Machine Learning with Applications in Information Security,Second Edition,is a classroom-tested introduction to machine learning and deep learning algorithms and techniques,reinforced via realistic applications. It covers core classic machine learning topics in depth,including Hidden Markov Models (HMM),Support Vector Machines (SVM),and clustering,and advanced deep learning architectures.

Format: Hardback
Length: 534 pages
Publication date: 27 September 2022
Publisher: Taylor & Francis Ltd

Introduction to Machine Learning with Applications in Information Security, Second Edition

This comprehensive textbook offers a thorough introduction to machine learning and deep learning algorithms and techniques, reinforced through practical applications in the field of information security. Designed with accessibility in mind, it avoids the use of complex theorems and mathematical theory, focusing on presenting topics at an intuitive level with just enough detail to clarify the underlying concepts.

The book delves into core classic machine learning topics in great depth, encompassing Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. It also explores various advanced machine learning topics, such as k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). Furthermore, it comprehensively covers fundamental deep learning topics, including backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN). Additionally, the book presents a wide range of advanced deep learning architectures, such as Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec.

Moreover, the book discusses several cutting-edge deep learning topics, including dropout regularization, attention, explainability, and adversarial attacks. The examples provided throughout the text are drawn from the realm of information security, with a significant emphasis on malware analysis. These applications serve to demystify the topics by illustrating the practical use of various learning techniques in straightforward scenarios. While some exercises in the book require programming skills, it assumes a basic understanding of computing concepts.

Overall, Introduction to Machine Learning with Applications in Information Security, Second Edition is an invaluable resource for students, researchers, and professionals seeking to gain a deeper understanding of machine learning and its applications in information security. Its comprehensive coverage, practical examples, and accessible writing style make it an essential tool for anyone looking to advance their knowledge in this field.

Weight: 932g
Dimension: 164 x 240 x 36 (mm)
ISBN-13: 9781032204925
Edition number: 2 ed