Codebook Filesystem Compression for Intrusion Detection
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Solution Overview
Problem
The rapid growth of data storage demand outstrips the capacity to store it, and existing data compression methods are inadequate for multimedia data, while intrusion detection systems are limited by reliance on signature libraries and vulnerable to new threats.
Innovation Solution
A system and method for filesystem data compression using codebooks that measure probability distributions for real-time intrusion detection, integrating compression into filesystems for per-file or filegroup basis, and utilizing statistical analysis to detect anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional data compression methods are used, then storage capacity is doubled, but compression effectiveness decreases substantially for multimedia data
Solution Approach 1:
The patent transforms the compression approach by changing from traditional compression algorithms to a probability distribution-based encoding system. The system measures probability distributions of data streams and uses statistical algorithms to encode data, fundamentally altering the compression parameters to achieve superior effectiveness for multimedia data while maintaining high storage capacity utilization.
Solution Approach 2:
The patent replaces traditional mechanical compression algorithms with a statistical measurement system. By substituting the compression mechanism with probability distribution analysis and statistical encoding, the system achieves both high compression effectiveness for multimedia and efficient storage capacity utilization, resolving the contradiction between quantity and productivity.
2Reliability
If signature libraries are used for intrusion detection, then known attacks are detected, but the system is vulnerable to new threats and requires frequent updates
Solution Approach 1:
The patent implements a self-updating intrusion detection system that automatically measures probability distributions of data streams and adapts to new threats without requiring manual signature library updates. The system uses statistical algorithms to autonomously detect both known and novel attacks, maintaining high reliability for known threats while achieving versatility for new threats through continuous adaptive learning.
Solution Approach 2:
The patent transforms the static signature library approach into a dynamic probability distribution measurement system. By continuously measuring and analyzing probability distributions of incoming data streams, the system adapts its detection capabilities in real-time, achieving both reliability for known attacks and versatility for new threats through dynamic statistical analysis rather than static pattern matching.
3Loss of information
If data is transmitted in uncompressed form, then data integrity is maintained, but bandwidth requirements increase tremendously
Solution Approach 1:
The patent changes the transmission parameter from traditional compression to probability distribution-based encoding. This encoding method achieves superior compression ratios for multimedia data while maintaining lossless data integrity through the mathematical properties of probability distribution measurement and statistical reconstruction, thereby reducing bandwidth requirements without sacrificing data完整性.
Solution Approach 2:
The patent creates a universal encoding system that simultaneously achieves data compression, integrity preservation, and efficient bandwidth utilization. The probability distribution-based approach serves multiple functions: it compresses multimedia data effectively, maintains lossless integrity through statistical reconstruction, and reduces bandwidth requirements, resolving the contradiction between information preservation and quantity reduction.
Data Source
AI summary
A system and method for filesystem data compression using codebooks, that measures in real-time the probability distribution of an encoded data stream, compares the probability distribution to a reference probability distribution, and uses one or more statistical algorithms to determine the divergence between the two sets of probability distributions to determine if an unusual distribution is the result of a data intrusion. The system comprises both encoding and decoding machines, an intrusion detection module, a codebook training module, and various databases which perform various analyses on encoded data streams. Further, the system comprises a system for integrating the compression into a filesystem for both system-wide compression on a per-file or filegroup basis, and intrusion or alteration detection of files.


