Intelligent Electromagnetic Sensors for Non-Invasive Trojan Detection
| Autor: | Chen, Ethan, Kan, John, Yang, Bo-Yuan, Zhu, Jimmy, Chen, Vanessa |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
real time
Chemical technology ComputerApplications_COMPUTERSINOTHERSYSTEMS TP1-1185 Biochemistry Article Atomic and Molecular Physics and Optics Analytical Chemistry machine learning electromagnetic sensing hardware security Quality of Life Electrical and Electronic Engineering Electromagnetic Phenomena Instrumentation |
| Zdroj: | Sensors; Volume 21; Issue 24; Pages: 8288 Sensors, Vol 21, Iss 8288, p 8288 (2021) Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s21248288 |
| Popis: | Rapid growth of sensors and the Internet of Things is transforming society, the economy and the quality of life. Many devices at the extreme edge collect and transmit sensitive information wirelessly for remote computing. The device behavior can be monitored through side-channel emissions, including power consumption and electromagnetic (EM) emissions. This study presents a holistic self-testing approach incorporating nanoscale EM sensing devices and an energy-efficient learning module to detect security threats and malicious attacks directly at the front-end sensors. The built-in threat detection approach using the intelligent EM sensors distributed on the power lines is developed to detect abnormal data activities without degrading the performance while achieving good energy efficiency. The minimal usage of energy and space can allow the energy-constrained wireless devices to have an on-chip detection system to predict malicious attacks rapidly in the front line. |
| Databáze: | OpenAIRE |
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