A Security-by-Design Decision-Making Model for Risk Management in Autonomous Vehicles

Autonomous/self-driving vehicles have gained significant attention these days, as one of the intelligent transportation systems. However, those risks related to their physical implementation and security against cyber threats. Therefore, this study proposes a new security-by-design model for estimating uncertainty autonomous measuring risks; thus it assists decision-makers in addressing design attack surfaces. The proposed is developed using neutrosophic sets that efficiently tackle multi-criteria decision-making (MCDM) problems with extensive conflicting criteria alternatives. integrates MCDM, Analytic Hierarchy Process (AHP), Multi-Attributive Border Approximation Area Comparison (MABAC), Preference Ranking Organization Method Enrichment Evaluations II (PROMETHEE II), along single-valued (SVNSs). An illustrative case considering ten self-driving used validate feasibility model. Compared state-of-the-art methods, considered consistent reliable deal represent incomplete risk information sets.