Evaluating ML-Based Anomaly Detection Across Datasets of Varied Integrity: A Case Study

Cybersecurity remains a critical challenge in the digital age, with network traffic flow anomaly detection being a key pivotal instrument in the fight against cyber threats. In this study, we address the prevalent issue of data integrity in network traffic datasets, which are instrumental in developing machine learning (ML) models for anomaly detection. We introduce two refined versions of the CICIDS-2017 dataset, NFS-2023-nTE and NFS-2023-TE, processed using NFStream to ensure methodologically sound flow expiration and labeling. Our research contrasts the …

age anomaly anomaly detection case case study challenge cs.lg cs.ni cyber cybersecurity data data integrity datasets detection digital digital age fight flow issue key machine machine learning network pivotal study threats traffic