TY - JOUR
T1 - ODPV
T2 - An Efficient Protocol to Mitigate Data Integrity Attacks in Intelligent Transport Systems
AU - Javed, Muhammad Awais
AU - Khan, Mohammad Zubair
AU - Zafar, Usman
AU - Siddiqui, Muhammad Faisal
AU - Badar, Rabiah
AU - Lee, Byung Moo
AU - Ahmad, Farhan
N1 - Funding Information:
Corresponding authors: Muhammad Awais Javed ([email protected]), Mohammad Zubair Khan ([email protected]), and Byung Moo Lee ([email protected]) 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.
Publisher Copyright:
© 2013 IEEE.
PY - 2020/7/1
Y1 - 2020/7/1
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.
KW - Data integrity
KW - intelligent transport systems
KW - vehicular network
UR - http://www.scopus.com/inward/record.url?scp=85087797435&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2020.3004444
DO - 10.1109/ACCESS.2020.3004444
M3 - Article
AN - SCOPUS:85087797435
VL - 8
SP - 114733
EP - 114740
JO - IEEE Access
JF - IEEE Access
SN - 2169-3536
M1 - 9123344
ER -
