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Monitoring Air Pollutants Using Wireless Sensor Networks Read chapter Read first chapter

2020 | OriginalPaper | Chapter

A Study: Machine Learning and Deep Learning Approaches for Intrusion Detection System

Authors : C. H. Sekhar, K. Venkata Rao

Published in: Second International Conference on Computer Networks and Communication Technologies

Publisher: Springer International Publishing

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Abstract

System security is one of the real worries of the difficult time. With the fast advancement and monstrous utilization of web over the previous decade, the vulnerabilities of system security have turned into an important issue. Interruption identification framework is utilized to distinguish unapproved get to and uncommon assaults over the verified systems. High volume, assortment and fast of information produced in the system have made the information examination procedure to identify assaults by conventional strategies extremely troublesome. To comprehend the present status of usage of Machine and Deep learning methods for tackling the interruption recognition issues, this study paper listing out the related examinations in the continuous period focusing. This overview paper gives the various models of the detection system and briefly on Machine and Deep learning algorithms.

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previous chapter Identity Based Reliable Data Sharing with Revoked System in Cloud
next chapter Systematic Literature Survey on IDS Based on Data Mining
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Metadata
Title
A Study: Machine Learning and Deep Learning Approaches for Intrusion Detection System
Authors
C. H. Sekhar
K. Venkata Rao
Copyright Year
2020
Book
Second International Conference on Computer Networks and Communication Technologies

Print ISBN: 978-3-030-37050-3

Electronic ISBN: 978-3-030-37051-0

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-37051-0_94