Phishing Detection Using Content-Based Image Classification is an invaluable resource for any deep learning and cybersecurity professional and scholar trying to solve various cybersecurity tasks using new age technologies like Deep Learning and Computer Vision. With various rule-based phishing detection techniques at play which can be bypassed by phishers, this book provides a step-by-step approach to solve this problem using Computer Vision and Deep Learning techniques with significant accuracy.

The book offers comprehensive coverage of the most essential topics, including:






Programmatically reading and manipulating image data



Extracting relevant features from images



Building statistical models using image features



Using state-of-the-art Deep Learning models for feature extraction



Build a robust phishing detection tool even with less data



Dimensionality reduction techniques



Class imbalance treatment



Feature Fusion techniques



Building performance metrics for multi-class classification task

Another unique aspect of this book is it comes with a completely reproducible code base developed by the author and shared via python notebooks for quick launch and running capabilities. They can be leveraged for further enhancing the provided models using new advancement in the field of computer vision and more advanced algorithms.