Machine learning based side‐channel‐attack countermeasure with hamming‐distance redistribution and its application on advanced encryption standard

2017 ◽  
Vol 53 (14) ◽  
pp. 926-928 ◽  
Author(s):  
Weiwei Shan ◽  
Shuai Zhang ◽  
Yukun He
Author(s):  
Qingyun Zou ◽  
Xiaoxin Cui ◽  
Zhenhui Dai ◽  
Yisong Kuang ◽  
Yi Zhong ◽  
...  

Integration ◽  
2019 ◽  
Vol 68 ◽  
pp. 80-86
Author(s):  
Luca Crocetti ◽  
Luca Baldanzi ◽  
Matteo Bertolucci ◽  
Luca Sarti ◽  
Berardino Carnevale ◽  
...  

Author(s):  
Stjepan Picek ◽  
Annelie Heuser ◽  
Alan Jovic ◽  
Shivam Bhasin ◽  
Francesco Regazzoni

We concentrate on machine learning techniques used for profiled sidechannel analysis in the presence of imbalanced data. Such scenarios are realistic and often occurring, for instance in the Hamming weight or Hamming distance leakage models. In order to deal with the imbalanced data, we use various balancing techniques and we show that most of them help in mounting successful attacks when the data is highly imbalanced. Especially, the results with the SMOTE technique are encouraging, since we observe some scenarios where it reduces the number of necessary measurements more than 8 times. Next, we provide extensive results on comparison of machine learning and side-channel metrics, where we show that machine learning metrics (and especially accuracy as the most often used one) can be extremely deceptive. This finding opens a need to revisit the previous works and their results in order to properly assess the performance of machine learning in side-channel analysis.


2020 ◽  
Vol 55 (3) ◽  
pp. 794-804 ◽  
Author(s):  
Weiwei Shan ◽  
Shuai Zhang ◽  
Jiaming Xu ◽  
Minyi Lu ◽  
Longxing Shi ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Siva Kotipalli ◽  
Yong-Bin Kim ◽  
Minsu Choi

This work presents the design, hardware implementation, and performance analysis of novel asynchronous AES (advanced encryption standard) Key Expander and Round Function, which offer increased side-channel attack (SCA) resistance. These designs are based on a delay-insensitive (DI) logic paradigm known as null convention logic (NCL), which supports useful properties for resisting SCAs including dual-rail encoding, clock-free operation, and monotonic transitions. Potential benefits include reduced and more uniform switching activities and reduced signal-to-noise (SNR) ratio. A novel method to further augment NCL AES hardware with random voltage scaling technique is also presented for additional security. Thereby, the proposed components leak significantly less side-channel information than conventional clocked approaches. To quantitatively verify such improvements, functional verification and WASSO (weighted average simultaneous switching output) analysis have been carried out on both conventional synchronous approach and the proposed NCL based approach using Mentor Graphics ModelSim and Xilinx simulation tools. Hardware implementation has been carried out on both designs exploiting a specified side-channel attack standard evaluation FPGA board, called SASEBO-GII, and the corresponding power waveforms for both designs have been collected. Along with the results of software simulations, we have analyzed the collected waveforms to validate the claims related to benefits of the proposed cryptohardware design approach.


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