Malicious Website Lifespan Prediction for Priority Blocklisting
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Solution Overview
Problem
The high number of malicious websites and the increasing operational costs and personnel dependency associated with constructing blocklists and watchlists make it impractical to monitor and block all sites, with existing technologies lacking the ability to predict the lifespan of malicious websites.
Innovation Solution
A malicious website lifespan prediction system that includes a communication device, storage device, and arithmetic logic unit to observe events at malicious websites, apply decision rules to predict lifespan, and generate blocklists or watchlists based on this prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all malicious websites are blocked or observed, then security coverage is improved, but operational costs and personnel dependency increase significantly
Solution Approach 1:
The patent segments the malicious website population into different priority groups based on predicted lifespan. Instead of treating all malicious websites uniformly, the system divides them into high-priority (long-lived) and low-priority (short-lived) categories, enabling selective blocking and monitoring strategies that reduce operational complexity while maintaining security coverage.
Solution Approach 2:
The system performs preliminary action by predicting the lifespan of malicious websites before blocking or monitoring them. By analyzing domain registration patterns, historical data, and other indicators in advance, the system pre-classifies websites into priority groups, allowing operators to focus resources on high-priority targets without manual assessment of each website.
2Measurement precision
If manual construction of blocklists and watchlists is performed, then selection accuracy is improved, but personnel dependency and operational costs increase
Solution Approach 1:
The system implements self-service by automatically constructing and updating blocklists and watchlists without requiring manual personnel intervention. The lifespan prediction algorithm autonomously analyzes malicious website characteristics, predicts their operational duration, and generates priority-based lists that can be directly deployed for blocking and monitoring, eliminating the need for manual curation while maintaining high selection accuracy.
Solution Approach 2:
The system changes the parameter of list construction from manual expert judgment to automated algorithmic prediction based on lifespan parameters. By transforming the selection criterion into a quantifiable metric (predicted lifespan), the system enables automatic generation of accurate blocklists and watchlists without personnel dependency.
3Productivity
If the blocklist and watchlist are updated frequently to capture new malicious websites, then detection capability is improved, but operational costs increase
Solution Approach 1:
The system applies periodic action by updating blocklists and watchlists based on predicted lifespan cycles rather than continuous manual updates. Websites are re-evaluated and lists are refreshed at intervals appropriate to their predicted operational duration, reducing unnecessary update operations while maintaining detection capability for actively malicious sites.
Data Source
AI summary
A malicious website lifespan prediction system includes a communication device that accesses a network, a storage device that stores information on malicious websites, and an arithmetic logic unit that observes predetermined events at the malicious websites, applies results of the observation to a decision rule defining a relationship between a tendency related to the predetermined event at the malicious website and a lifespan of the malicious website to predict the lifespan of the malicious website, and selects predetermined malicious websites from among the malicious websites according to the lifespan and generates a blocklist or a watchlist.