IoT based security and privacy implementation in smart home

Research Article
Open access

IoT based security and privacy implementation in smart home

J. Rajasekhar 1 , T. Thanusha 2 , G. Naga Jyothi 3 , K. Tejaswi 4 , Laith Abualigah 5*
  • 1 Koneru Lakhmaiah Education Foundation    
  • 2 Koneru Lakhmaiah Education Foundation    
  • 3 Koneru Lakhmaiah Education Foundation    
  • 4 Koneru Lakhmaiah Education Foundation, Vaddeswaram    
  • 5 Al al-Bayt University, Middle East University    
  • *corresponding author aligah.2020@gmail.com
ACE Vol.44
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-327-2
ISBN (Online): 978-1-83558-328-9

Abstract

Internet-of-Thing’s technology is being increasingly important in our daily lives. As IoT technology evolved, IoT devices face a data protection hazard, particularly smart home IoT gateway devices, which became evident. The demand for a low-cost, secure smart home gateway device or router among smart home users. The problem is that as the internet of things (IoT) becomes more ubiquitous, there is a growing need to simplify wireless network control mechanisms. Because data collecting and the process includes processes such as monitoring, judging, and controlling are all involved in IoT, the control mechanism is challenging to simplify. Many internets of things technology offer memory and communication capabilities, and are easily vulnerable to hacking, due to the mobile software available at the tip of one's fingers to operate the linked gadgets to the web. In the Internet of Things, secure data transfer is always a concern. To increase safety in IoT and wireless networks, the current study introduces a unique RSA-based method, as well as the AES algorithm and the lightweight protocol message queue telemetry transport (MQTT).

Keywords:

IoT, MQTT, security, aes kdsb algorithm

Rajasekhar,J.;Thanusha,T.;Jyothi,G.N.;Tejaswi,K.;Abualigah,L. (2024). IoT based security and privacy implementation in smart home. Applied and Computational Engineering,44,202-207.
Export citation

References

[1]. Sathishkumar V E, Changsun Shin, Youngyun Cho, “Efficient energy consumption prediction model for a data analytic-enabled industry building in a smart city”, Building Research & Information, Vol. 49. no. 1, pp. 127-143, 2021.

[2]. Sathishkumar V E, Youngyun Cho, “A rule-based model for Seoul Bike sharing demand prediction using Weather data”, European Journal of Remote Sensing, Vol. 52, no. 1, pp. 166-183, 2020.

[3]. Sathishkumar V E, Jangwoo Park, Youngyun Cho, “Seoul Bike Trip duration prediction using data mining techniques”, IET Intelligent Transport Systems, Vol. 14, no. 11, pp. 1465-1474, 2020.

[4]. Sathishkumar V E, Jangwoo Park, Youngyun Cho, “Using data mining techniques for bike sharing demand prediction in Metropolitan city”, Computer Communications, Vol. 153, pp. 353-366, 2020.

[5]. Sathishkumar V E, Yongyun Cho, “Season wise bike sharing demand analysis using random forest algorithm”, Computational Intelligence, pp. 1-26, 2020.

[6]. Sathishkumar V E, Myeongbae Lee, Jonghyun Lim, Yubin Kim, Changsun Shin, Jangwoo Park, Yongyun Cho, “An Energy Consumption Prediction Model for Smart Factory using Data Mining Algorithms” KIPS Transactions on Software and Data Engineering, Vol. 9, no. 5, pp. 153-160, 2020.

[7]. Sathishkumar V E, Jonghyun Lim, Myeongbae Lee, Yongyun Cho, Jangwoo Park, Changsun Shin, and Yongyun Cho, “Industry Energy Consumption Prediction Using Data Mining Techniques”, International Journal of Energy Information and Communications, Vol. 11, no. 1, pp. 7-14, 2020.

[8]. Ronggang Zhang, Sathishkumar V E, R. Dinesh Jackson Samuel, “Fuzzy Efficient Energy Smart Home Management System for Renewable Energy Resources”, Sustainability, Vol. 12, no. 8, pp. 1-15, 2020.

Cite this article

Rajasekhar,J.;Thanusha,T.;Jyothi,G.N.;Tejaswi,K.;Abualigah,L. (2024). IoT based security and privacy implementation in smart home. Applied and Computational Engineering,44,202-207.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation

ISBN：978-1-83558-327-2(Print) / 978-1-83558-328-9(Online)
Editor：Mustafa İSTANBULLU
Conference website: https://2023.confmla.org/
Conference date: 18 October 2023
Series: Applied and Computational Engineering
Volume number: Vol.44
ISSN：2755-2721(Print) / 2755-273X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).

References

[1]. Sathishkumar V E, Changsun Shin, Youngyun Cho, “Efficient energy consumption prediction model for a data analytic-enabled industry building in a smart city”, Building Research & Information, Vol. 49. no. 1, pp. 127-143, 2021.

[2]. Sathishkumar V E, Youngyun Cho, “A rule-based model for Seoul Bike sharing demand prediction using Weather data”, European Journal of Remote Sensing, Vol. 52, no. 1, pp. 166-183, 2020.

[3]. Sathishkumar V E, Jangwoo Park, Youngyun Cho, “Seoul Bike Trip duration prediction using data mining techniques”, IET Intelligent Transport Systems, Vol. 14, no. 11, pp. 1465-1474, 2020.

[4]. Sathishkumar V E, Jangwoo Park, Youngyun Cho, “Using data mining techniques for bike sharing demand prediction in Metropolitan city”, Computer Communications, Vol. 153, pp. 353-366, 2020.

[5]. Sathishkumar V E, Yongyun Cho, “Season wise bike sharing demand analysis using random forest algorithm”, Computational Intelligence, pp. 1-26, 2020.

[6]. Sathishkumar V E, Myeongbae Lee, Jonghyun Lim, Yubin Kim, Changsun Shin, Jangwoo Park, Yongyun Cho, “An Energy Consumption Prediction Model for Smart Factory using Data Mining Algorithms” KIPS Transactions on Software and Data Engineering, Vol. 9, no. 5, pp. 153-160, 2020.

[7]. Sathishkumar V E, Jonghyun Lim, Myeongbae Lee, Yongyun Cho, Jangwoo Park, Changsun Shin, and Yongyun Cho, “Industry Energy Consumption Prediction Using Data Mining Techniques”, International Journal of Energy Information and Communications, Vol. 11, no. 1, pp. 7-14, 2020.

[8]. Ronggang Zhang, Sathishkumar V E, R. Dinesh Jackson Samuel, “Fuzzy Efficient Energy Smart Home Management System for Renewable Energy Resources”, Sustainability, Vol. 12, no. 8, pp. 1-15, 2020.

For authors
Guide for authors Policies for authors Aims and scope Subscription Open access policy
For editors
Policies for editors Editorial board
For reviewers
Policies for reviewers Privacy policy

Cookies are used by this site.
Copyright © 2024 EWA Publishing, its licensors, and contributors. All rights reserved, including text and data mining, AI training, and similar technologies.