AI/ML Solution Against Cybersecurity Issues in Connected and Autonomous Vehicles (CAVs)

• Author(s) / Creator(s)

  • Hansen Zhang

• With the rapid development of Connected and Autonomous Vehicles (CAVs), critical challenges appear as well. Cybersecurity in CAVs is one of the most significant issues in the upcoming decades. This is a capstone project report for the MINT program essentially aims to solve Control Area Network (CAN) cybersecurity issues by gathering valid network message datasets M-CAN Intrusion Dataset (M-CAN) dataset to complete an Artificial Intelligence/Machine Learning (AI/ML) Model that facilitates the Intrusion Detect System (IDS). The outcome helps detect and classify cyberattacks
  through CAN inside of CAVs data communication. And the conclusion is made up of the comparison of the J48 decision tree classification ML algorithm and the Naïve Bayes classification ML algorithm. Both have pros and cons compared with each other.
  This project overall covers several concepts involving Connected and Autonomous
  Vehicles (CAVs), the Internet of Things (IoT), 5G data communication, Controller Area
  Network (CAN) protocol, Cyberattacks, Cybersecurity, and AI/ML.
  The project report is composed of the following 5 sections:

  1. Relative background knowledge was described in the Introduction section to help viewers better comprehend the project topic and understand part of the fundamental mechanism of CAVs related to this project.
  2. The Literature Review section provides an analysis of the current condition and procedure of cybersecurity of CAVs research so far. The purpose is to acknowledge the research progress and establish the context and significance of the study and provide a basis for the next two steps, which are the methodology and results of the project.
  3. The methodology section decomposes the procedure of M-CAN dataset selection, data analysis, dataset preprocessing, model implementation, and model performance analysis procedure.
  4. The discussion part describes the challenges and issues that were met during the project and some opinions related to this project.
  5. A conclusion was made in the last section.

• Date created

  2023-04-01

• Subjects / Keywords

  • Cybersecurity
  • Autonomous Vehicles

• Type of Item

  Research Material

• DOI

  https://doi.org/10.7939/r3-3v1d-fp49

• License

  Attribution-NonCommercial 4.0 International