| Title | Intrusion Detection For Controller Area Network Using Support Vector Machines |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Tanksale, Vinayak |
| Conference Name | 2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW) |
| Keywords | automobile communications, automobiles, CAN protocol, communication standard, computer network security, controller area network, controller area network security, controller area networks, Cyber-physical systems, delays, ECU, feature extraction, feature vector selection, Internet of Things, Intrusion detection, light-weight nature, machine learning, parameter selection, process secure communication, Protocols, pubcrawl, Resiliency, security countermeasures, support vector machine, support vector machine based intrusion detection system, Support vector machines |
| Abstract | Controller Area Network is the most widely adopted communication standard in automobiles. The CAN protocol is robust and is designed to minimize overhead. The light-weight nature of this protocol implies that it can't efficiently process secure communication. With the exponential increase in automobile communications, there is an urgent need for efficient and effective security countermeasures. We propose a support vector machine based intrusion detection system that is able to detect anomalous behavior with high accuracy. We outline a process for parameter selection and feature vector selection. We identify strengths and weaknesses of our system and propose to extend our work for time-series based data. |
| DOI | 10.1109/MASSW.2019.00032 |
| Citation Key | tanksale_intrusion_2019 |
Intrusion Detection For Controller Area Network Using Support Vector Machines