Work

External Sinkhole Attack Detection in Large-Scale WSNs Using Metaheuristic Feature Selection

Year: 2026

Type: preprint

Abstract: Sinkhole attacks in large-scale wireless sensor networks (WSNs) pose a serious threat to network functionality. This paper presents a metaheuristic feature selection for sinkhole attack detection using the bee swarm optimization (BSO) algorithm. In an external sinkhole attack simulation with 2000 nodes deployed over a 3000 $\times$ 3000 m$^2$ field, the proposed method achieves a detection accuracy of 0.997 while reducing the 16-feature set to eight features.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2608.15274

Authors: Han, Seungwoo, Kitagata, Sawako, Chanpornpakdi, Ingon, Tanaka, Toshihisa, Nam, Su Man

Institutions: Tokyo University of Agriculture and Technology, Cheongju University

Language: English

Topic: Security in Wireless Sensor Networks

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7203695552

Cites:

Cited by:

Related to: 10