Adaptive Compression-Encryption Pipeline for Data Drift Resilience

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Solution Overview

Problem

The rapid growth of data storage demand outstrips the capacity to store it, and existing data compression and encryption methods are inadequate, especially with the rise of multimedia data and quantum computing threats.

Innovation Solution

An adaptive data processing system that combines compression and encryption, dynamically selects processing techniques based on data characteristics, and includes a feedback loop for continuous monitoring and retraining to adapt to changing data distributions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If traditional data compression methods are used, then storage capacity is improved, but data security deteriorates due to inadequate protection against quantum computing threats

Engineering Contradiction:

Improvestorage capacityVSAvoiddata security

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The patent combines compression and encryption into a single integrated processing pipeline. The compression engine and encryption engine work sequentially to simultaneously reduce data size and secure data, resolving the contradiction between storage efficiency and security protection.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The system dynamically selects processing techniques based on data characteristics. The dynamic technique selection module analyzes input data properties and adjusts compression and encryption parameters in real-time, allowing the system to adapt to different data types and threat levels.

Inventive Principle:

Principle #15Dynamics

2Productivity

If data is transformed into dyadic distributions, then compression efficiency is improved, but processing complexity increases

Engineering Contradiction:

Improvecompression efficiencyVSAvoidprocessing complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs preliminary analysis of data characteristics before applying compression transformations. The dynamic technique selection module pre-determines the appropriate dyadic transformation approach based on data properties, simplifying the subsequent processing steps.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The compression engine automatically adapts to different data types through self-adjusting parameters. The system monitors processing results and autonomously optimizes transformation depth and encoding strategies without external intervention.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If dynamic technique selection is implemented, then adaptability to different data types is improved, but system complexity increases

Engineering Contradiction:

Improveadaptability to data characteristicsVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system divides the processing pipeline into distinct modular components: analysis module, technique selection module, compression engine, and encryption engine. Each module has a specific function, making the complex system manageable and maintainable while preserving adaptability.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The dynamic technique selection module serves multiple functions: it analyzes data characteristics, selects appropriate compression algorithms, determines encryption parameters, and monitors processing performance. This multi-functionality reduces overall system complexity despite the need for adaptability.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Productivity

If feedback-driven optimization is used, then system performance is improved, but computational overhead increases

Engineering Contradiction:

Improvesystem performanceVSAvoidcomputational overhead

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The feedback loop operates periodically rather than continuously. The system monitors processing results at intervals and adjusts parameters accordingly, reducing computational overhead while maintaining performance optimization benefits.

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The system implements feedback mechanisms that monitor compression ratios, encryption performance, and processing speed. This feedback drives adaptive parameter adjustment to optimize performance while avoiding excessive computational overhead through intelligent threshold-based adjustments.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12395185B2Adaptive data processing system with dynamic technique selection and feedback- driven optimization

Publication Date: 2025.08.19 ATOMBEAM TECH INC

AI summary

A system and method for adaptive data processing combining compression and encryption. The system analyzes input data characteristics, compares probability distributions, and creates a transformation matrix to convert data into a dyadic distribution. It generates a main data stream of transformed data and a secondary stream of transformation information. The system dynamically selects and applies processing techniques, including transformation, encoding, compression, and encryption algorithms, based on analyzed characteristics and real-time performance metrics. It compresses the main data stream using Huffman coding and implements security measures to protect the output. A feedback loop monitors technique effectiveness, updates a knowledge base, and influences future selections. The system can operate in lossless, lossy, or modified lossless modes, adapting to different application requirements. This approach offers an efficient solution for scenarios where both data reduction and security are critical concerns.