During this event the CARAMEL project participated in the discussion session dedicated to providing a platform for discussion of opportunities and collaborations for innovation and research in Europe, in which the project’s technical coordinator Peter Hofmann took part in the important panel session “The Good, the Bad and the Trendy of Multi-Partner Research Projects in Europe”. Although the conference was originally scheduled to be held in a face-to-face format, it had to be reorganised at short notice to an online format.
Besides the presentation of CARAMEL project a CARAMEL paper was presented as part of conference’s activities
A Comprehensive Solution for Securing Connected and Autonomous Vehicles
- What makes the project concept unique?
In the CARAMEL project, we strive to implement machine-learning based detection of attacks against the connected and/or autonomous vehicle by analysing sensor data, V2X data, and the status of embedded controllers like the OBU (on-board unit) in real-time using a tamper-proof device that directly integrated into the car – the anti-hacking device (AHD). This architecture and concept are novel and innovative, and CARAMEL is the first project to implement and demonstrate this.
- What project outcomes can be of use to the DATE 2022 community?
Even as CARAMEL implements its concepts and architectures in the automotive space, the key CARAMEL innovations are transferable to other IoT and Embedded applications domains as well, such as factory floors, building automation systems or others. Therefore, the CARAMEL presentation and presence of CARAMEL representatives during the conference would be of value to the DATE 2022 community.
- What inputs (solutions) are expected from the DATE 2022 community?
In the CARAMEL project, several integration options for the anti-hacking device based on different IoT devices have been pursued already. However, for the concept to be commercially viable and cost-effective, the concept of a machine-learning-based intrusion device must be even better integrated into commercial offerings for the Automotive and IoT market. The DATE 2022 community could provide valuable input for that endeavour.
- What new research topics and trends does the project introduce?
CCAM and IoT both will face important security challenges in the future as bad actors discover these new areas for their activities. Since bad actors will use machine learning to subvert machine-learning-based processes and algorithms in the CCAM and IoT world (eg. using Generative Adversarial Networks (GAN)), a trend in the security industry is also to use machine learning to detect and counter these attacks. The CARAMEL project showcases this approach in the Automotive context.
- Fundació Privada i2CAT, Internet i Innovació digital a Catalunya, Spain
- DEUTSCHE TELEKOM SECURITY GMBH, Germany
- ALTRAN DEUTSCHLAND SAS & CO KG, Germany
- EIGHT BELLS LTD, Cyprus
- UBIWHERE LDA, Portugal
- CYBERLENS BV, Netherlands
- GREENFLUX ASSETS BV, Netherlands
- SIDROCO HOLDINGS LIMITED, Cyprus
- 0 INFINITY LIMITED, UK
- UNIVERSITY OF CYPRUS, Cyprus
- University of Patras, Greece
- Idneo Technologies SAU, Spain
- AVL LIST GmbH, Austria
- PANASONIC AUTOMOTIVE SYSTEMS EUROPE GMBH, Germany
- ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE, South Korea
- KOREA AUTOMOTIVE TECHNOLOGY INSTITUTE, South Korea
- MOBIGEN CO LTD, Republic of Korea
- ATOS IT SOLUTIONS AND SERVICES IBERIA SL, Spain