Multipart File Fixity Hashing for Trusted Integrity Verification
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Solution Overview
Problem
Current solutions for verifying file integrity, such as using cryptographic hashes for large files, are inefficient and vulnerable to attacks in cloud infrastructures that support multipart uploads and downloads, allowing attackers to forge files in trusted databases.
Innovation Solution
The method involves slicing a file into parts, calculating digests for each part, combining them into a master hash, and using a private key to generate a master hash signature, which is verified using a public key and stored in a trusted database, ensuring the file's pristine state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cryptographic operations are performed on the entire image data, then image security is improved, but processing time increases
Solution Approach 1:
The patent divides the image data into multiple blocks and performs cryptographic operations on selected blocks rather than the entire image. This segmentation allows the system to maintain security for critical image portions while reducing overall processing time by excluding non-critical portions from encryption/decryption operations.
Solution Approach 2:
The patent applies cryptographic operations to only a partial set of image blocks based on confidence scores, rather than processing all blocks. This partial action approach maintains security for uncertain regions while skipping redundant cryptographic operations on already-verified regions, thereby reducing processing time.
2Productivity
If image data is compressed, then transmission efficiency is improved, but image quality deteriorates
Solution Approach 1:
The patent applies different quality levels of compression to different image blocks based on their confidence scores and security requirements. Critical blocks with low confidence scores undergo minimal or no compression to preserve quality, while non-critical blocks with high confidence scores can tolerate higher compression ratios, thus optimizing overall transmission efficiency without significantly degrading image quality.
3Measurement precision
If confidence threshold is increased, then detection accuracy is improved, but false negatives increase
Solution Approach 1:
The patent dynamically adjusts the confidence threshold for cryptographic operations based on the detected confidence scores of image blocks. Instead of using a fixed high threshold that would cause false negatives, the system adaptively selects blocks for cryptographic processing, ensuring that blocks with scores below the threshold still receive appropriate security treatment when needed, thereby reducing false negatives while maintaining detection accuracy.
Data Source
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AI summary
Fixity data processing of a file by an ingester, including: receiving and processing the file by slicing the file into a plurality of parts; calculating a digest of each part until digests of all of the plurality of parts have been calculated; calculating a master hash as a combination of the digests of all of the plurality of parts; calculating a master hash signature using the master hash and a private key of the ingester; forming a fixity data including a set of digests which includes digests of all of the plurality of parts, the master hash, the master hash signature, and a public key of the ingester; sending the fixity data to a verifier; and storing, in a trusted database, a fixity metadata including the master hash, the master hash signature, the public key of the ingester, and an identifier of the file.