Traffic Log Extraction Using Adaptive Regular Expressions

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Solution Overview

Problem

Existing systems face challenges in efficiently extracting and analyzing data from network traffic logs using regular expressions, particularly in determining the type of data to extract, direction of traffic, and optimizing regular expressions for maximum data extraction.

Innovation Solution

A system utilizing a regular expression based log data extraction system that includes a log collector, regular expressions datastore, log data extraction characterization system, log parsing system, and data extraction system to collect, characterize, parse, and extract data from network traffic logs, dynamically updating and optimizing regular expressions for improved data extraction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional log parsing methods are used, then the system is simple to implement, but the data extraction efficiency and accuracy are insufficient

Engineering Contradiction:

Improvedata extraction efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system incorporates a feedback mechanism where extracted data is used to refine and optimize regular expressions dynamically. The characterization system analyzes extraction results and feeds back into the regular expression generation, creating an iterative improvement loop that enhances data extraction efficiency over time while managing system complexity through automated optimization.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs self-optimization by automatically generating and refining regular expressions based on the log data characteristics. The characterization system analyzes the logs and adjusts the extraction patterns independently, allowing the system to improve its own performance without external intervention, thereby increasing productivity while containing complexity through self-managed optimization.

Inventive Principle:

Principle #25Self-service

2Quantity of substance

If comprehensive data extraction is performed, then the quantity of extracted data increases, but the time required for processing increases

Engineering Contradiction:

Improveamount of extracted dataVSAvoidprocessing time

Core Design Contradiction:

Quantity of substanceVSLoss of time

Solution Approach 1:

The system applies different extraction strategies to different parts of the log data based on their characteristics. The characterization system identifies specific patterns and fields within the logs and applies targeted regular expressions to extract relevant data efficiently, rather than applying a uniform extraction approach to entire logs, thereby increasing the quantity of extracted data while minimizing processing time through localized optimization.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system performs preliminary characterization of the log data to understand its structure and patterns before executing the full extraction process. By analyzing and categorizing the log formats in advance, the system can pre-compile optimized regular expressions and extraction parameters, enabling faster processing and increasing the amount of data extracted without proportionally increasing processing time.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If fixed regular expressions are used, then the system is easy to operate, but it cannot adapt to different log types and traffic directions

Engineering Contradiction:

Improveadaptability to different log typesVSAvoidsystem operation simplicity

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system transitions from static, fixed regular expressions to dynamic, adaptive extraction patterns. The characterization system continuously analyzes log data and automatically adjusts the regular expressions to match different log types and traffic directions. This dynamic adaptation allows the system to handle diverse log formats without requiring manual reconfiguration, thereby enhancing versatility while maintaining ease of operation through automated adjustment.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system creates a universal extraction framework that can handle multiple log types and traffic directions through a single integrated platform. The characterization system enables the same system to adapt its extraction patterns for different scenarios, making it multi-functional and versatile. This universality is achieved through automated pattern recognition and regular expression generation, allowing the system to operate simply while adapting to various log formats and traffic characteristics.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12602383B2Normalization and extraction of log data

Publication Date: 2026.04.14 THREATSTOP

AI summary

Extracting data from traffic logs using regular expressions. A traffic log is received from a network device. A characterization of an extraction of data from the traffic log is determined. The traffic log is parsed by applying a first regular expression to the traffic log according to the characterization of the extraction of data from the traffic log to generate parsed data. Data is extracted from the traffic log by applying a second regular expression to the parsed data according to the characterization of the extraction of data from the traffic log to generate extracted data.