Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial Systems
The need for reliable communications in industrial systems becomes more evident as industries strive to increase reliance on automation. This trend has sustained the adoption of WirelessHART communications as a key enabling technology and its operational integrity must be ensured. This paper focuses...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/13/4906 |
| _version_ | 1797441903641231360 |
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| author | Willie H. Mims Michael A. Temple Robert F. Mills |
| author_facet | Willie H. Mims Michael A. Temple Robert F. Mills |
| author_sort | Willie H. Mims |
| collection | DOAJ |
| description | The need for reliable communications in industrial systems becomes more evident as industries strive to increase reliance on automation. This trend has sustained the adoption of WirelessHART communications as a key enabling technology and its operational integrity must be ensured. This paper focuses on demonstrating pre-deployment counterfeit detection using active 2D Distinct Native Attribute (2D-DNA) fingerprinting. Counterfeit detection is demonstrated using experimentally collected signals from eight commercial WirelessHART adapters. Adapter fingerprints are used to train 56 Multiple Discriminant Analysis (MDA) models with each representing five authentic network devices. The three non-modeled devices are introduced as counterfeits and a total of 840 individual authentic (modeled) versus counterfeit (non-modeled) ID verification assessments performed. Counterfeit detection is performed on a fingerprint-by-fingerprint basis with best case per-device Counterfeit Detection Rate (%CDR) estimates including 87.6% < %CDR < 99.9% and yielding an average cross-device %CDR ≈ 92.5%. This full-dimensional feature set performance was echoed by dimensionally reduced feature set performance that included per-device 87.0% < %CDR < 99.7% and average cross-device %CDR ≈ 91.4% using only 18-of-291 features—the demonstrated %CDR > 90% with an approximate 92% reduction in the number of fingerprint features is sufficiently promising for small-scale network applications and warrants further consideration. |
| first_indexed | 2024-03-09T12:33:58Z |
| format | Article |
| id | doaj.art-78fa1ec8523f4986936c111dc2ed576a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T12:33:58Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-78fa1ec8523f4986936c111dc2ed576a2023-11-30T22:26:59ZengMDPI AGSensors1424-82202022-06-012213490610.3390/s22134906Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial SystemsWillie H. Mims0Michael A. Temple1Robert F. Mills2Department of Electrical and Computer Engineering, US Air Force Institute of Technology, Wright-Patterson AFB, OH 45433, USADepartment of Electrical and Computer Engineering, US Air Force Institute of Technology, Wright-Patterson AFB, OH 45433, USADepartment of Electrical and Computer Engineering, US Air Force Institute of Technology, Wright-Patterson AFB, OH 45433, USAThe need for reliable communications in industrial systems becomes more evident as industries strive to increase reliance on automation. This trend has sustained the adoption of WirelessHART communications as a key enabling technology and its operational integrity must be ensured. This paper focuses on demonstrating pre-deployment counterfeit detection using active 2D Distinct Native Attribute (2D-DNA) fingerprinting. Counterfeit detection is demonstrated using experimentally collected signals from eight commercial WirelessHART adapters. Adapter fingerprints are used to train 56 Multiple Discriminant Analysis (MDA) models with each representing five authentic network devices. The three non-modeled devices are introduced as counterfeits and a total of 840 individual authentic (modeled) versus counterfeit (non-modeled) ID verification assessments performed. Counterfeit detection is performed on a fingerprint-by-fingerprint basis with best case per-device Counterfeit Detection Rate (%CDR) estimates including 87.6% < %CDR < 99.9% and yielding an average cross-device %CDR ≈ 92.5%. This full-dimensional feature set performance was echoed by dimensionally reduced feature set performance that included per-device 87.0% < %CDR < 99.7% and average cross-device %CDR ≈ 91.4% using only 18-of-291 features—the demonstrated %CDR > 90% with an approximate 92% reduction in the number of fingerprint features is sufficiently promising for small-scale network applications and warrants further consideration.https://www.mdpi.com/1424-8220/22/13/4906device fingerprintingcounterfeit detectionIoTIIoTIR 4.0multiple discriminant analysis |
| spellingShingle | Willie H. Mims Michael A. Temple Robert F. Mills Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial Systems Sensors device fingerprinting counterfeit detection IoT IIoT IR 4.0 multiple discriminant analysis |
| title | Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial Systems |
| title_full | Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial Systems |
| title_fullStr | Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial Systems |
| title_full_unstemmed | Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial Systems |
| title_short | Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial Systems |
| title_sort | active 2d dna fingerprinting of wirelesshart adapters to ensure operational integrity in industrial systems |
| topic | device fingerprinting counterfeit detection IoT IIoT IR 4.0 multiple discriminant analysis |
| url | https://www.mdpi.com/1424-8220/22/13/4906 |
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