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2019 | OriginalPaper | Chapter

An Empirical Study on Performance Server Analysis and URL Phishing Prevention to Improve System Management Through Machine Learning

Authors : Antonio J. Tallón-Ballesteros, Simon James Fong, Raymond Kwok-Kay Wong

Published in: Economics of Grids, Clouds, Systems, and Services

Publisher: Springer International Publishing

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Abstract

This paper tackles some important matters such as the server performance and the URL phishing. Nowadays the system management is a crucial issue and any potential failure needs to be detected quickly and, at the same time, to avoid URL phishing via defining rules in the firewall setting. An empirical study through data mining is conducted covering different prediction techniques. Lastly, some guidelines are provided to emit a critical view about what may happen and how to act immediately.

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previous chapter Secure Query Processing over Encrypted Data Using a Distributed Index Structure for Outsourcing Sensitive Data
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Metadata
Title
An Empirical Study on Performance Server Analysis and URL Phishing Prevention to Improve System Management Through Machine Learning
Authors
Antonio J. Tallón-Ballesteros
Simon James Fong
Raymond Kwok-Kay Wong
Copyright Year
2019
Book
Economics of Grids, Clouds, Systems, and Services

Print ISBN: 978-3-030-13341-2

Electronic ISBN: 978-3-030-13342-9

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-13342-9_17

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