TY  - JOUR
AU  - Ahmed, Amjed Abbas
AU  - Salim, Rana Ali 
AU  - Hasan, Mohammad Kamrul 
PY  - 2023/12/22
Y2  - 2025/01/01
TI  - Deep Learning Method for Power Side-Channel Analysis on Chip Leakages
JF  - Elektronika ir Elektrotechnika
JA  - ELEKTRON ELEKTROTECH
VL  - 29
IS  - 6
SE  - 
DO  - 10.5755/j02.eie.34650
UR  - https://eejournal.ktu.lt/index.php/elt/article/view/34650
SP  - 50-57
AB  - <p>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 masking-countermeasure 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.</p>
ER  -