Asynchronous URL Analysis for Spam Detection in Live Messaging
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Solution Overview
Problem
Traditional anti-spam techniques are ineffective against very short spam messages from semi-legitimate sources, especially those using URL shortening services, as they often lack sufficient content for analysis and result in high false positives and delayed message processing.
Innovation Solution
A method and system for asynchronous analysis of URLs in messages, which identifies and prioritizes URLs for expedited analysis, utilizing URL block lists and non-URL-based anti-spam analysis, and includes a URL analysis process that examines the contents of linked websites to determine spam status, thereby reducing delays and improving detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional URL-based spam signatures are used, then spam blocking is effective for constant spam messages, but they become ineffective against very short spam messages with shortened URLs that are used only once or in very few messages
Solution Approach 1:
The system performs preliminary analysis of messages during the submission phase by extracting and analyzing URLs before the message is fully processed. This allows the system to identify spam URLs in advance and block them before they reach users, rather than waiting for traditional signature-based detection after spam has been distributed.
Solution Approach 2:
The spam detection process is segmented into separate phases: initial URL extraction and analysis during message submission, followed by asynchronous continued analysis. This segmentation allows the system to handle URL analysis independently from other message processing tasks, improving both speed and accuracy of spam detection.
2Measurement precision
If comprehensive URL analysis is performed synchronously in the live message processing stream, then spam detection accuracy is improved, but message processing delays increase
Solution Approach 1:
URL analysis is initiated as a preliminary asynchronous task during message submission rather than blocking the main processing stream. This allows the system to start comprehensive URL analysis immediately while the message continues processing in parallel, eliminating delays without sacrificing detection accuracy.
Solution Approach 2:
The URL analysis process continues asynchronously throughout the message processing lifecycle rather than being a single synchronous step. The system maintains continuous analysis of URLs even after initial message processing, ensuring comprehensive detection while keeping the main message stream flowing without interruptions.
3Reliability
If all messages are analyzed in real-time with complete URL analysis, then spam detection reliability is improved, but system resource consumption increases
Solution Approach 1:
The system applies different levels of analysis intensity to different messages based on their characteristics. Messages with shortened URLs, suspicious patterns, or from unverified senders receive more intensive asynchronous URL analysis, while clearly legitimate messages receive minimal processing. This localized quality approach ensures high detection reliability for suspicious messages while conserving resources on obvious legitimate traffic.
Solution Approach 2:
The system performs partial URL analysis initially during message submission, then continues with more intensive analysis asynchronously only for messages that show spam indicators. This partial action approach provides sufficient detection capability for most messages while reserving full resource-intensive analysis for only those cases where it is truly needed.
Data Source
AI summary
A method and apparatus for asynchronous analysis of URLs in messages in a live message processing environment whereby an identified URL included in a message identified for further analysis is extracted and prioritized based on one or more prioritization parameters. The URL is then sent from a live message processing stream to a URL analysis process and the live message processing stream is stalled, with respect to that message, until the results of the URL analysis process are received, or until a defined “timeout” period passes. The results, or “verdict”, of the URL analysis process are then sent back to the live message processing stream in an asynchronous manner based on the prioritization of the URL. If the results of the URL analysis process are not received by the live message processing stream before the defined “timeout” period passes, then the “best” action is taken based on the best available data/verdict. If the results of the URL analysis process are received by the live message processing stream before the defined “timeout” period passes, then the “best” action is taken based on the verdict provided by the URL analysis process.