Received June 11, 2020, accepted June 20, 2020, date of publication June 23, 2020, date of current version July 1, 2020. Digital Object Identifier 10.1109/ACCESS.2020.3004444 ODPV: An Efficient Protocol to Mitigate Data Integrity Attacks in Intelligent Transport Systems MUHAMMAD AWAIS JAVED 1 , (Senior Member, IEEE), MOHAMMAD ZUBAIR KHAN 2 , USMAN ZAFAR 1 , MUHAMMAD FAISAL SIDDIQUI 1 , RABIAH BADAR 1 , BYUNG MOO LEE 3 , (Member, IEEE), AND FARHAN AHMAD 4 , (Member, IEEE) 1 Department of Electrical and Computer Engineering, COMSATS University Islamabad (CUI), Islamabad 45550, Pakistan 2 Department of Computer Science, College of Computer Science and Engineering, Taibah University, Madinah 41477, Saudi Arabia 3 School of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, South Korea 4 Cyber Security Research Group, College of Engineering and Technology, University of Derby, Derby DE22 1GB, U.K. Corresponding authors: Muhammad Awais Javed (awais.javed@comsats.edu.pk), Mohammad Zubair Khan (mkhanb@taibahu.edu.sa), and Byung Moo Lee (blee@sejong.ac.kr) This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Korea Government Ministry of Science and ICT (MSIT) under Grant NRF-2020R1F1A1048470 and Grant NRF-2019R1A4A1023746. 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. INDEX TERMS Data integrity, intelligent transport systems, vehicular network. I. INTRODUCTION As the cities are expanded with the growing population, people frequently travel long distances for work and other purposes. Intelligent Transportation Systems (ITS) are thus a major need of the present to improve traffic manage- ment and reduce traveling times [1]–[3]. Future smart cities will effectively solve traffic issues such as accidents, timely emergency notification issuance, and congestion on the road [4]–[6]. Wireless connectivity between vehicles provides a poten- tial solution to major transportation problems [7]–[9]. Wireless-enabled automobiles along with the infrastructure components on the road are linked with the traffic man- agement centers that use intelligent data analysis tools to efficiently manage city traffic and improve traffic flow. The transportation system is progressively moving toward elec- tric, autonomous and intelligent vehicles [10]. The associate editor coordinating the review of this manuscript and approving it for publication was Huan Zhou . The major components of future ITS include the On-board Units (OBUs) that are devices fitted at the vehicles to com- municate to other OBUs or infrastructure units [11]. Another important component of ITS is the Road Side Units (RSUs) that are wireless devices installed at various places on the road. RSUs can transmit and receive data to/from the OBUs [12], [13]. RSUs provide OBUs with information such as traffic services (traffic congestion measurement, accident notification, and road conditions), infotainment and adver- tisements. The last component of ITS is the Traffic Command Center (TCC) which is connected to all RSUs and manages city-wide data. Although the wireless connectivity provided by the ITS improves safety and traffic management, security attacks could negatively impact the performance of various appli- cations [14]. Thus, the privacy and security of data shared among the different components of ITS is an important technical task [13], [15]. Malicious nodes could cause great security risk as most ITS applications involve human safety. So, it is important to ensure integrity, authenticity, trust, VOLUME 8, 2020 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ 114733