Phishing Detection Using Content-Based Image Classification

Phishing Detection Using Content-Based Image Classification is a valuable resource for professionals and scholars using Deep Learning and Computer Vision to solve cybersecurity tasks. It provides a step-by-step approach to solving the problem with significant accuracy, covering topics such as image data manipulation, feature extraction, and Deep Learning models. The book also includes a reproducible code base for further enhancement.

Format: Hardback
Length: 130 pages
Publication date: 02 June 2022
Publisher: Taylor & Francis Ltd

Phishing Detection Using Content-Based Image Classification is a vital resource for deep learning and cybersecurity professionals seeking to address diverse cybersecurity challenges utilizing cutting-edge technologies like Deep Learning and Computer Vision. The prevalence of rule-based phishing detection techniques, which can be circumvented by phishers, necessitates a comprehensive approach. This book offers a step-by-step solution using Computer Vision and Deep Learning techniques, achieving significant accuracy.

The book encompasses a wide range of essential topics, including:

• Programmatically reading and manipulating image data.
• Extracting relevant features from images.
• Building statistical models using image features.
• Employing state-of-the-art Deep Learning models for feature extraction.
• Developing a robust phishing detection tool with limited data.
• Dimensionality reduction techniques.
• Class imbalance treatment.
• Feature Fusion techniques.
• Building performance metrics for multi-class classification tasks.

Moreover, this book stands out for its fully reproducible code base, developed by the author and made available through python notebooks. This facilitates quick launch and running capabilities, enabling users to further enhance the provided models with advancements in computer vision and more advanced algorithms.

Weight: 400g
Dimension: 216 x 138 (mm)
ISBN-13: 9781032108537