Introduction to Machine Learning with Applications in Information Security

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.

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.

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