Title: New security protocols of internet of things: improving the security in IoT

Authors: N. Ashokkumar; M. Ananthi; M. Sri Geetha; V.P. Arul Kumar

Addresses: Department of Electronics and Communication Engineering, Mohan Babu University, Tirupathi, Andrapradesh, India ' Department of Artificial Intelligence and Data Science, V.S.B. Engineering College, Karur, India ' School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Delhi NCR, Faridabad, India ' Department of Information Technology, Karpagam Institute of Technology, Tamil Nadu – 641021, India

Abstract: The industrial domains using IoT devices are expanding together with the market for IoT solutions and services. Security problems have been solved by researchers using machine learning to find intrusions at the network level. Using information from large source area datasets, transfer learning has been used to find dangerous traffic in internet of things systems that were not predicted. The problem is that most IoT devices work in small, different settings, like home networks, which makes it hard to pick good source domains for learning. This study gives us a plan for how to deal with this problem. Our suggested method says to choose a dataset as the source area for learning when it is hard to find a good dataset through pre-learning with transfer learning. Transfer learning is checked to see if it should be used so that the best way can be used in these situations.

Keywords: internet of things; IoT; intrusion detection; transfer learning; wireless sensor networks; WSNs; security.

DOI: 10.1504/IJESDF.2026.155007

International Journal of Electronic Security and Digital Forensics, 2026 Vol.18 No.4, pp.494 - 507

Received: 14 Jun 2024
Accepted: 10 Oct 2024
Published online: 22 Jul 2026 *

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