MSc Thesis Proposal Announcement by Smarth Kukreja:"Machine Learning based Approach for Detecting Location Spoofing in Vehicular Communication "

Friday, June 4, 2021 - 13:00 to 14:30

SCHOOL OF COMPUTER SCIENCE 

The School of Computer Science is pleased to present… 

MSc Thesis Proposal by: Smarth Kukreja 

 
Date: Friday June 04th, 2021 
Time:  1:00pm  – 2:30pm 
Passcode: If interested in attending this event, contact the Graduate Secretary at csgradinfo@uwindsor.ca

Abstract:  

Vehicular Ad hoc Network (VANET) is an evolving subset of MANET. It’s deployed on the roads, where vehicles act as mobile nodes. Active security and Intelligent Transportation System (ITS) are integral applications of VANET, which require stable and uninterrupted vehicle-to-vehicle communication technology. VANET, is a type of wireless network, due to which it is quite prone to security attacks. Extremely dynamic connections, sensitive data sharing and time-sensitivity of this network make it a vulnerable to security attacks. The messages shared between the vehicles are the basic safety message (BSM), these messages are broadcasted by each vehicle in the network to report its status to the other vehicles and Road Side Unit (RSU).  One common attack is to use position falsification to hamper the roadside safety, leading to road accidents and congestion. Identifying malicious nodes involved in such attacks is crucial to ensure safety in the network. The proposed research presents a neural network based approach for detecting position falsification attacks in VANET.   
 
The proposed Deep Learning-based detection of attackers is done using the dataset called Vehicular Reference Misbehavior Dataset (VeReMi). VeReMi dataset provides five classes of attackers, each broadcasting fabricated coordinates concerning the type. This MLP-based model uses resampled single BSM and two consecutive BSM to detect these attacks.  
 
 Keywords:  Deep Learning, Multi-Level Perceptron (MLP), VeReMi dataset, VANET, BSM, RSU, Position Falsification  
 

MSc Thesis Committee:  

Internal Reader: Dr. Kalyani Selvarajah    
External Reader: Dr. Animesh Sarker        
Advisor:  Dr. Arunita Jaekel 
 

MSc Thesis Proposal Announcement   Vector Institute in Artificial Intelligence artificial intelligence approved topic logo

 

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