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Uncovering Hidden Domain Registration Clusters with AI/ML Every day, thousands of domains are registered—but not all registrations follow the same organic pattern. These domain registration clusters are nearly impossible to detect manually. That’s where AI and machine learning come in. At #whoisxmlapi, we leveraged AI-powered pattern recognition to analyze years of domain registration data. Here’s how we cracked the code: Identifying Anomalies in the Noise By examining registration data over time, our AI models uncovered spikes—clusters of domain purchases happening within narrow timeframes, often from the same sources or with similar naming conventions. As you can see from this graph, there's something going on! Possibly government sponsored? Machine Learning for Pattern Recognition Our models didn’t just find spikes; they categorized them. Whether it was marketing-driven bulk buys, new industry trends, or less benign activities (like phishing networks), AI allowed us to fingerprint these high-volume registrations with precision. From Insight to Action Understanding the “why” behind these clusters is just as important as finding them. By layering in additional intelligence, we can distinguish legitimate domain expansions from potential threats, helping cybersecurity teams, brand protection specialists, and researchers stay ahead of the curve. The digital landscape is constantly shifting, but AI gives us a new way to see the patterns others miss. #AI #MachineLearning #Cybersecurity #DomainAnalysis #ThreatIntelligence #DataScience #InternetResearch