Thesis project. A hybrid AI system using CNN and SVM architectures for real-time alcohol detection through facial biometric analysis. Trained on a custom 24K image dataset.

Security-focused ML API for phishing detection. Features NLP-based classification optimized with ONNX for inference, integrated with a Flask backend and SQLite/SQLAlchemy for persistence.

Mobile security application designed to identify malicious URLs. Integrates a Python/TensorFlow NLP model with an Android-based frontend for real-time link analysis.

Threat intelligence platform categorizing web links using an ensemble of Scikit-Learn classifiers. Features a Streamlit interface for live URL safety verification.

ML-based security tool for detecting SQL injection payloads. Utilizes NLP techniques and Scikit-Learn to identify malicious query patterns in real-time web requests.

High-precision classification system for electronic communication. Employs Scikit-Learn and NLP pipelines to filtered unwanted content with high accuracy.

Continuous monitoring system designed to identify suspicious network patterns. Leverages ML models to flag potential security breaches and unusual traffic behavior.

Intelligent system for detecting fraudulent transactions and activities. Uses advanced classification algorithms to minimize false positives in financial security.

NLP-powered tool designed to verify the authenticity of news articles. Employs text analysis and ML models to distinguish between credible and misinformative content.

Vision-based security system focused on facial safety and verification. Utilizes deep learning to provide robust performance in dynamic environment.

Secure token-based authentication framework. Implements bcrypt password hashing, session management, and protected API routes using Flask and SQLAlchemy.

A comprehensive guide and resource list for aspiring cybersecurity professionals. Covers foundational skills to advanced security engineering paths.