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 journalArticlepeer-review

15 Citations (Scopus)
13 Downloads (Pure)


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 languageEnglish
Article number9123344
Pages (from-to)114733-114740
Number of pages8
JournalIEEE Access
Publication statusPublished - 23 Jun 2020
Externally publishedYes

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/


  • Data integrity
  • intelligent transport systems
  • vehicular network

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)


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