التفاصيل البيبلوغرافية
| العنوان: |
Deep Learning Method for Power Side-Channel Analysis on Chip Leakages. |
| المؤلفون: |
Ahmed, Amjed Abbas, Salim, Rana Ali, Hasan, Mohammad Kamrul |
| المصدر: |
Electronics & Electrical Engineering; 2023, Vol. 29 Issue 6, p50-57, 8p |
| مصطلحات موضوعية: |
DEEP learning, ADVANCED Encryption Standard, CONVOLUTIONAL neural networks, SIGNAL processing, NOISE control, LEAKAGE |
| مستخلص: |
Power side channel analysis signal analysis is automated using deep learning. Signal processing and cryptanalytic techniques are necessary components of power side channel analysis. Chip leakages can be found using a classification approach called deep learning. In addition to this, we do this so that the deep learning network can automatically tackle signal processing difficulties such as re-alignment and noise reduction. We were able to break minimally protected Advanced Encryption Standard (AES), as well as maskingcountermeasure AES and protected elliptic-curve cryptography (ECC). These results demonstrate that the attacker knowledge required for side channel analysis, which had previously placed a significant emphasis on human abilities, is decreasing. This research will appeal to individuals with a technical background who have an interest in deep learning, side channel analysis, and security. [ABSTRACT FROM AUTHOR] |
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