Introduction to Machine Learning With Applications in Information - Securit

List of contents

Introduction. I TOOLS OF THE TRADE. A Revealing Introduction to Hidden Markov Models. A Full Frontal View of Profile Hidden Markov Models. Principal Components of Principal. Component Analysis. A Reassuring Introduction to Support Vector Machines. A Comprehensible Collection of Clustering Concepts. Many Mini Topics. Data Analysis. II APPLICATIONS. HMM Applications. PHMM Applications. PCA Applications. SVM Applications. Clustering Applications

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.

Summary

This class-tested textbook will provide in-depth coverage of the fundamentals of machine learning, with an exploration of applications in information security. The book will cover malware detection, cryptography, and intrusion detection. The book will be relevant for students in machine learning and computer security courses.

Product details

• Authors: Mark Stamp, Mark (Department of Computer Science Stamp
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 30.06.2020
• EAN: 9780367573058
• ISBN: 978-0-367-57305-8
• No. of pages: 364
• Series: Chapman & Hall/CRC Machine Learning & Pattern Recognition
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics