Project
Intrusion detection system
Project work
Developed a deep learning intrusion detection system trained from scratch to identify and categorize network intrusions. Architectures compared include MLP, CNN, and transformer-based sequence models, optimized for imbalanced traffic data, with preprocessing, statistical feature engineering, and visualization. This is project work and is not listed as a journal publication on the CV.
The CV reports 89% detection accuracy for this system. No matching journal paper is listed on the CV.
Tech Python · TensorFlow · Pandas · Scikit-learn · Matplotlib · Jupyter Notebooks