Transforming Message Logs into Images for ML Analysis
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Solution Overview
Problem
Current methods for analyzing communication message logs require significant human intervention and are not suitable for machine-learning algorithms, as text logs fail to represent service primitives effectively.
Innovation Solution
A method and system that transform message logs into images by converting message content into decimal numbers, associating them with color values, and generating images, allowing for the use of machine-learning algorithms for pattern analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If message logs are analyzed using text-based machine-learning algorithms, then the analysis can be automated, but text logs are not suitable for representing service primitives effectively
Solution Approach 1:
The patent transforms message logs from text format to image format by converting service primitives into visual representations where different parameters (message type, direction, protocol layer) are encoded as distinct visual features such as color, shape, and position. This parameter transformation enables machine-learning algorithms to effectively process and analyze service primitives while maintaining full information fidelity.
2Measurement precision
If human experts manually analyze message logs, then detailed pattern recognition can be achieved, but significant human intervention and time are required
Solution Approach 1:
The patent creates visual copies of message log data in image format that preserve all essential patterns and relationships. These visual copies can be rapidly processed by machine-learning algorithms to achieve expert-level pattern recognition accuracy without requiring actual human intervention, thereby eliminating the time loss associated with manual analysis while maintaining measurement precision.
3Adaptability or versatility
If message logs are transformed into images, then machine-learning algorithms can be applied effectively, but additional transformation steps are required
Solution Approach 1:
The patent segments the message log transformation process into distinct, manageable components: extracting service primitive parameters, mapping parameters to visual features, generating image representations, and processing through machine-learning algorithms. This segmentation reduces overall complexity by making each step independent and well-defined, while enabling versatile application of various machine-learning algorithms to the generated images.
Data Source
AI summary
A method is provided for transforming message logs into images. The method comprises the step of receiving a message log comprising a plurality of messages. The method further comprises the step of selecting a content of at least one message. In addition, the method comprises the step of transforming the content block-wise into decimal numbers. Furthermore, the method comprises the step of associating each decimal number with a color value thereby translating each message into a sequence of symbols. Moreover, the method comprises the step of generating an image from the symbols of the plurality of messages.