Ajoneuvoalustojen tietoturva, AaTi (AaTi)
Main funder
Funder's project number: 1143/31/2016
Funds granted by main funder (€)
- 355 000,00
Funding program
Project timetable
Project start date: 01/07/2016
Project end date: 30/09/2018
Summary
Concerning the Intelligent Transport System (ITS), many research projects are already underway to develop a variety of communication solutions between vehicles, roadside stations and services. Cybersecurity is central from the point of the usability of the services. Primarily the car safety should be taken care.
The Controller Area Network (CAN) is an automation bus that was originally designed for real-time data transfer of distributed control systems to cars. Later the CAN bus was developed as a universal automation system for many automation solutions. One of its characteristics is that bus traffic is not supervised in any way due to the lack of timing of control. In other words, its control units do not have mechanisms for detecting counterfeit message packets.
AaTi study highlights different approaches and their usability to reveal the car's CAN bus malfunctions. The study complements earlier studies on the safety of vehicles in the CAN bus. Based on the test results, practical methods can be evaluated to detect changes in CAN bus traffic, such as targeted cyber-attacks.
Initially, at the AaTi study attempted to identify the message content of the bus and to detect interferences via the neuro network solution. However, the problem with the neural network was the computational performance required and the lack of prediction accuracy. After that the study was focused on experiments that based on the arrival times of control messages, i.e., their timing-based disturbance detection. For this sense the research did concentrate to kernel density estimation, to one-class support vector machine solution, to absolute deviation method and to categorization. Due to methodological challenges, at the end of the study, a method of detecting disturbances based on statistical processing of message traffic was developed.
Key words: Cybersecurity, car, CAN bus, disturbance detection
The Controller Area Network (CAN) is an automation bus that was originally designed for real-time data transfer of distributed control systems to cars. Later the CAN bus was developed as a universal automation system for many automation solutions. One of its characteristics is that bus traffic is not supervised in any way due to the lack of timing of control. In other words, its control units do not have mechanisms for detecting counterfeit message packets.
AaTi study highlights different approaches and their usability to reveal the car's CAN bus malfunctions. The study complements earlier studies on the safety of vehicles in the CAN bus. Based on the test results, practical methods can be evaluated to detect changes in CAN bus traffic, such as targeted cyber-attacks.
Initially, at the AaTi study attempted to identify the message content of the bus and to detect interferences via the neuro network solution. However, the problem with the neural network was the computational performance required and the lack of prediction accuracy. After that the study was focused on experiments that based on the arrival times of control messages, i.e., their timing-based disturbance detection. For this sense the research did concentrate to kernel density estimation, to one-class support vector machine solution, to absolute deviation method and to categorization. Due to methodological challenges, at the end of the study, a method of detecting disturbances based on statistical processing of message traffic was developed.
Key words: Cybersecurity, car, CAN bus, disturbance detection
