Network Infrastructure Analysis via Unified Data Lake Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Network analysts face challenges in efficiently gathering, processing, and analyzing data from disparate sources to identify changes in network infrastructure and threats, due to the need for manual querying, data standardization, and visualization of large datasets.
Innovation Solution
A system that aggregates network data from multiple sources into a central repository, processes it to remove duplicates, aligns formats, and generates an interactive graphical interface for visualizing network activity over time, allowing analysts to focus on threat analysis rather than data collection and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If analysts manually query multiple disparate data sources to gather network data, then comprehensive network infrastructure information can be obtained, but significant time is incurred for data collection and processing
Solution Approach 1:
The patent combines multiple disparate data sources (DNS records, WHOIS data, SSL certificates, vulnerability scans) into a single unified data lake. This consolidation allows analysts to query all network infrastructure information from one centralized location rather than manually querying each source separately, thereby maintaining comprehensive information coverage while dramatically reducing data collection time.
Solution Approach 2:
The system pre-processes and standardizes data from multiple sources before analysts need it, organizing information into consistent formats and relationships in advance. This preliminary organization of data eliminates the need for analysts to perform time-consuming data gathering and initial processing steps when conducting network infrastructure analysis.
2Loss of information
If data from multiple providers is gathered individually, then complete network data sets can be obtained, but the data requires extensive standardization and formatting work
Solution Approach 1:
The patent implements a universal data model that can accommodate multiple data types and formats from different providers through a common schema. This multi-functional framework automatically adapts to various input formats (DNS, WHOIS, SSL, vulnerability data) and standardizes them into a unified structure, eliminating manual formatting work while preserving complete data sets.
Solution Approach 2:
The system introduces an intermediary layer (the data lake with unified schema) between the disparate data sources and the analysis tools. This intermediary automatically handles data standardization and formatting transformations, serving as a mediator that converts multiple provider formats into a consistent structure without requiring manual intervention from analysts.
3Reliability
If analysts manually aggregate and reduce large data sets to identify trends, then network threats can be detected, but the process is time-consuming and limits analytical capacity
Solution Approach 1:
The system enables self-service analysis by providing analysts with direct access to pre-processed, organized data in the unified data lake. The data is automatically aggregated and structured in ways that facilitate trend identification and threat detection, allowing analysts to focus their expertise on interpretation rather than manual data processing, thereby maintaining reliability while increasing productivity.
Solution Approach 2:
The patent transforms the data analysis process by adding a temporal dimension through time-series visualization capabilities. This allows analysts to view network infrastructure changes and threats over time through graphical interfaces, enabling rapid pattern recognition and trend identification without manual aggregation, thus preserving detection reliability while enhancing analytical throughput.
4Loss of information
If detailed network data is visualized over time periods, then patterns and correlations can be identified, but the visualization complexity increases
Solution Approach 1:
The system addresses visualization complexity by introducing temporal and spatial dimensions through graphical time-series displays. Instead of presenting raw detailed data, the system projects network activity patterns across time periods in visual formats that naturally reveal correlations and trends, maintaining information completeness while reducing the perceived complexity through intuitive visualization.
Solution Approach 2:
The patent employs visual encoding techniques including color variations to represent different network activities, threat levels, and time periods. These color-coded visualizations enable analysts to quickly perceive patterns and correlations in network data without being overwhelmed by raw data complexity, as visual cues naturally organize and highlight important relationships.
Data Source
AI summary
Some embodiments are directed to techniques for infrastructure analysis of Internet-based activity. Techniques are disclosed to enable analysts to spend more time focusing on analyzing and identifying threats to in a network infrastructure, and little time on data collection and data processing. Specifically, techniques are described for identifying network data relevant to Internet activity and providing an interactive interface (e.g., a “heat map” interface) for viewing and interactive analysis of the network data. The network data may be identified for assessing Internet activity with respect to one or more attributes, such as an Internet domain name or an Internet protocol (IP) address.