Araştırma Makalesi

A better way to detect sybil attacks in vehiuclar ad hoc networks

Cilt: 16 Sayı: 1 26 Mart 2025
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A better way to detect sybil attacks in vehiuclar ad hoc networks

Abstract

Sybil attacks, enabled by the anonymous nature of peer-to-peer broadcast communication in vehicular private networks (VANETs), pose a serious security threat. These attacks can significantly disrupt traffic flow, reduce efficiency, and potentially endanger traffic safety. Detecting Sybil attacks in VANETs is particularly challenging due to the dynamic network topology, real-time constraints, and decentralized nature of these networks. This paper proposes a novel Sybil attack detection method for VANETs, leveraging deep learning analysis of received signal strength indicator (RSSI) time series. The proposed system is designed to deliver effective results, even in brief interactions. Experimental results demonstrate the efficacy of our LSTM-based and CNN-based approaches, achieving 93.45% and 94.28% sensitivity in detecting attack messages, respectively.

Keywords

Kaynakça

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  2. [2] M. T. Garip, P. H. Kim, P. Reiher and M. Gerla, "INTERLOC: An interference-aware RSSI-based localization and sybil attack detection mechanism for vehicular ad hoc networks," 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA, 2017, pp. 1-6, doi: 10.1109/CCNC.2017.8013424.
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  4. [4] Y. Yao, B. Xiao, G. Yang, Y. Hu, L. Wang and X. Zhou, "Power Control Identification: A Novel Sybil Attack Detection Scheme in VANETs Using RSSI," in IEEE Journal on Selected Areas in Communications, vol. 37, no. 11, pp. 2588-2602, Nov. 2019, doi: 10.1109/JSAC.2019.2933888.
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Ayrıntılar

Birincil Dil

İngilizce

Konular

Derin Öğrenme , Makine Öğrenme (Diğer)

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

26 Mart 2025

Yayımlanma Tarihi

26 Mart 2025

Gönderilme Tarihi

3 Kasım 2024

Kabul Tarihi

9 Ocak 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 16 Sayı: 1

Kaynak Göster

IEEE
[1]Z. C. Taysi, “A better way to detect sybil attacks in vehiuclar ad hoc networks”, DÜMF MD, c. 16, sy 1, ss. 81–87, Mar. 2025, doi: 10.24012/dumf.1578650.
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