Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems

Akshat Gaurav; B. B. Gupta; Kwok Tai Chui

doi:10.1007/978-981-16-8664-1_16

Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems

Akshat Gaurav, B. B. Gupta, Kwok Tai Chui

Electronic Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

Vehicular ad hoc networks (VANETs) are a critical component of intelligent transportation systems (ITS). Because VANET allows the transmission of critical and life-saving information between vehicle nodes, any effort to compromise the network should be recognized immediately, if at all feasible. The distributed denial-of-service (DDoS) assault is one kind of cyber-attack that affects VANET systems’ availability. As a consequence of the DDoS assault, vehicle nodes are unable to transmit vital information. In this context, this experiment proposed edge computing-based DDoS detection techniques. The proposed technique uses packet entropy to distinguish DDoS attack traffic from normal communication. To determine the entropy values, we performed an in-depth study of five different machine learning methods.

Original language	English
Title of host publication	Cyber Security, Privacy and Networking - Proceedings of ICSPN 2021
Editors	Dharma P. Agrawal, Nadia Nedjah, B. B. Gupta, Gregorio Martinez Perez
Pages	175-184
Number of pages	10
DOIs	https://doi.org/10.1007/978-981-16-8664-1_16
Publication status	Published - 2022
Event	International Conference on Cyber Security, Privacy and Networking, ICSPN 2021 - Virtual, Online Duration: 17 Sept 2021 → 19 Sept 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	370
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Cyber Security, Privacy and Networking, ICSPN 2021
City	Virtual, Online
Period	17/09/21 → 19/09/21

Keywords

Entropy
Machine learning
Side channel attacks
VANET

Access to Document

10.1007/978-981-16-8664-1_16

Cite this

Gaurav, A., Gupta, B. B., & Chui, K. T. (2022). Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems. In D. P. Agrawal, N. Nedjah, B. B. Gupta, & G. Martinez Perez (Eds.), Cyber Security, Privacy and Networking - Proceedings of ICSPN 2021 (pp. 175-184). (Lecture Notes in Networks and Systems; Vol. 370). https://doi.org/10.1007/978-981-16-8664-1_16

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title = "Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems",

abstract = "Vehicular ad hoc networks (VANETs) are a critical component of intelligent transportation systems (ITS). Because VANET allows the transmission of critical and life-saving information between vehicle nodes, any effort to compromise the network should be recognized immediately, if at all feasible. The distributed denial-of-service (DDoS) assault is one kind of cyber-attack that affects VANET systems{\textquoteright} availability. As a consequence of the DDoS assault, vehicle nodes are unable to transmit vital information. In this context, this experiment proposed edge computing-based DDoS detection techniques. The proposed technique uses packet entropy to distinguish DDoS attack traffic from normal communication. To determine the entropy values, we performed an in-depth study of five different machine learning methods.",

keywords = "Entropy, Machine learning, Side channel attacks, VANET",

author = "Akshat Gaurav and Gupta, {B. B.} and Chui, {Kwok Tai}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Cyber Security, Privacy and Networking, ICSPN 2021 ; Conference date: 17-09-2021 Through 19-09-2021",

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Gaurav, A, Gupta, BB & Chui, KT 2022, Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems. in DP Agrawal, N Nedjah, BB Gupta & G Martinez Perez (eds), Cyber Security, Privacy and Networking - Proceedings of ICSPN 2021. Lecture Notes in Networks and Systems, vol. 370, pp. 175-184, International Conference on Cyber Security, Privacy and Networking, ICSPN 2021, Virtual, Online, 17/09/21. https://doi.org/10.1007/978-981-16-8664-1_16

Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems. / Gaurav, Akshat; Gupta, B. B.; Chui, Kwok Tai.
Cyber Security, Privacy and Networking - Proceedings of ICSPN 2021. ed. / Dharma P. Agrawal; Nadia Nedjah; B. B. Gupta; Gregorio Martinez Perez. 2022. p. 175-184 (Lecture Notes in Networks and Systems; Vol. 370).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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