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Identifying and Correlating Anomalies in Internetwide Scan

Andrew Morris

Identifying and correlating anomalies in internet-wide network scan data using machine learning.

Summary

Network Scanning Scale

Internet-wide scanning generates massive datasets. Identifying meaningful anomalies in this data is challenging without machine learning approaches.

Anomaly Detection

The presentation covers techniques for identifying anomalies in scan data and correlating them across scans. Understanding patterns in global internet scans reveals infrastructure vulnerabilities.

Machine Learning Application

ML models trained on network scan data can identify unusual patterns, misconfigurations, and potentially vulnerable systems at scale.

Applications

Identifying anomalies in internet-wide scans enables discovery of vulnerable services and infrastructure before attackers do.

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