Automatic Parser Generation for Diverse Log Formats
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Solution Overview
Problem
Analyzing data from computer networks for security and compliance purposes is difficult and expensive due to the need for corresponding parsers, which are often inadequate for varying and new log formats emitted by diverse devices.
Innovation Solution
A data collection and analysis platform that automatically selects and generates parsers based on received data, using a library of parser rules and regular expressions to identify patterns and structure in log data, and supports obfuscation of sensitive information for secure analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual parser deployment is used for each device type, then parsing accuracy is improved, but device complexity and operational difficulty increase significantly
Solution Approach 1:
The system enables automatic parser generation by analyzing log data patterns and generating corresponding parsers without manual intervention. The parser generator automatically detects data formats, creates parsing rules, and deploys parsers based on received log data, eliminating the need for manual parser deployment while maintaining high parsing accuracy
Solution Approach 2:
The system dynamically adjusts parser parameters and generation strategies based on the specific characteristics of received log data. By analyzing data patterns, device types, and format variations, the system automatically modifies parsing parameters to optimize accuracy for each specific data source
2Measurement precision
If parsers are manually configured for diverse log formats, then data interpretation accuracy is improved, but time consumption and operational cost increase
Solution Approach 1:
The system performs preliminary actions by pre-generating parsers based on analyzed log data patterns before actual data processing begins. The automatic parser generation creates ready-to-use parsers in advance, eliminating the need for time-consuming manual configuration when new data sources are encountered
Solution Approach 2:
The parser generator automatically detects log data formats, analyzes patterns, and generates appropriate parsers without human intervention. This self-service capability eliminates manual parser configuration time while maintaining accurate data interpretation through automated format detection and rule generation
3Adaptability or versatility
If comprehensive parser library is maintained for all device types, then adaptability to new formats is improved, but system complexity and maintenance burden increase
Solution Approach 1:
The system implements a universal parser generation mechanism that can handle diverse log formats through a single automated system. Instead of maintaining separate parsers for each device type, the parser generator analyzes incoming log data and automatically generates appropriate parsers, providing universal adaptability without proportionally increasing system complexity
Solution Approach 2:
The automatic parser generation system continuously learns from received log data and self-updates its parsing capabilities. By analyzing new data formats and generating corresponding parsers autonomously, the system maintains high adaptability to new device types without requiring manual library updates or increasing maintenance burden
Data Source
AI summary
Automatically generating a parser is disclosed. Raw data is received from a first remote device. A determination that the raw data does not, within a predefined confidence measure, conform to any rules included in a set of rules is made. A clustering function is performed on the raw data. At least one parser rule is generated based on the clustering.