Behavioral Pattern Analysis and Anomaly Detection in Enterprise Network Connection Logs Using Unsupervised Machine Learning Methods
Abstract
This dataset comprises enterprise network connection logs collected from operational monitoring systems and used to study behavioral patterns and anomalous activities. Each record represents an individual network connection event, capturing temporal information, source and destination addresses, port usage, associated services, and traffic length characteristics. The dataset supports the evaluation of unsupervised machine learning methods for network behavior modeling and anomaly detection, as reported in the associated study.
Fields of Study & Subjects
Network Security and Intrusion Detection
Internet Traffic Analysis and Secure E-voting
Software System Performance and Reliability
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 12 January 2026
- Language
- EN
- Document type
- Dataset