(Note this talk is at 4 pm rather than the usual 3 pm slot)

Modern vehicles comprise multiple networked computers, known as Electronic Control Units (ECUs), to realise a range of functionality and features such as driving and powertrain control, connectivity, sensing and body modules. Such ECUs are interconnected through onboard networks, including typically a data bus known as the Controller Area Network (CAN). Due to a combination of connectivity (over various interfaces) and complexity (of design and features), modern vehicles are also subject to cyber-attacks. They can seriously impact the safety of a vehicle if packets are successfully sent on the vehicle’s internal wired network. Counteracting automotive cybersecurity threats requires the investigations of threat models, countermeasures, detection methods and resolution options. This presents a number of challenges specific to the automotive field. First, it is difficult to conduct experimentation on real systems. Conducting tests on live vehicles is costly and might result in vehicle damage or risks to property and life. It also presents challenges regarding ethics, insurance and legality, and the researchers may not have access to rolling roads or private tracks. Given such challenges, it is understandable why research into automotive cyberattack detection has tended to be done using offline experiments on previously captured data. To facilitate the development and validation of security measures as well as to assure a secure automotive CPS, it is vital to replicate the on-board network and a series of components, along with a connected external environment representing required use cases and driving scenarios in an instrumental and controllable environment. In this talk, we introduce a multi-component testbed representing a flexible and functional in-vehicle architecture for real environment trials to train, test, validate and demonstrate IDS solutions.

Zoom meeting: https://newcastleuniversity.zoom.us/j/81739506151?pwd=RVNMZmxibmVhL1hTODFYWnZwWFpKUT09
Meeting ID: 817 3950 6151
Passcode: 068732

Youtube live streaming: https://youtu.be/B8KrpkUaXTw

Youtube VoD