Side channel analysis method and system based on bit decoupling and medium

By employing a bit-decoupling-based side-channel analysis method, this approach utilizes adaptive feature extraction and attention mechanisms to model bit dependencies, combined with gated residual connections. This solves the problems of model complexity and information loss in existing side-channel analysis methods, achieving efficient and stable key recovery.

CN121887374AActive Publication Date: 2026-04-17QINGDAO INST OF COMPUTING TECH XIDIAN UNIV
3 Cites 0 Cited by

Patent Information

Application Number
CN202610351918.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-23
Publication Date
2026-04-17
Estimated Expiration
2046-03-23

AI Technical Summary

Technical Problem

Existing side-channel analysis methods are inefficient in the face of advanced protection measures. The single-byte 256 classification model suffers from the curse of dimensionality and information loss, while the independent bit model ignores the nonlinear dependencies between bits, making key recovery difficult.

Method used

A side-channel analysis method based on bit decoupling is adopted. Binary bit vectors are generated by multi-label decoupling, and bit feature dependencies are modeled using an adaptive feature extraction network and attention mechanism. A gated residual connection mechanism is introduced for training, and the output fused features are used for key recovery.

Benefits of technology

It significantly reduces the number of model parameters and sample requirements, improves key recovery capability in low signal-to-noise ratio environments, automatically adapts to signal changes, has good stability and convergence, and can effectively utilize strong leaked bits to assist in the prediction of weak leaked bits.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention relates to the technical field of side channel analysis, and particularly provides a side channel analysis method and system based on bit decoupling and a medium, and the method comprises the steps: obtaining power consumption data during encryption, calculating an intermediate value, and carrying out the multi-label decoupling; extracting multi-scale features from the preprocessed energy traces, performing weighted fusion, and outputting global shared features; mapping the global shared features into initial bit features through linear projection, calculating a dependency relationship between the bit features by using an attention mechanism, and generating interactive bit features; the fusion proportion is dynamically adjusted through gating parameters, fusion features are input into a multi-label classifier, the posterior probability of each bit is obtained, and a loss function is adopted for training; and inputting a to-be-measured energy trace into the trained neural network model, outputting a prediction probability, and selecting a target key by calculating the confidence coefficient of the candidate key through traversal. According to the method, the quantity of required energy traces is greatly reduced, and meanwhile, the attack success rate in a low signal-to-noise ratio environment is remarkably improved.
Need to check novelty before this filing date? Find Prior Art