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Machine Learning Approach for Cloud Data Analytics in IoT
book

Machine Learning Approach for Cloud Data Analytics in IoT

by Sachi Nandan Mohanty, Jyotir Moy Chatterjee, Monika Mangla, Suneeta Satpathy, Sirisha Potluri
July 2021
Intermediate to advanced
528 pages
13h 35m
English
Wiley-Scrivener
Content preview from Machine Learning Approach for Cloud Data Analytics in IoT

6Cloud Cryptography for Cloud Data Analytics in IoT

N. Jayashri1* and K. Kalaiselvi2

1Department of Computer Applications, Dr. M.G.R. Educational and Research Institute, Chennai, Tamilnadu, India

2Department of Computer Applications, School of Computing Sciences, Vels Institute of Science, Technology and Advanced Studies (Formerly Vels University), Chennai, Tamil Nadu, India

Abstract

The potential Internet of Things (IoT) will have a profoundly prudent business and social impact on our lives. A hub of interest in IoT systems is typically an asset obligation, which makes them focus on digital assault baiting. In this way, broad attempts have been devoted to identifying security and safety difficulties in trendy IoT, primarily through conventional cryptographic methodologies. In any case, the remarkable qualities of IoT hubs make it the main objective of the association and collaboration between objects and objects sent through remote systems to satisfy the target set for them as a united element, to achieve a superior domain for the use of big data. What is more, based on the creativity of remote systems, both platforms and IoT may grow quickly and together. In this section, it methodically audits the security needs, the assault vectors, and the current security responses for IoT systems. It also addresses insights into current machine learning solutions for solving various security issues in IoT systems and a few future cryptography cloud analysis headlines.

Keywords: Internet ...

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Publisher Resources

ISBN: 9781119785804Purchase Link