Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021)

Enhanced Security Model for Pervasive Computing Using Machine Learning Techniques

Authors
Jayashree Agarkhed, Geetha Pawar
Corresponding Author
Geetha Pawar
Available Online 13 September 2021.
DOI
https://doi.org/10.2991/ahis.k.210913.051How to use a DOI?
Keywords
ubiquitous computing(ubicomp), pervasive computing, artificial intelligence, machine learning, Enhanced Trust model Introduction
Abstract

In recent mobile world the pervasive computing plays the vital role in data computing and communication. The pervasive computing provides the mobile environment for decentralized computational services where the user work and socializes. Pervasive computing in recent trend moves away from the desktop to make surrounding as flexible and portable dev ices like laptop, notepad, smartphones and personal digital assistants. Pervasive environment devices are worldwide and able to receive various communication services including TV, cable network, radio station and other audio-visual services. The users and the system in this pervasive environment may face the challenges of user trust, data privacy and user and device node identity. To give the feasible determination for these challenges. This paper aims to propose a dynamic-learning pervasive computing environment to refer the challenges’ proposed efficient trust model (ETM) for trustworthy and untrustworthy attackers. ETM model also compared with existing generic models, it also provides 97 % accuracy rate than existing models.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021)
Series
Atlantis Highlights in Computer Sciences
Publication Date
13 September 2021
ISBN
978-94-6239-428-5
ISSN
2589-4900
DOI
https://doi.org/10.2991/ahis.k.210913.051How to use a DOI?
Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jayashree Agarkhed
AU  - Geetha Pawar
PY  - 2021
DA  - 2021/09/13
TI  - Enhanced Security Model for Pervasive Computing Using Machine Learning Techniques
BT  - Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021)
PB  - Atlantis Press
SP  - 414
EP  - 420
SN  - 2589-4900
UR  - https://doi.org/10.2991/ahis.k.210913.051
DO  - https://doi.org/10.2991/ahis.k.210913.051
ID  - Agarkhed2021
ER  -