ODPV: An Efficient Protocol to Mitigate Data Integrity Attacks in Intelligent Transport Systems

Muhammad Awais  Javed; Muhammad Zubair Khan; Usman Zafar; Muhammad Faisal Siddiqui; Rabiah Badar; Byung Moo Lee; Farhan Ahmad

doi:10.1109/ACCESS.2020.3004444

ODPV: An Efficient Protocol to Mitigate Data Integrity Attacks in Intelligent Transport Systems

Muhammad Awais Javed, Muhammad Zubair Khan, Usman Zafar, Muhammad Faisal Siddiqui, Rabiah Badar, Byung Moo Lee, Farhan Ahmad

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

62 Downloads (Pure)

Abstract

Intelligent Transport Systems (ITS) require accurate information to be shared among vehicles and infrastructure nodes for applications including accident information or pre-crash warnings, to name a few. Due to its sensitive nature, ITS applications are vulnerable against data integrity attacks where nodes transmit false information that results in wrong decision making by the applications. A characteristic of such attacks is that the false transmitted information is significantly different than the actual information. In this paper, we propose an Outlier Detection, Prioritization and Verification (ODPV) protocol that efficiently isolates false data and improves traffic management decisions. ODPV uses the isolation forest algorithm to detect outliers, fuzzy logic to prioritize outliers and C-V2X communications to verify the outliers. Extensive simulation results verify the effectiveness of the proposed protocol to isolate the outliers.

Original language	English
Article number	9123344
Pages (from-to)	114733-114740
Number of pages	8
Journal	IEEE Access
Volume	8
DOIs	https://doi.org/10.1109/ACCESS.2020.3004444
Publication status	Published - 23 Jun 2020
Externally published	Yes

Bibliographical note

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

Keywords

Data integrity
intelligent transport systems
vehicular network

ASJC Scopus subject areas

General Computer Science
General Materials Science
General Engineering

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10.1109/ACCESS.2020.3004444Licence: CC BY

PublishedFinal published version, 1.04 MBLicence: CC BY

Cite this

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title = "ODPV: An Efficient Protocol to Mitigate Data Integrity Attacks in Intelligent Transport Systems",

abstract = "Intelligent Transport Systems (ITS) require accurate information to be shared among vehicles and infrastructure nodes for applications including accident information or pre-crash warnings, to name a few. Due to its sensitive nature, ITS applications are vulnerable against data integrity attacks where nodes transmit false information that results in wrong decision making by the applications. A characteristic of such attacks is that the false transmitted information is significantly different than the actual information. In this paper, we propose an Outlier Detection, Prioritization and Verification (ODPV) protocol that efficiently isolates false data and improves traffic management decisions. ODPV uses the isolation forest algorithm to detect outliers, fuzzy logic to prioritize outliers and C-V2X communications to verify the outliers. Extensive simulation results verify the effectiveness of the proposed protocol to isolate the outliers.",

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doi = "10.1109/ACCESS.2020.3004444",

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AU - Javed, Muhammad Awais

AU - Khan, Muhammad Zubair

AU - Zafar, Usman

AU - Siddiqui, Muhammad Faisal

AU - Badar, Rabiah

AU - Lee, Byung Moo

AU - Ahmad, Farhan

N1 - This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

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Y1 - 2020/6/23

N2 - Intelligent Transport Systems (ITS) require accurate information to be shared among vehicles and infrastructure nodes for applications including accident information or pre-crash warnings, to name a few. Due to its sensitive nature, ITS applications are vulnerable against data integrity attacks where nodes transmit false information that results in wrong decision making by the applications. A characteristic of such attacks is that the false transmitted information is significantly different than the actual information. In this paper, we propose an Outlier Detection, Prioritization and Verification (ODPV) protocol that efficiently isolates false data and improves traffic management decisions. ODPV uses the isolation forest algorithm to detect outliers, fuzzy logic to prioritize outliers and C-V2X communications to verify the outliers. Extensive simulation results verify the effectiveness of the proposed protocol to isolate the outliers.

AB - Intelligent Transport Systems (ITS) require accurate information to be shared among vehicles and infrastructure nodes for applications including accident information or pre-crash warnings, to name a few. Due to its sensitive nature, ITS applications are vulnerable against data integrity attacks where nodes transmit false information that results in wrong decision making by the applications. A characteristic of such attacks is that the false transmitted information is significantly different than the actual information. In this paper, we propose an Outlier Detection, Prioritization and Verification (ODPV) protocol that efficiently isolates false data and improves traffic management decisions. ODPV uses the isolation forest algorithm to detect outliers, fuzzy logic to prioritize outliers and C-V2X communications to verify the outliers. Extensive simulation results verify the effectiveness of the proposed protocol to isolate the outliers.

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KW - vehicular network

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ODPV: An Efficient Protocol to Mitigate Data Integrity Attacks in Intelligent Transport Systems

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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