File Hashing Robustness via Pre-Computed Modifier Codes
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Solution Overview
Problem
Existing hashing methods lack robustness, making it difficult to distinguish between similar data sets, leading to a high probability of generating the same hash from different but similar data.
Innovation Solution
A method that calculates a modifier code for a file, increasing the number of possible hashes by mixing it with different mixer numbers using the same hashing function, involving steps to generate and compare lists of modifier codes and mixer numbers, and selecting the most robust modifier code based on hash counts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a standard hashing function is used on similar data files, then the hashing process is simple and fast, but the same hash is generated for different but similar data, reducing security
Solution Approach 1:
The patent introduces a modifier code as an intermediary element between the original data and the hashing function. This modifier code is combined with the data before hashing, ensuring that even similar data produces different hashes. The modifier code acts as a mediator that breaks the direct relationship between similar inputs and identical outputs, thereby enhancing hashing robustness without fundamentally changing the hashing process itself
Solution Approach 2:
The patent changes the input parameters of the hashing function by introducing a modifier code that varies the data being hashed. Instead of hashing the original data directly, the system hashes the combination of original data and modifier code. This parameter change ensures that similar data files produce different hash values, improving reliability while maintaining a relatively simple process
2Reliability
If multiple mixer numbers are tested to increase hash diversity, then the number of different hashes increases, but the computational time and resources increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-selecting and storing effective modifier codes that have been proven to generate unique hashes for similar data. Instead of testing multiple mixer numbers each time hashing is needed, the system uses pre-computed modifier codes from a lookup table, significantly reducing computational time while maintaining hash uniqueness
Solution Approach 2:
The patent uses partial action by selecting only the necessary number of modifier codes required to achieve sufficient hash diversity. Rather than exhaustively testing all possible mixer numbers, the system uses a limited set of pre-determined modifier codes that provide adequate uniqueness, reducing computational overhead while maintaining security
3Reliability
If a modifier code is added to increase the number of possible hashes, then hashing robustness improves, but the complexity of selecting the optimal modifier code increases
Solution Approach 1:
The patent resolves the complexity of modifier code selection by performing it in advance. A lookup table is pre-computed containing modifier codes that have been tested and verified to produce unique hashes for similar data. During actual hashing operations, the system simply retrieves the appropriate modifier code from this pre-prepared table, eliminating the need for complex real-time selection processes
Solution Approach 2:
The patent uses copying by storing pre-computed modifier codes in a lookup table that can be reused multiple times. Instead of recalculating optimal modifier codes for each hashing operation, the system copies and reuses proven modifier codes from the table, simplifying the selection process while maintaining security
Data Source
AI summary
Method for calculating a modifier code of a file, the method comprising the following steps:a) establishing a list of possible modifier codes;b) establishing a list of a plurality of possible mixer numbers;c) for each modifier code: i) creating a list of hashes of the file;ii) for each mixer number, calculating the hash of the file mixed and modified by the modifier code, the modification of the file being performed using the same modification function;iii) adding each hash calculated in step ii) to the list of hashes of the file;iv) counting the number of different elements N of the list of hashes;v) memorizing this number N, as well as the associated modifier code, if N is the first to be counted or is greater than the number N previously memorized; andd) returning the last modifier code memorized.