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MohamedMostafa010 / ExeRay

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ExeRay AI detects malicious Windows executables using ML. Analyzes entropy, imports, and metadata for rapid classification, aiding incident response. Built with Python and scikit-learn.

python machine-learning ai random-forest detection scikit-learn machine-learning-algorithms malware python3 executable artificial-intelligence xgboost machinelearning exe malicious random-forest-classifier gridsearchcv benign aimodel xgboost-classifier
  • Updated Mar 30, 2026
  • Python

Piyush-Sambyall / Network-Intrusion-Detection-System

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This ML-based Network Intrusion Detection System classifies traffic as Benign, DDoS, or Port-Scan. Powered by a Random Forest model and 22 OSI-layer features, it achieves 93% accuracy with a low 1.84% false-positive rate. The end-to-end pipeline includes synthetic dataset generation, automated preprocessing, model training, and deep evaluation.

machine-learning ddos deep-learning random-forest tensorflow scikit-learn pandas classification pyhton portscan cyber-security network-security nsl-kdd benign network-traffic-analysis cicids2017
  • Updated Jul 16, 2026
  • Python

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