PMID- 32033269
OWN - NLM
STAT- MEDLINE
DCOM- 20201110
LR  - 20201110
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 20
IP  - 3
DP  - 2020 Feb 5
TI  - Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical 
      Systems.
LID - 10.3390/s20030844 [doi]
LID - 844
AB  - 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.
FAU - Johnson, Anju P
AU  - Johnson AP
AUID- ORCID: 0000-0002-7017-1644
AD  - 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.
FAU - Al-Aqrabi, Hussain
AU  - Al-Aqrabi H
AUID- ORCID: 0000-0003-1920-7418
AD  - Department of Computer Science, Centre for Industrial Analytics (CIndA), School 
      of Computing and Engineering, University of Huddersfield, Queensgate, 
      Huddersfield HD1 3DH, UK.
FAU - Hill, Richard
AU  - Hill R
AUID- ORCID: 0000-0003-0105-7730
AD  - Department of Computer Science, Centre for Industrial Analytics (CIndA), School 
      of Computing and Engineering, University of Huddersfield, Queensgate, 
      Huddersfield HD1 3DH, UK.
LA  - eng
PT  - Journal Article
DEP - 20200205
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
MH  - Benchmarking
MH  - Computer Security/*trends
MH  - *Computers
MH  - Humans
MH  - Internet/*trends
MH  - Internet of Things/*trends
MH  - Natural Science Disciplines/trends
MH  - Neural Networks, Computer
PMC - PMC7038767
OTO - NOTNLM
OT  - astrocytes
OT  - bio-inspired engineering
OT  - cyber-physical systems
OT  - design for trust
OT  - field programmable gate qrray
OT  - hardware trojan horse
OT  - internet of things
OT  - security
OT  - spiking neural networks
COIS- The authors declare no conflict of interest.
EDAT- 2020/02/09 06:00
MHDA- 2020/11/11 06:00
PMCR- 2020/02/01
CRDT- 2020/02/09 06:00
PHST- 2019/12/12 00:00 [received]
PHST- 2020/02/02 00:00 [revised]
PHST- 2020/02/02 00:00 [accepted]
PHST- 2020/02/09 06:00 [entrez]
PHST- 2020/02/09 06:00 [pubmed]
PHST- 2020/11/11 06:00 [medline]
PHST- 2020/02/01 00:00 [pmc-release]
AID - s20030844 [pii]
AID - sensors-20-00844 [pii]
AID - 10.3390/s20030844 [doi]
PST - epublish
SO  - Sensors (Basel). 2020 Feb 5;20(3):844. doi: 10.3390/s20030844.