Identification of Microcontroller Unit Instruction Execution Using Electromagnetic Leakage and Neural Network Classification

被引：5

作者：

Yuan, Shih-Yi ^{[1
]}

机构：

[1] Feng Chia Univ, Dept Commun Engn, Taichung 40724, Taiwan

来源：

IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY | 2022年 / 64卷 / 04期

关键词：

Frequency-domain analysis; Electromagnetic interference; Data models; Analytical models; Time-domain analysis; Solid modeling; Training; Electromagnetic interference (EMI); IEC; 61967; neural network (NN); MODEL;

D O I：

10.1109/TEMC.2022.3159868

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this article, a novel method is proposed for determining the running state of a system through the classification of electromagnetic interference (EMI) leakage using neural network (NN) models. A modified IEC 61967 measurement platform is used to analyze the EMI signals of a microcontroller unit during its operation. A total of 17 NN models are developed and tested to determine the optimal model. The optimal NN model has ungrouped-Top3 and ungrouped-Top5 accuracies of 77.13% and 91.94%, respectively. The ungrouped-Top1 accuracy is improved by 7.53%. They are the highest improvements ever achieved to the best of the author's knowledge.

引用

页码：930 / 940

页数：11

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