TY - GEN
T1 - Intelligent security measures for smart cyber physical systems
AU - Shafique, Muhammad
AU - Khalid, Faiq
AU - Rehman, Semeen
N1 - Funding Information:
ACKNOWLEDGMENT This work is supported in parts by the Austrian Research Promotion Agency (FFG) and the Austrian Federal Ministry for Transport, Innovation, and Technology (BMVIT) under the “ICT of the Future” project, IoT4CPS: Trustworthy IoT for Cyber-Physical Systems.
Publisher Copyright:
© 2018 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/10/12
Y1 - 2018/10/12
N2 - The exponential growth of cyber-physical systems (CPS), especially in safety-critical applications, has imposed several security threats (like manipulation of communication channels, hardware components, and associated software) due to complex cybernetics and the interaction among (independent) CPS domains. These security threats have led to the development of different static as well as adaptive detection and protection techniques on different layers of the CPS stack, e.g., cross-layer and intra-layer connectivity. This paper first presents a brief overview of various security threats at different CPS layers, their respective threat models and associated research challenges to develop robust security measures. Moreover, this paper provides a brief yet comprehensive survey of the state-of-the-art static and adaptive techniques for detection and prevention, and their inherent limitations, i.e., incapability to capture the dormant or uncertainty-based runtime security attacks. To address these challenges, this paper also discusses the intelligent security measures (using machine learning-based techniques) against several characterized attacks on different layers of the CPS stack. Furthermore, we identify the associated challenges and open research problems in developing intelligent security measures for CPS. Towards the end, we provide an overview of our project on security for smart CPS along with important analyses.
AB - The exponential growth of cyber-physical systems (CPS), especially in safety-critical applications, has imposed several security threats (like manipulation of communication channels, hardware components, and associated software) due to complex cybernetics and the interaction among (independent) CPS domains. These security threats have led to the development of different static as well as adaptive detection and protection techniques on different layers of the CPS stack, e.g., cross-layer and intra-layer connectivity. This paper first presents a brief overview of various security threats at different CPS layers, their respective threat models and associated research challenges to develop robust security measures. Moreover, this paper provides a brief yet comprehensive survey of the state-of-the-art static and adaptive techniques for detection and prevention, and their inherent limitations, i.e., incapability to capture the dormant or uncertainty-based runtime security attacks. To address these challenges, this paper also discusses the intelligent security measures (using machine learning-based techniques) against several characterized attacks on different layers of the CPS stack. Furthermore, we identify the associated challenges and open research problems in developing intelligent security measures for CPS. Towards the end, we provide an overview of our project on security for smart CPS along with important analyses.
KW - Attack Surface
KW - Attacks
KW - Autonomous Vehicle
KW - CPS
KW - Cyber-Physical Systems
KW - Deep Learning
KW - DNNs
KW - Intelligent Measures
KW - Machine Learning
KW - Neural Networks
KW - Security
KW - Static and Dynamic Techniques
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UR - http://www.scopus.com/inward/citedby.url?scp=85056484526&partnerID=8YFLogxK
U2 - 10.1109/DSD.2018.00058
DO - 10.1109/DSD.2018.00058
M3 - Conference contribution
AN - SCOPUS:85056484526
T3 - Proceedings - 21st Euromicro Conference on Digital System Design, DSD 2018
SP - 280
EP - 287
BT - Proceedings - 21st Euromicro Conference on Digital System Design, DSD 2018
A2 - Konofaos, Nikos
A2 - Novotny, Martin
A2 - Skavhaug, Amund
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st Euromicro Conference on Digital System Design, DSD 2018
Y2 - 29 August 2018 through 31 August 2018
ER -