Security analysis for cyber‐physical systems under undetectable attacks: A geometric approach

2018 ◽  
Vol 30 (11) ◽  
pp. 4359-4370 ◽  
Author(s):  
Zhengen Zhao ◽  
Ying Yang ◽  
Yuzhe Li ◽  
Ruijie Liu
Keyword(s):  
Security Analysis ◽  
Geometric Approach ◽  
Cyber Physical Systems ◽  
Physical Systems

scholarly journals Conceptualizing the key features of cyber‐physical systems in a multi‐layered representation for safety and security analysis

2019 ◽  
Vol 23 (2) ◽  
pp. 189-210 ◽  
Author(s):  
Nelson H. Carreras Guzman ◽  
Morten Wied ◽  
Igor Kozine ◽  
Mary Ann Lundteigen
Keyword(s):  
Security Analysis ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Key Features

An Actor-Based Approach for Security Analysis of Cyber-Physical Systems

2020 ◽  
pp. 130-147
Author(s):  
Fereidoun Moradi ◽  
Sara Abbaspour Asadollah ◽  
Ali Sedaghatbaf ◽  
Aida Čaušević ◽  
Marjan Sirjani ◽  
...  
Keyword(s):  
Security Analysis ◽  
Cyber Physical Systems ◽  
Physical Systems

scholarly journals Risk Management and Standard Compliance for Cyber-Physical Systems of Systems

2021 ◽  
Vol 13 (2) ◽  
pp. 32-39
Author(s):  
George Matta ◽  
Sebastian Chlup ◽  
Abdelkader Magdy Shaaban ◽  
Christoph Schmittner ◽  
Andreas Pinzenöhler ◽  
...  
Keyword(s):  
Risk Management ◽  
Cyber Security ◽  
Security Analysis ◽  
Cyber Physical Systems ◽  
Risk Identification ◽  
Security Requirements ◽  
Systems Of Systems ◽  
Physical Systems ◽  
Railway Systems ◽  
Industry Standards

The Internet of Things (IoT) and cloud technologies are increasingly implemented in the form of Cyber-Physical Systems of Systems (CPSoS) for the railway sector. In order to satisfy the security requirements of Cyber-Physical Systems (CPS), domainspecific risk identification assessment procedures have been developed. Threat modelling is one of the most commonly used methods for threat identification for the security analysis of CPSoS and is capable of targeting various domains. This paper reports our experience of using a risk management framework identify the most critical security vulnerabilities in CPSoS in the domain and shows the broader impact this work can have on the domain of safety and security management. Moreover, we emphasize the application of common analytical methods for cyber-security based on international industry standards to identify the most vulnerable assets. These will be applied to a meta-model for automated railway systems in the concept phase to support the development and deployment of these systems. Furthermore, it is the first step to create a secure and standard complaint system by design.

Fuzzy Control in Cyber-Physical Systems

2020 ◽  
Vol 2 (2) ◽  
pp. 46-58
Author(s):  
Michael Gr. Voskoglou
Keyword(s):  
Fuzzy Control ◽  
Autonomous Vehicles ◽  
Input Data ◽  
Fuzzy Numbers ◽  
Geometric Approach ◽  
Cyber Physical Systems ◽  
Control Model ◽  
Triangular Fuzzy Numbers ◽  
Physical Systems ◽  
Braking System

Controllers are devices regulating the operation of other devices or systems. Fuzzy controllers analyze the input data in terms of variables which take on continuous values in the interval [0, 1]. Since fuzzy logic has the advantage of expressing the solution of the problems in the natural language, the use of fuzzy instead of traditional controllers makes easier the mechanization of tasks that have been already successfully performed by humans. In the present paper a theoretical fuzzy control model is developed for the braking system of autonomous vehicles, which are included among the most characteristic examples of Cyber-Physical Systems. For this, a simple geometric approach is followed using triangular fuzzy numbers as the basic tools.

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