Internet Endpoint Profiling via Search Engine Semantic Analysis
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Solution Overview
Problem
Current methods for profiling Internet endpoints at a global scale are hindered by the inapplicability of state-of-art packet-level traffic classification tools due to access and processing power issues, despite vast amounts of publicly available information about endpoint behaviors.
Innovation Solution
A method utilizing an Internet search engine to generate profiling rules by inputting Internet endpoint identifiers, ranking phrases from search results, and classifying endpoints based on semantic URL classes and IP tags, without requiring network traffic traces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If packet-level traffic classification tools are used for profiling Internet endpoints, then measurement precision can be improved, but device complexity and processing power requirements become prohibitive for global scale analysis
Solution Approach 1:
The patent extracts only the necessary information elements from network traffic - specifically source/destination IP addresses and port numbers - rather than analyzing complete packet-level data. This extraction approach maintains profiling accuracy while dramatically reducing processing complexity and resource requirements, enabling global scale endpoint characterization.
Solution Approach 2:
The patent segments the endpoint profiling task into distinct functional components: data collection from network traces, IP address normalization, endpoint classification, and result aggregation. This segmentation allows each component to be optimized independently and processed in parallel, reducing overall system complexity while maintaining measurement precision.
2Quantity of substance
If network traffic traces are collected at global scale, then quantity of information available for profiling increases, but access issues and processing power requirements make it inapplicable
Solution Approach 1:
The patent performs preliminary actions by pre-collecting and storing network trace data in a standardized format before profiling analysis. IP addresses are normalized and endpoint characteristics are pre-computed, allowing subsequent profiling queries to execute efficiently without reprocessing raw traffic data, thus handling large volumes at global scale.
Solution Approach 2:
The patent creates simplified copies of network traffic data - specifically extracting only IP address and port information from complete packet traces - and stores these copies for profiling analysis. This copying approach enables efficient processing of global scale data volumes while maintaining the essential information needed for endpoint characterization.
3Productivity
If publicly available information about endpoint behaviors is systematically utilized, then productivity of endpoint profiling improves, but measurement precision may be compromised without network traffic traces
Solution Approach 1:
The patent introduces search engines as intermediaries to bridge publicly available information and endpoint profiling needs. By querying search engines with IP addresses and analyzing the structure and content of returned web pages, the system extracts meaningful endpoint characteristics without direct access to network traffic, maintaining both productivity and measurement precision.
Solution Approach 2:
The patent transitions from analyzing network traffic data (one dimension) to analyzing web page content and structure (another dimension). By examining HTML content, page titles, and document characteristics from search engine results, the system achieves accurate endpoint classification through a different informational dimension that is equally valuable for profiling.
Data Source
AI summary
The present invention relates to a method of profiling an Internet endpoint associated with an Internet Protocol (IP) address, an IP prefix, or a domain name, the method includes generating a profiling rule using an Internet search engine, obtaining a search result by inputting the IP address, the IP prefix, or the domain name to the Internet search engine, and classifying the Internet endpoint based on the search result using the profiling rule.