cyber-threat-detection

Cyber threat detection using machine learning is a proactive approach to cybersecurity that involves training machine learning algorithms. Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

A Windows-based USB Threat Monitoring Tool developed to detect and monitor malicious USB activities.

Behavioral anomaly detection in synthetic enterprise security logs using unsupervised ML, adversarial attack simulation, and feature engineering

RAG-grounded SOC alert triage: Wazuh alerts classified via deterministic MITRE ATT&CK/CAPEC/CWE/CVE retrieval, calibrated confidence scoring, and automated NIST-compliant incident reporting. FastAPI + ChromaDB + PostgreSQL + React + Gemini 3.5 Flash Lite.

A Python and Machine Learning based system that detects potential cyber threats by analyzing suspicious activities and classifying them based on their risk level.

AI and NLP-based cybersecurity threat intelligence system that analyses social media data, detects relevant threats, classifies threat categories, and provides explainable insights through automated analysis.