Abstract
In this paper, we proposed a learning-based method to find the instruction which CPU is executing. Reverse engineering is an important issue on military, product security analysis, and intellectual property. Our work is a kind of reverse engineering. We can get the information of instruction without direct accessing CPU. While a CPU is running, it would emit EM signal. We collect the EM signal and combine Deep learning model and novel speech processing method to classify it. In our work, firstly, we use Deep learning network based on convolution neural network (CNN). Then, we propose a Tree Structure Network (TSN) and combine label to solve the problems of both data imbalance and Hard Separate Pairs(HSP). Finally, we can classify the EM signal with 61% Top-1 (the strictest) accuracy. To the best of our knowledge, this is the first work that use learning-based method to classify the EM signal.
| Original language | English |
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| Title of host publication | 2019 Joint International Symposium on Electromagnetic Compatibility, Sapporo and Asia-Pacific International Symposium on Electromagnetic Compatibility, EMC Sapporo/APEMC 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 246-249 |
| Number of pages | 4 |
| ISBN (Electronic) | 9784885523229 |
| DOIs | |
| State | Published - 06 2019 |
| Externally published | Yes |
| Event | 2019 Joint International Symposium on Electromagnetic Compatibility, Sapporo and Asia-Pacific International Symposium on Electromagnetic Compatibility, EMC Sapporo/APEMC 2019 - Sapporo, Japan Duration: 03 06 2019 → 07 06 2019 |
Publication series
| Name | 2019 Joint International Symposium on Electromagnetic Compatibility, Sapporo and Asia-Pacific International Symposium on Electromagnetic Compatibility, EMC Sapporo/APEMC 2019 |
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Conference
| Conference | 2019 Joint International Symposium on Electromagnetic Compatibility, Sapporo and Asia-Pacific International Symposium on Electromagnetic Compatibility, EMC Sapporo/APEMC 2019 |
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| Country/Territory | Japan |
| City | Sapporo |
| Period | 03/06/19 → 07/06/19 |
Bibliographical note
Publisher Copyright:© 2019 The Institute of Electronics, Information and Communication Engineer.
Keywords
- Convolutional neural network
- Information leakage
- Instruction EM signal classification
- Reverse engineering