(WH) links, malicious nodes can mislead legitimate paths in the network, further causing serious consequences such as traffic analysis attacks (i.e., by eavesdropping and monitoring exchanged traffic), denial of service (DoS) or selective packet loss attacks. This paper uses rescue equipment (vehicle-mounted base stations, rescue control centers, etc.) as an effective third-party auditor (TPA), and combines the commonly used Z-Score (Standard Score) data processing method to propose a new detection method based on pure mathematical statistics for detecting wormhole attacks. Finally, we perform a large number of simulations to evaluate the proposed method. Since our proposed strategy does not require auxiliary equipment such as GPS positioning and timers, as a pure data statistical analysis method, it is obviously more economically valuable, feasible, and practical than other strategies in disaster relief.