The last decade has experienced a steady growth in the number of reported security breaches due to viruses, ransomwares, etc. Given that and taking into consideration the tremendous success Machine Learning (ML) and Deep Learning (DL) have demonstrated in many different areas, a series of work have been conduced on learning-based security systems such as vulnerability discovery, malware and intrusion detection. However, applying ML or AI blindly could bring a lot of damages to your business if not done properly. In fact, cybersecurity has a lot of particularities and many factors must be considered.
In this concise volume, we will delve into ML and DL, unpacking the underlying mathematical complexities. We'll go through a variety of models including but not limited to Word2Vec, Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Transformers, and Attention mechanism. We will also be shedding light on the sophisticated architecture of Generative Pre-trained Transformers (GPT) among other significant topics.
This book will continuously be updated with latest findings and updates.
