Circuit Part Correlation for Side-Channel Leakage Source Identification
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Solution Overview
Problem
Existing methods for side channel analysis fail to accurately identify the source of side channel leakage in electronic circuits, such as power consumption or electromagnetic radiation, which can reveal sensitive information like cryptographic keys.
Innovation Solution
A method is developed to simulate the operation of an electronic circuit under stimulus, compare the simulated leakage with an expected leakage model, and rank circuit parts based on correlation to identify the source of side channel leakage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If side channel analysis is performed using power consumption monitoring, then information leakage can be detected, but the source of leakage cannot be accurately identified
Solution Approach 1:
The circuit design is divided into multiple circuit parts, and the simulation determines a correlation value for each individual circuit part. This segmentation allows the identification of specific leakage sources rather than detecting leakage at the circuit level only, directly resolving the contradiction by enabling precise source identification while maintaining manageable analysis complexity through modular evaluation.
Solution Approach 2:
A simulation-based intermediary model is introduced that computes expected leakage quantities for each circuit part and compares them with actual measured leakage. This intermediary simulation layer acts as a mediator between the physical circuit and the analysis tool, enabling accurate source identification without requiring direct complex measurement of each circuit component.
2Measurement precision
If circuit simulation is performed for each circuit part, then leakage sources can be identified, but computational time increases
Solution Approach 1:
The simulation performs computations over a determined leakage time interval, focusing computational resources on the relevant time window where leakage occurs. This preliminary identification of the leakage time interval prevents unnecessary simulations outside this window, reducing overall computational time while maintaining accurate source identification within the critical period.
Solution Approach 2:
The analysis focuses computational effort locally on circuit parts that exhibit higher correlation values with the leakage model. Rather than uniformly analyzing all circuit parts with equal depth, the method applies local quality by concentrating simulation resources on suspicious components, thereby reducing total simulation time while preserving identification accuracy for the most likely leakage sources.
3Measurement precision
If correlation analysis is performed between simulated and expected leakage responses, then circuit parts can be ranked, but measurement and detection difficulty increases
Solution Approach 1:
The method creates a simulated copy of the circuit's leakage behavior through simulation, which can be easily manipulated and analyzed. This simulated leakage response copy allows for straightforward correlation calculations with measured leakage, avoiding the complexity of directly analyzing the physical circuit's leakage characteristics while maintaining measurement accuracy through the simulation model.
Data Source
AI summary
A method of identifying, in a circuit design of an electronic circuit, a source of side channel leakage of the electronic circuit. The method comprises: a) simulating over a leakage time interval an operation of the circuit in response to at least one stimulus, thereby deriving for each one of the at least one stimulus per circuit part of the electronic circuit a respective simulated leakage quantity circuit part response over the leakage time interval; b) obtaining for each one of the at least one stimulus an expected leakage quantity response over the leakage time interval from a processing of each one of the at least one stimulus by a leakage model, the leakage model modelling a leak-quantity at a processing of a secure asset; c) determining respective circuit part correlations over the leakage time interval between the respective simulated leakage quantity circuit part responses and the expected leakage quantity responses; d) ranking the circuit parts based on the circuit part correlations between the respective simulated leakage quantity circuit part responses and the expected leakage quantity responses and e) identifying as the source of side channel leakage the circuit part for which a highest one of the circuit correlations has been determined between the expected leakage quantity responses and the respective simulated leakage quantity circuit part responses.