Encoded Data Stream Analysis for Compression-Based 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 and intrusion detection systems are inadequate due to reliance on signature libraries, vulnerability to protocol attacks, and inefficiencies in processing encrypted packets.
Innovation Solution
A system and method for data compression with intrusion detection that measures the probability distribution of encoded data streams, compares it to a reference distribution, and uses statistical algorithms to detect anomalies, independent of signature libraries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is used to increase storage capacity, then storage efficiency improves, but intrusion detection capability deteriorates
Solution Approach 1:
The patent combines data compression and intrusion detection into a single unified system. The compression algorithm simultaneously reduces data size and extracts statistical features for security analysis, eliminating the need for separate processing pipelines and enabling both functions to reinforce each other.
Solution Approach 2:
The compression system performs multiple functions: it compresses data for efficient storage, detects intrusions through statistical analysis, and adapts to new threats dynamically. This multi-functional approach replaces traditional systems that required separate compression and security tools.
2Measurement precision
If signature-based intrusion detection is used, then detection accuracy improves for known threats, but system vulnerability worsens to new and unknown threats
Solution Approach 1:
The system dynamically adapts its detection parameters based on real-time statistical analysis of data flows. Instead of relying on static signature libraries, the compression algorithm continuously learns normal traffic patterns and automatically adjusts to detect deviations, enabling effective detection of both known and emerging threats.
Solution Approach 2:
The system performs preliminary statistical characterization of normal data patterns during the compression process. By establishing baseline probability distributions in advance, the system is prepared to quickly detect anomalies without waiting for signature updates, providing immediate protection against new threats.
3Reliability
If probability distribution analysis is performed on encoded data streams, then intrusion detection effectiveness improves, but processing complexity increases
Solution Approach 1:
The patent merges probability distribution analysis with the data compression process itself. Statistical features are extracted during encoding rather than as a separate post-processing step, reducing overall system complexity while maintaining high detection effectiveness.
Data Source
AI summary
Data compression with intrusion detection, 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.