Project Overview:
Developed a deep learning model using Convolutional Neural Networks (CNN) to predict and detect SQL Injection attacks in SQL queries. The project involved pre-processing textual data, extracting features with CountVectorizer, and training a CNN model. The model was evaluated using accuracy, precision, and recall metrics, achieving high performance (accuracy: 97.26%, precision: 91.94%, recall: 99.60%). The model was then deployed to predict SQL Injection attempts in real-time SQL queries.
Key Skills:
Deep Learning (CNN) Text Preprocessing and Feature Extraction Model Evaluation (Accuracy, Precision, Recall) SQL Injection Detection.