Publication Date

Spring 5-20-2019

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Mark Stamp

Second Advisor

Thomas Austin

Third Advisor

Fabio Di Troia

Abstract

In this paper, we consider intrusion detection systems (IDS) in the context of a controller area network (CAN), which is also known as the CAN bus. We provide a discussion of various IDS topics, including masquerade detection, and we include a selective survey of previous research involving IDS in a CAN network. We also discuss background topics and relevant practical issues, such as data collection on the CAN bus. Finally, we present experimental results where we have applied a variety of machine learning techniques to CAN data. We use both actual and simulated data in order to detect the status of a vehicle from its network packets as well as detect masquerade behavior on a vehicle network.

Available for download on Wednesday, May 20, 2020

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