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Article

Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical Systems

1
Department of Engineering and Technology, Centre for Planning, Autonomy and Representation of Knowledge (PARK), School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
2
Department of Computer Science, Centre for Industrial Analytics (CIndA), School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(3), 844; https://doi.org/10.3390/s20030844
Received: 12 December 2019 / Revised: 2 February 2020 / Accepted: 2 February 2020 / Published: 5 February 2020
Internet of Things (IoT) and Cyber-Physical Systems (CPS) have profoundly influenced the way individuals and enterprises interact with the world. Although attacks on IoT devices are becoming more commonplace, security metrics often focus on software, network, and cloud security. For CPS systems employed in IoT applications, the implementation of hardware security is crucial. The identity of electronic circuits measured in terms of device parameters serves as a fingerprint. Estimating the parameters of this fingerprint assists the identification and prevention of Trojan attacks in a CPS. We demonstrate a bio-inspired approach for hardware Trojan detection using unsupervised learning methods. The bio-inspired principles of pattern identification use a Spiking Neural Network (SNN), and glial cells form the basis of this work. When hardware device parameters are in an acceptable range, the design produces a stable firing pattern. When unbalanced, the firing rate reduces to zero, indicating the presence of a Trojan. This network is tunable to accommodate natural variations in device parameters and to avoid false triggering of Trojan alerts. The tolerance is tuned using bio-inspired principles for various security requirements, such as forming high-alert systems for safety-critical missions. The Trojan detection circuit is resilient to a range of faults and attacks, both intentional and unintentional. Also, we devise a design-for-trust architecture by developing a bio-inspired device-locking mechanism. The proposed architecture is implemented on a Xilinx Artix-7 Field Programmable Gate Array (FPGA) device. Results demonstrate the suitability of the proposal for resource-constrained environments with minimal hardware and power dissipation profiles. The design is tested with a wide range of device parameters to demonstrate the effectiveness of Trojan detection. This work serves as a new approach to enable secure CPSs and to employ bio-inspired unsupervised machine intelligence. View Full-Text
Keywords: security; internet of things; cyber-physical systems; hardware trojan horse; design for trust; field programmable gate qrray; bio-inspired engineering; spiking neural networks; astrocytes security; internet of things; cyber-physical systems; hardware trojan horse; design for trust; field programmable gate qrray; bio-inspired engineering; spiking neural networks; astrocytes
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MDPI and ACS Style

Johnson, A.P.; Al-Aqrabi, H.; Hill, R. Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical Systems. Sensors 2020, 20, 844. https://doi.org/10.3390/s20030844

AMA Style

Johnson AP, Al-Aqrabi H, Hill R. Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical Systems. Sensors. 2020; 20(3):844. https://doi.org/10.3390/s20030844

Chicago/Turabian Style

Johnson, Anju P., Hussain Al-Aqrabi, and Richard Hill. 2020. "Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical Systems" Sensors 20, no. 3: 844. https://doi.org/10.3390/s20030844

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