Rolling SHA-256 Verification and Adaptive Document Extraction
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Solution Overview
Problem
Existing systems face challenges in ensuring the integrity of workflow event sequences and efficient document extraction in cloud environments, with blockchain-based verification introducing latency and computational overhead, and template-based systems failing for unseen document layouts, leading to high computational costs and environmental impact.
Innovation Solution
A system utilizing a rolling SHA-256 digest salted with microsecond-precision timestamps for decentralized event verification and an adaptive document extraction method using layout hash-based routing, combining CPU-based template processing with GPU-driven AI fallback for efficient and sustainable document processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blockchain-based verification is used for event integrity, then security and immutability are improved, but latency and computational overhead increase significantly
Solution Approach 1:
The patent extracts the cryptographic verification function from the blockchain consensus mechanism, implementing it as a standalone rolling hash computation that can be performed independently without waiting for block confirmations or network consensus, thereby eliminating the latency bottleneck while preserving integrity verification
Solution Approach 2:
The patent replaces the complex blockchain mechanical system (consensus algorithms, block chaining, network propagation) with a simpler cryptographic hash chain mechanism that uses rolling SHA-256 digests with timestamp salting, achieving the same integrity guarantees with minimal computational overhead and no network dependency
2Productivity
If template-based rules are used for document extraction, then processing speed is improved, but adaptability to unseen layouts deteriorates
Solution Approach 1:
The patent implements a dynamic document extraction system that switches between two processing modes: template-based extraction for known layouts (fast path) and AI-based extraction for unseen layouts (adaptive path), allowing the system to adapt its behavior based on the document type while maintaining high processing throughput
Solution Approach 2:
The patent introduces an intermediary AI model layer that acts as a fallback mechanism when template-based extraction fails, enabling the system to handle unseen document layouts by routing to the AI model only when necessary, thus maintaining both speed and adaptability
3Adaptability or versatility
If AI systems are used for document extraction, then adaptability to various layouts is improved, but computational cost and energy consumption increase
Solution Approach 1:
The patent applies partial action by using AI-based extraction only for a subset of documents that require it (unseen layouts), rather than applying it universally to all documents, thereby reducing overall computational cost and energy consumption while maintaining high adaptability where needed
Solution Approach 2:
The patent uses lightweight template-based extraction rules for the majority of common document types, reserving expensive AI computational resources only for edge cases that cannot be handled by templates, effectively replacing expensive computational objects with cheap rule-based objects wherever possible
Data Source
AI summary
A system and method for secure and efficient automated workflows includes two complementary components. A digest embedding system verifies the integrity of workflow event sequences using a rolling SHA-256 digest salted with microsecond-precision timestamps. A template-caching extractor adaptively processes heterogeneous electronic documents. The digest system enables decentralized verification without querying centralized audit logs. The extractor uses a layout hash derived from document structure to route documents through either a low-latency, rule-based extraction path or a fallback artificial intelligence model path. New templates are generated for previously unseen layouts exceeding a confidence threshold. The disclosed methods improve latency, resource utilization, energy utilization and scalability in sectors including finance, healthcare, and logistics, offering advantages over existing prior art in terms of integration, specific mechanisms for timestamp salting, hardware security module utilization for workflow events, layout-based template caching, and adaptive learning.


