Autonomous Vehicles, Volume 1

14Applying Nature-Inspired Algorithms for Threat Modeling in Autonomous Vehicles

Manas Kumar Yogi*, Siva Satya Prasad Pennada, Sreeja Devisetti and Sri Siva Lakshmana Reddy Dwarampudi

Department of Computer Science Engineering, Pragati Engineering College (Autonomous), Surampalem, A.P., India

Abstract

This paper focuses on the security properties of autonomous vehicles and the inherent threat posed by the limitations of design principles applied as part of traditional smart vehicle design. Our paper sheds light on the threat models and adversary models where knowledge of the attacker plays an important part in analyzing their attack patterns and how the attacks develop over time. For the most part, nature-inspired algorithms consider optimization problems as a black box. Therefore, it isn’t important to compute subordinates of the inquiry space. This reality makes nature-inspired algorithms profoundly adaptable with regard to taking care of different sorts of problems. Our paper applies nature-inspired algorithms to optimize the threat analysis model and this helps to develop measures to mitigate them. The nature-inspired algorithms have a good convergence rate to find an optimal solution so this model can be applied to develop a threat model suitable for autonomous vehicles. Attacker-based threat models are the strongest class of threat model, so we introduce the nature-inspired algorithms in this aspect of threat modeling. We develop design guidelines for enhancing the security ...