Introduction to Machine Learning With Applications in Information - Securit

Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications.

List of contents

1. Preface
   About the Author
   
   
   
   1. What is Machine Learning?
   
   
   2. A Revealing Introduction to Hidden Markov Models
   
   
   3. Principles of Principal Component Analysis
   
   
   4. A Reassuring Introduction to Support Vector Machines
   
   
   5. A Comprehensible Collection of Clustering Concepts
   
   
   6. Many Mini Topics
   
   
   7. Deep Thoughts on Deep Learning
   
   
   8. Onward to Backpropagation
   
   
   9. A Deeper Diver into Deep Learning
   
   
   10. Alphabet Soup of Deep Learning Topics
   
   
   11. HMMs for Classic Cryptanalysis
   
   
   12. Image Spam Detection
   
   
   13. Image-Based Malware Analysis
   
   
   14. Malware Evolution Detection
   
   
   15. Experimental Design and Analysis
   
   
   16. Epilogue
   References
   Index
   

About the author

Mark Stamp is a Professor at San Jose State University, and the author of two textbooks, Information Security: Principles and Practice and Applied Cryptanalysis: Breaking Ciphers in the Real World. He previously worked at the National Security Agency (NSA) for seven years, which was followed by two years at a small Silicon Valley startup company.

Summary

Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications.

Product details

• Authors: Mark Stamp, Stamp Mark
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 27.09.2022
• EAN: 9781032204925
• ISBN: 978-1-0-3220492-5
• No. of pages: 534
• Series: Chapman & Hall/CRC Machine Learning & Pattern Recognition
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Social sciences, law, business > Business > General, dictionaries; machine learning, BUSINESS & ECONOMICS / Statistics, COMPUTERS / Security / General, COMPUTERS / Programming / Games, COMPUTERS / Machine Theory, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Data Science / Neural Networks