Cyber-Physical Systems (CPSs) have become an essential ingredient of today’s digital world. They operate in a deeply embedded manner inside infrastructures for transportation, power grids, smart buildings, and several other application domains. The implementation of most CPSs involves components like sensors, real-time computing platforms, actuators, networking primitives, etc. at the hardware level. Such an infrastructure needs to run real-time compute and communication tasks which implement critical functionalities. This often opens up different possible attack surfaces inside the system. Attackers exploit such vulnerabilities to launch network level and physical level attacks on safety-critical CPSs. This has led to the rethinking of basic CPS design methods, migrating from a safety-aware and resource-level budget-aware approach to making security a first-class design constraint. In this chapter, we elaborate on such security-aware CPS design techniques, specifically for the automotive domain.
Resource Aware Synthesis of Automotive Security Primitives
Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems ; Kapitel : 6 ; 189-224
2023-03-27
36 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Resource-aware automotive control systems design
TIBKAT | 2017
|Resource-Aware Automotive Control Systems Design
TIBKAT | 2017
|Uncertainty-Aware Imitation Learning using Kernelized Movement Primitives
BASE | 2019
|Uncertainty-Aware Imitation Learning using Kernelized Movement Primitives
BASE | 2019
|Uncertainty-Aware Imitation Learning using Kernelized Movement Primitives
BASE | 2019
|