Side-Channel Cracking Device Using Leakage Model Correlation
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Solution Overview
Problem
Side-channel attacks on IoT devices are inefficient due to high measurement and algorithm noise, requiring large data processing and complexity, which hinders quick cracking of secret keys.
Innovation Solution
A cracking method and device that builds a leakage model, performs mathematical calculations on input data to generate a mathematical model, hypothesizes keys, generates simulation data, detects leakage data, and determines the secret key by correlating simulation and calculated data, reducing noise and data complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional side-channel attack methods are used, then the secret key can be cracked, but the cracking time is long due to high measurement noise and algorithm noise requiring large data processing
Solution Approach 1:
The patent extracts and removes noise components from the leakage data through mathematical calculations. By separating the signal from measurement noise and algorithm noise, the method improves the signal-to-noise ratio and reduces the data processing burden, thereby decreasing cracking time while maintaining measurement precision.
Solution Approach 2:
The patent performs preliminary mathematical calculations on the leakage model before the actual cracking process. By pre-processing the data to eliminate noise and extract relevant features, the method prepares optimized data structures that reduce subsequent processing time and improve cracking efficiency.
2Productivity
If traditional side-channel attack methods are used, then the secret key can be cracked, but the data processing complexity is high requiring large quantity of data
Solution Approach 1:
The patent extracts only the essential features from the leakage data by removing noise components and redundant information. This extraction process reduces the quantity of data that needs to be processed while maintaining the critical information needed for cracking, thereby improving productivity and reducing processing complexity.
Solution Approach 2:
The patent transforms the leakage data through mathematical calculations that change the parameters of the data representation. By converting raw leakage data into processed features with improved signal-to-noise ratio, the method reduces data complexity and increases cracking efficiency with fewer data points required.
3Measurement precision
If more data is collected to improve cracking accuracy, then the cracking accuracy improves, but the data processing time and complexity increase
Solution Approach 1:
The patent extracts the essential cryptographic information from leakage data by removing measurement noise and algorithm noise. This extraction allows accurate cracking with fewer data points, improving measurement precision while reducing the time required to process large volumes of data.
Solution Approach 2:
The patent performs preliminary noise reduction and feature extraction on the leakage data before the cracking process. This pre-processing step improves cracking accuracy by enhancing signal quality, while simultaneously reducing the time needed to process the data by eliminating redundant and noisy information.
Data Source
AI summary
A cracking method for cracking a secret key of an encrypting device includes: building up a leakage model for the encrypting device; performing a mathematical calculation on the leakage model, according to a plurality of sets of input data, to generate a mathematical model; generating a plurality of sets of hypothesized keys; generating a plurality of sets of simulation data corresponding to the hypothesized keys using the mathematical model; providing the input data for the encrypting device and detecting a plurality of sets of leakage data generated by the encrypting device; performing the mathematical calculation on the leakage data to generate calculated data; determining a correlation between each of the simulation data and the calculated data; and determining one of the hypothesized keys to be consistent with the secret key according to the correlation.