research-article

Entropy as a new metric for denial of service attack detection in vehicular ad-hoc networks

Authors:

Mohamed Nidhal Mejri,

Jalel Ben-OthmanAuthors Info & Claims

MSWiM '14: Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems

Pages 73 - 79

https://doi.org/10.1145/2641798.2641800

Published: 21 September 2014 Publication History

Abstract

Vehicular Ad hoc Networks (VANETs) aim to enhance driving conditions and provide with drivers and road users a high level of safety. Thus, they are exposed to several kinds of attacks, especially Denial Of Service attacks family (DOS) which affect the availability of services of authentic users. In this paper, we define "Packets entropy" as a new metric to be used for VANETs denial of service attack detection. We propose also a new detection scheme for this effect. Using "Packets entropy", the proposed method is able to detect VANET DOS attacks by the supervision of traffic traces during short monitoring periods. It presents the advantage of rapidity, to be executed by any node of the VANET network and does not require any modification of the 802.11p MAC layer protocol used as a standard for VANETs. Simulations show the high efficiency of the newly defined metric and the related proposed detection method.

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Cited By

Verma ASaha RKumar GConti MKim T(2024)PREVIR: Fortifying Vehicular Networks Against Denial of Service AttacksIEEE Access10.1109/ACCESS.2024.338299212(48301-48320)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3382992
Verma ASaha RKumar GKim T(2021)The Security Perspectives of Vehicular Networks: A Taxonomical Analysis of Attacks and SolutionsApplied Sciences10.3390/app1110468211:10(4682)Online publication date: 20-May-2021
https://doi.org/10.3390/app11104682
Sharshembiev KYoo SElmahdi E(2021)Protocol misbehavior detection framework using machine learning classification in vehicular Ad Hoc networksWireless Networks10.1007/s11276-021-02565-7Online publication date: 16-Feb-2021
https://doi.org/10.1007/s11276-021-02565-7
Show More Cited By

Index Terms

Entropy as a new metric for denial of service attack detection in vehicular ad-hoc networks
1. Networks
  1. Network protocols
  2. Network types
    1. Mobile networks
    2. Wireless access networks

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Published In

cover image ACM Conferences

MSWiM '14: Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems

September 2014

352 pages

ISBN:9781450330305

DOI:10.1145/2641798

General Chairs:
Ravi Prakash
University of Texas at Dallas, USA
,
Azzedine Boukerche
University of Ottawa, Canada
,
Program Chairs:
Cheng Li
Memorial University of Newfoundland, Canada
,
Falko Dressler
University of Paderborn, Germany

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 September 2014

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MSWiM'14

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SIGSIM

MSWiM'14: 17th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

September 21 - 26, 2014

QC, Montreal, Canada

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MSWiM '14 Paper Acceptance Rate 32 of 128 submissions, 25%;

Overall Acceptance Rate 398 of 1,577 submissions, 25%

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Citations

Cited By

Verma ASaha RKumar GConti MKim T(2024)PREVIR: Fortifying Vehicular Networks Against Denial of Service AttacksIEEE Access10.1109/ACCESS.2024.338299212(48301-48320)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3382992
Verma ASaha RKumar GKim T(2021)The Security Perspectives of Vehicular Networks: A Taxonomical Analysis of Attacks and SolutionsApplied Sciences10.3390/app1110468211:10(4682)Online publication date: 20-May-2021
https://doi.org/10.3390/app11104682
Sharshembiev KYoo SElmahdi E(2021)Protocol misbehavior detection framework using machine learning classification in vehicular Ad Hoc networksWireless Networks10.1007/s11276-021-02565-7Online publication date: 16-Feb-2021
https://doi.org/10.1007/s11276-021-02565-7
Gaurav AGupta BCastiglione APsannis KChoi C(2021)A Novel Approach for Fake News Detection in Vehicular Ad-Hoc Network (VANET)Computational Data and Social Networks10.1007/978-3-030-66046-8_32(386-397)Online publication date: 4-Jan-2021
https://doi.org/10.1007/978-3-030-66046-8_32
Jahan FSun WNiyaz QAlam M(2019)Security Modeling of Autonomous SystemsACM Computing Surveys10.1145/333779152:5(1-34)Online publication date: 13-Sep-2019
https://dl.acm.org/doi/10.1145/3337791
Sharshembiev KYoo SElmahdi EKim YJeong G(2019)Fail-Safe Mechanism Using Entropy Based Misbehavior Classification and Detection in Vehicular Ad Hoc Networks2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00042(123-128)Online publication date: Jul-2019
https://doi.org/10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00042
Sharma SKaushik B(2019)A survey on internet of vehicles: Applications, security issues & solutionsVehicular Communications10.1016/j.vehcom.2019.100182(100182)Online publication date: Sep-2019
https://doi.org/10.1016/j.vehcom.2019.100182
He YYu FZhao NYin HBoukerche ANotare MCoutinho R(2017)Deep Reinforcement Learning (DRL)-based Resource Management in Software-Defined and Virtualized Vehicular Ad Hoc NetworksProceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications10.1145/3132340.3132355(47-54)Online publication date: 21-Nov-2017
https://dl.acm.org/doi/10.1145/3132340.3132355
Zhang DYu FWei ZBoukerche ADe Grande RNotare MDarehshoorzadeh A(2016)Software-defined Vehicular Ad Hoc Networks with Trust ManagementProceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications10.1145/2989275.2989285(41-49)Online publication date: 13-Nov-2016
https://dl.acm.org/doi/10.1145/2989275.2989285
Lacroix JEl-Khatib KAkalu RDe Grande RNotare MDarehshoorzadeh A(2016)Vehicular Digital ForensicsProceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications10.1145/2989275.2989282(59-66)Online publication date: 13-Nov-2016
https://dl.acm.org/doi/10.1145/2989275.2989282
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