Machine Learning in Cyber Trust Security, Privacy, and Reliability

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Synopsis

Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms.
This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover what types of learning methods are at their disposal, summarizing the state-of-the-practice in this significant area, and giving a classification of existing work.
Those working in the field of cyber-based systems, including industrial managers, researchers, engineers, and graduate and senior undergraduate students will find this an indispensable guide in creating systems resistant to and tolerant of cyber attacks.

Book details

Edition:
2009
Author:
Jeffrey J. P. Tsai, Philip S. Yu
ISBN:
9780387887357
Related ISBNs:
9780387887340
Publisher:
Springer US
Pages:
N/A
Reading age:
Not specified
Includes images:
No
Date of addition:
2021-02-10
Usage restrictions:
Copyright
Copyright date:
2009
Copyright by:
N/A 
Adult content:
No
Language:
English
Categories:
Computers and Internet, Nonfiction