Ciphertext Comparison via Segmented Lookup Tables Against Side-Channel Leakage
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Solution Overview
Problem
Existing post-quantum cryptography (PQC) algorithms are vulnerable to side channel attacks, particularly through differential power analysis and profiling attacks during ciphertext comparison operations, exposing secret keys.
Innovation Solution
A method and apparatus that segment ciphertexts into part bitstreams, utilize lookup tables to generate intermediate and result values with identical Hamming weights, and perform comparisons using these values to obscure power consumption patterns, thereby preventing side channel attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ciphertext comparison is performed using conventional methods, then comparison functionality is achieved, but the system becomes vulnerable to side channel attacks that can restore secret keys
Solution Approach 1:
The ciphertexts are segmented into multiple part bitstreams for processing. The comparison operation divides the ciphertexts into segments, processes each segment through lookup tables to generate intermediate values, and then combines results. This segmentation allows the system to maintain security by ensuring consistent Hamming weights across all intermediate values while breaking down the complex comparison into manageable parts that can be processed through the lookup table structure.
Solution Approach 2:
Lookup tables are introduced as intermediary structures that map input bitstream pairs to intermediate values with consistent Hamming weights. These lookup tables act as mediators between the raw ciphertext comparison and the final result, ensuring that no information about the actual ciphertext values leaks through power consumption patterns. The intermediary lookup tables transform the comparison operation into a form that is resistant to side channel analysis.
2Reliability
If lookup tables with consistent Hamming weights are used, then side channel attack resistance is improved, but memory requirements and processing complexity increase
Solution Approach 1:
Instead of using a single large lookup table that would require storing all possible ciphertext pairs, the system divides the lookup table into multiple smaller tables, each handling specific segments of the ciphertext. Each local lookup table stores only the necessary mappings for its specific segment, reducing the overall memory requirement. The local quality principle allows each table to be optimized for its specific function while collectively providing comprehensive coverage for the entire ciphertext comparison operation.
Data Source
AI summary
A ciphertext comparison method according to an embodiment is performed by a processor in a computing apparatus, and the method includes an operation of segmenting a first ciphertext and a second ciphertext into m part bitstreams (in this instance, m is a natural number satisfying 1<m), respectively; an operation of extracting a value corresponding to a j−1th part bitstream (in this instance, j=i+1, i is a natural number satisfying 0≤i≤m−1) of the first ciphertext and a j−1th part bitstream of the second ciphertext, as a jth intermediate value between a first value and a second value in a first lookup table including the first value and the second value of which Hamming weights are identical; an operation extracting a value corresponding to the jth intermediate value and a j−1th result value, as a jth result value between a third value and a fourth value in a second lookup table including the third value and the fourth value of which Hamming weights are identical; and in a case of j≠m, an operation of repeatedly performing extraction as the jth intermediate value and extraction as the jth result value by increasing J; and in a case of j=m, an operation of outputting an mth result value as a result value of comparison between the first ciphertext and the second ciphertext.