scholarly journals Security‐ and safety‐critical cyber‐physical systems

2019 ◽  
Vol 32 (2) ◽  
Author(s):  
Atif Mashkoor ◽  
Johannes Sametinger ◽  
Miklós Biro ◽  
Alexander Egyed
Keyword(s):  
Cyber Physical Systems ◽  
Physical Systems ◽  
Safety Critical

Safety-Critical, Dependable, and Fault-Tolerant Cyber-Physical Systems

2018 ◽  
pp. 54-78
Author(s):  
Guru Prasad Bhandari ◽  
Ratneshwer Gupta
Keyword(s):  
Fault Tolerance ◽  
Fault Tolerant ◽  
Cyber Physical Systems ◽  
General Information ◽  
The Internet ◽  
Physical Systems ◽  
Safety Critical ◽  
Computer Based

Cyber-physical systems (CPSs) are co-engineered integrating with physical and computational components networks. Additionally, a CPS is a mechanism controlled or monitored by computer-based algorithms, tightly interacting with the internet and its users. This chapter presents the definitions relating to dependability, safety-critical and fault-tolerance of CPSs. These definitions are supplemented by other definitions like reliability, availability, safety, maintainability, integrity. Threats to dependability and security like faults, errors, failures are also discussed. Taxonomy of different faults and attacks in CPSs are also presented in this chapter. The main objective of this chapter is to give the general information about secure CPS to the learners for the further enhancement in the field of CPSs.

scholarly journals Timing Predictability and Security in Safety-Critical Industrial Cyber-Physical Systems: A Position Paper

2020 ◽  
Vol 10 (9) ◽  
pp. 3125
Author(s):  
Saad Mubeen ◽  
Elena Lisova ◽  
Aneta Vulgarakis Feljan
Keyword(s):  
Embedded Systems ◽  
Cyber Physical Systems ◽  
Position Paper ◽  
Technological Advancement ◽  
Functional Safety ◽  
Physical Systems ◽  
Safety Critical ◽  
Secure Embedded Systems ◽  
Time Critical ◽  
Networking Technology

Cyber Physical Systems (CPSs) are systems that are developed by seamlessly integrating computational algorithms and physical components, and they are a result of the technological advancement in the embedded systems and distributed systems domains, as well as the availability of sophisticated networking technology. Many industrial CPSs are subject to timing predictability, security and functional safety requirements, due to which the developers of these systems are required to verify these requirements during the their development. This position paper starts by exploring the state of the art with respect to developing timing predictable and secure embedded systems. Thereafter, the paper extends the discussion to time-critical and secure CPSs and highlights the key issues that are faced when verifying the timing predictability requirements during the development of these systems. In this context, the paper takes the position to advocate paramount importance of security as a prerequisite for timing predictability, as well as both security and timing predictability as prerequisites for functional safety. Moreover, the paper identifies the gaps in the existing frameworks and techniques for the development of time- and safety-critical CPSs and describes our viewpoint on ensuring timing predictability and security in these systems. Finally, the paper emphasises the opportunities that artificial intelligence can provide in the development of these systems.

scholarly journals Safety Verification Utilizing Model-based Development for Safety Critical Cyber-Physical Systems

2017 ◽  
Vol 25 (0) ◽  
pp. 797-810 ◽  
Author(s):  
Tasuku Ishigooka ◽  
Habib Saissi ◽  
Thorsten Piper ◽  
Stefan Winter ◽  
Neeraj Suri
Keyword(s):  
Cyber Physical Systems ◽  
Safety Verification ◽  
Physical Systems ◽  
Safety Critical ◽  
Model Based

scholarly journals Challenges of Machine Learning Applied to Safety-Critical Cyber-Physical Systems

2020 ◽  
Vol 2 (4) ◽  
pp. 579-602
Author(s):  
Ana Pereira ◽  
Carsten Thomas
Keyword(s):  
Machine Learning ◽  
Autonomous Driving ◽  
Cyber Physical Systems ◽  
Shop Floor ◽  
Safety Engineering ◽  
Safety Hazards ◽  
Physical Systems ◽  
Safety Critical ◽  
Holistic Approaches ◽  
Transportation Vehicle

Machine Learning (ML) is increasingly applied for the control of safety-critical Cyber-Physical Systems (CPS) in application areas that cannot easily be mastered with traditional control approaches, such as autonomous driving. As a consequence, the safety of machine learning became a focus area for research in recent years. Despite very considerable advances in selected areas related to machine learning safety, shortcomings were identified on holistic approaches that take an end-to-end view on the risks associated to the engineering of ML-based control systems and their certification. Applying a classic technique of safety engineering, our paper provides a comprehensive and methodological analysis of the safety hazards that could be introduced along the ML lifecycle, and could compromise the safe operation of ML-based CPS. Identified hazards are illustrated and explained using a real-world application scenario—an autonomous shop-floor transportation vehicle. The comprehensive analysis presented in this paper is intended as a basis for future holistic approaches for safety engineering of ML-based CPS in safety-critical applications, and aims to support the focus on research onto safety hazards that are not yet adequately addressed.

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