ML-Based Malware Detection System - Data Labeling & Model Training
TextClassification
In this project, I implemented a signature-based matching technique in Python to enhance malware detection in software. I also integrated machine learning models to achieve a high accuracy rate in identifying and isolating potential threats. My work included designing an automated quarantine mode for improved system security.
• Labeled and classified text-based malware files using Python and ML models
• Used TensorFlow and PyTorch for model training and evaluation
• Focused on improving accuracy and reliability in threat detection
• Worked with real-world malware datasets for annotation and model fine-tuning.
In this project, I implemented a signature-based matching technique in Python to enhance malware detection in software. I also integrated machine learning models to achieve a high accuracy rate in identifying and isolating potential threats. My work included designing an automated quarantine mode for improved system security. • Labeled and classified text-based malware files using Python and ML models • Used TensorFlow and PyTorch for model training and evaluation • Focused on improving accuracy and reliability in threat detection • Worked with real-world malware datasets for annotation and model fine-tuning.
2021 - 2021