Descripció del projecte
Context:
The automotive industry is experiencing a major shift towards increasingly connected, autonomous and software-defined vehicles. This evolution has turned the vehicle’s electronic platforms (ECUs, CAN networks, etc.) and their environment (Apps and backends) into critical attack surfaces. A single vulnerability could compromise both the physical security of the vehicle and the privacy of its users.
Objective:
Our goal is to establish an advanced AI-assisted offensive security framework specifically tailored for the complex architecture of automotive electronic systems. This solution will propose intelligent and adaptive agents to conduct in-depth penetration testing, systematically simulating diverse and high-fidelity attack scenarios across the vehicle network. The main goal is the transition of security assessment from a reactive to a proactive and predictive model. By anticipating emerging attack surfaces and quantifying potential risk exposures, the framework will ensure maximum cybersecurity preparedness. Critically, its structure will ensure robust validation of compliance against industry-established benchmarks, in particular the requirements set by UNECE R155.
Through the use of intelligent agents, the framework will:
– Simulate complex attack scenarios.
– Anticipate emerging cybersecurity risks.
– Automated and scale penetration testing activities.
– Evolve from one-off assessments towards a continuous and proactive security approach.
The project will contribute to:
– Fast and proactive customer protection.
– Increase in internal cybersecurity maturity.
– Preparation for regulatory compliance, in particular UNECE R155.
– Preparation for future organizational responsibility for advanced vehicle electronic architectures.
