Key points are not available for this paper at this time.
This study proposes a new adaptive template attack scheme for extracting secret keys in Montgomery-ladder-based elliptic curve cryptography (ECC) by effectively exploiting the leakage difference between key bits 1 and 0. To determine the key length and number of computation cycles per bit of the ECC to be attacked, the proposed adaptive attack employs an adaptive leakage-windowing technique and correlation analysis on the power trace obtained from an ECC module with a secret key. The point of interest (POI) is identified at the bit with the maximum difference in leakage between key bits 1 and 0 using the leakage window per bit. The trace from the victim ECC hardware with secret key is compared to those collected in prior templates with key bits 1 and 0 to recover the key. To validate the performance, a Xilinx Artix-7 FPGA chip was used to implement an Edward-curve digital signature algorithm (EdDSA) with Ed25519 and SHA-512 accelerators. The experimental results show a favorable key recovery rate of 100%. Further attack results are presented for the ECC modules with advanced countermeasures against side-channel attack, such as projective coordinate and/or scalar randomization It is validated that the proposed adaptive attack is able to exploit successfully 100% the keys of Montgomery-ladder-based ECC accelerators without and with countermeasures of projective coordinate or scalar randomization. Only a heavily resource-consumed ECC module with implemented projective coordinate, scalar randomization and a cryptographic secure random number generator is capable of defending the proposed attack.
Building similarity graph...
Analyzing shared references across papers
Loading...
Chun-Heng You
National Yang Ming Chiao Tung University
Chih-Hao Chiang
National Yang Ming Chiao Tung University
Paul C.-P. Chao
National Yang Ming Chiao Tung University
IEEE Internet of Things Journal
National Yang Ming Chiao Tung University
Building similarity graph...
Analyzing shared references across papers
Loading...
You et al. (Mon,) studied this question.
synapsesocial.com/papers/68e712b5b6db64358768b750 — DOI: https://doi.org/10.1109/jiot.2024.3384076