PhD Seminar Presentation Announcement by Muhammad Anwar Shahid:"Detection of Bogus Information Attack in Connected Vehicles using Hybrid Approach "

Tuesday, August 30, 2022 - 11:00 to 12:00

SCHOOL OF COMPUTER SCIENCE 


The School of Computer Science at the University of Windsor is pleased to present … 

PhD. Seminar by: Muhammad Anwar Shahid 

 
Date: Tuesday August 30, 2022 
Time: 11:00AM – 12:00PM 
Passcode: If interested in attending this event, contact the Graduate Secretary at csgradinfo@uwindsor.ca with sufficient notice before the event to obtain the passcode.
 

Abstract: 

Vehicles on the roads play an important role in our daily lives. Increasing number of vehicles on the roads is producing more problems for traffic management authorities, drivers, and other people. Some of these problems include collisions, congestion, air pollution and fuel consumption. Connected and autonomous vehicles (CAVs) will form the backbone of future next-generation intelligent transportation systems (ITS) providing travel comfort, road safety, and several value-added services. Connected vehicles share sensitive information through Vehicle to Everything (V2X) communication. Road-Side Unit (RSU) and On-Board Unit (OBU) play an important role to share such information through Basic Safety Message (BSM). Security is one of the biggest challenges in Vehicular Adhoc Network (VANET) because vehicular communication is vulnerable to various attacks. In VANET, security must ensure that exchanged messages are not altered or created by malicious attackers. Denial of Service (DoS), Replay, Position Falsification and Sybil attacks are some of the known attacks in VANET. Timely detection of these attacks can play a vital role in securing vehicular communication.  
In this work, we proposed a robust framework to detect position falsification attack using hybrid approach.  In this approach, we use a combination of plausible data and machine learning algorithm to detect bogus information in BSMs in a timely manner. We used Vehicular Reference Misbehavior (VeReMi), a well-known simulated dataset available publicly, to perform our experiment. Our proposed hybrid approach shows an improvement to detect position falsification attack in terms of prediction rate. 
 
Keywords: VANET, ITS, DSRC, C-V2X, Basic Safety Message, Security Attacks, Plausibility, Machine Learning, Intrusion Detection System (IDS) 


PhD Doctoral Committee:  

Internal Reader: Dr. Boubakeur Boufama 
Internal Reader: Dr. Imran Ahmad 
External Reader: Dr. Ning Zhang 
Advisor(s): Dr. Arunita Jaekel 


PhD Seminar Announcement 

 
5113 Lambton Tower 401 Sunset Ave. Windsor ON, N9B 3P4 (519) 253-3000 Ext. 3716 csgradinfo@uwindsor.ca