H2020 Caramel Project

H2020 Caramel Project is rated 3 out of 5 in the category computer & network security. Read and write reviews about H2020 Caramel Project. CARAMEL: Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g., to traffic jams or malicious modifications in sensors’ firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians. CARAMEL’s goal is to proactively address modern vehicle cybersecurity challenges applying advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques and also to continuously seek methods to mitigate associated safety risks. In order to address cybersecurity considerations for the already here autonomous and connected vehicles, well-established methodologies coming from the ICT sector will be adopted, allowing to assess vulnerabilities and potential cyber attack impacts. Although past initiatives and cybersecurity projects related to the automotive industry have reached to security assurance frameworks for networked vehicles, several newly introduced technological dimensions like 5G, autopilots, and smart charging of Electric Vehicles (EVs) introduce cybersecurity gaps, not addressed satisfactorily yet. Considering the entire supply chain of automotive operations, CARAMEL targets to reach to commercial anti-hacking IDS/IPS products for the European automotive cybersecurity and to demonstrate their value through the extensive attack and penetration scenarios. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 833611