"Machine Learning and Data Mining for Computer Security"
provides an overview of the current state of research in machine
learning and data mining as it applies to problems in computer
security. This book has a strong focus on information processing
and combines and extends results from computer security.
The first part of the book surveys the data sources, the
learning and mining methods, evaluation methodologies, and past
work relevant for computer security. The second part of the book
consists of articles written by the top researchers working in this
area. These articles deals with topics of host-based intrusion
detection through the analysis of audit trails, of command
sequences and of system calls as well as network intrusion
detection through the analysis of TCP packets and the detection of
malicious executables.
This book fills the great need for a book that collects and
frames work on developing and applying methods from machine
learning and data mining to problems in computer security.
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