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A 5.5 KB Excel dataset presents results from a unified framework for evaluating machine learning-based Intrusion Detection Systems (IDS). The framework harmonizes features from the NSL-KDD and CICIDS2017 datasets and benchmarks models including Random Forest, which achieved 98.0% accuracy and 97.0% F1-score. Authored by Shailendra Mishra and last updated on April 20, 2026, this work focuses on reproducibility and statistical validation in cybersecurity research.
Data is provided in XLS format, which may require specific software to open.