Report
A Practical Methodology for ML-Based EM Side Channel Disassemblers
| العنوان: | A Practical Methodology for ML-Based EM Side Channel Disassemblers |
|---|---|
| المؤلفون: | Arguello, Cesar N., Searle, Hunter, Rampazzi, Sara, Butler, Kevin R. B. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Computer Science - Cryptography and Security |
| الوصف: | Providing security guarantees for embedded devices with limited interface capabilities is an increasingly crucial task. Although these devices don't have traditional interfaces, they still generate unintentional electromagnetic signals that correlate with the instructions being executed. By collecting these traces using our methodology and leveraging a random forest algorithm to develop a machine learning model, we built an EM side channel based instruction level disassembler. The disassembler was tested on an Arduino UNO board, yielding an accuracy of 88.69% instruction recognition for traces from twelve instructions captured at a single location in the device; this is an improvement compared to the 75.6% (for twenty instructions) reported in previous similar work. Comment: Accepted to the poster section of the 7th IEEE European Symposium on Security and Privacy 2022 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2206.10746 |
| رقم الانضمام: | edsarx.2206.10746 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |