Introduction to Machine Learning with Applications in Information Security

Auteur

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.

Texte du rabat

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.

Contenu

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