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Intelligent detection of black hole attacks for secure communication in autonomous and connected vehicles
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Hassan, Zohaib, Mehmood, Amjad, Maple, Carsten, Altaf Khan, Muhammad and Aldegheishem, Abdulaziz (2020) Intelligent detection of black hole attacks for secure communication in autonomous and connected vehicles. IEEE Access, 8 . pp. 199618-199628. doi:10.1109/ACCESS.2020.3034327 ISSN 2169-3536.
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WRAP-Intelligent-detection-black-hole-attacks-autonomous-connected-vehicles-Maple-2020.pdf - Accepted Version - Requires a PDF viewer. Download (2325Kb) | Preview |
Official URL: https://doi.org/10.1109/ACCESS.2020.3034327
Abstract
Detection of Black Hole attacks is one of the most challenging and critical routing security issues in vehicular ad hoc networks (VANETs) and autonomous and connected vehicles (ACVs). Malicious vehicles or nodes may exist in the cyber-physical path on which the data and control packets have to be routed converting a secure and reliable route into a compromised one. However, instead of passing packets to a neighbouring node, malicious nodes bypass them and drop any data packets that could contain emergency alarms. We introduce an intelligent black hole attack detection scheme (IDBA) tailored to ACV. We consider four key parameters in the design of the scheme, namely, Hop Count, Destination Sequence Number, Packet Delivery Ratio (PDR), and End-to-End delay (E2E). We tested the performance of our IDBA against AODV with Black Hole (BAODV), Intrusion Detection System (IdsAODV), and EAODV algorithms. Extensive simulation results show that our IDBA outperforms existing approaches in terms of PDR, E2E, Routing Overhead, Packet Loss Rate, and Throughput.
Item Type: | Journal Article | |||||||||||||||
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Subjects: | Q Science > QB Astronomy T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | |||||||||||||||
Library of Congress Subject Headings (LCSH): | Black holes (Astronomy), Signal processing, Wireless sensor networks -- Security measures, Automated vehicles, Intelligent transportation systems | |||||||||||||||
Journal or Publication Title: | IEEE Access | |||||||||||||||
Publisher: | IEEE | |||||||||||||||
ISSN: | 2169-3536 | |||||||||||||||
Official Date: | 28 October 2020 | |||||||||||||||
Dates: |
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Volume: | 8 | |||||||||||||||
Page Range: | pp. 199618-199628 | |||||||||||||||
DOI: | 10.1109/ACCESS.2020.3034327 | |||||||||||||||
Status: | Peer Reviewed | |||||||||||||||
Publication Status: | Published | |||||||||||||||
Reuse Statement (publisher, data, author rights): | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||||||||
Date of first compliant deposit: | 30 October 2020 | |||||||||||||||
Date of first compliant Open Access: | 4 November 2020 | |||||||||||||||
RIOXX Funder/Project Grant: |
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