Trustworthiness in Mobile Cyber Physical Systems
Kang, Kyungtae (editor)
Son, Junggab (editor)
Suh, Hyo-Joong (editor)
Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS.
KeywordsAUTOSAR; DAG; runnable scheduling; control-scheduling codesign; lagrange multiplier; Mobile Cyber-Physical Systems (MCPS); industry; Mobile Sink Groups (MSG); group mobility; real-time data delivery; Intelligent Transportation System (ITS); deep neural network; Red Light Runner (RLR); dynamic signal control; intersection safety; mixed-criticality; power-aware; real-time scheduling; DVFS; security taxonomies; event-based systems; mobile cyber physical systems; security flaws; searchable encryption; PEKS; forward privacy; trusted execution environment; SGX; data quality; large-scale; high-dimensionality; linear discriminant analysis; random projection; bootstrapping; controller area network bus; authentication; authenticity; resiliency; sustainability; formal verification; model checking; in-vehicle network; model compression; adversarial robustness; weight pruning; adversarial training; distillation; embedded system; secure AI; n/a
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Publication date and placeBasel, Switzerland, 2021
Technology: general issues