Data security model using deep learning and edge computing for Internet of Things (IoT) in smart city

Citation

M. S. Tahsin, M. Y. Aziz, T. A. Kabbo, T. Tahsin, N. h. Zumme and M. I. Hossain, "Data Security Model Using Deep Learning and Edge Computing for Internet of Things (IoT) in Smart City," 2021 19th OITS International Conference on Information Technology (OCIT), Bhubaneswar, India, 2021, pp. 381-386, doi: 10.1109/OCIT53463.2021.00081.

Abstract

In the current ongoing world of IoT (Internet of things) devices, it is vital to have a safe, secure and reliable cyberspace. Cyberspace or network is free from all sorts of unethical activities like hacked systems, data breaches and stolen data. For that goal to be accomplished, we need to have a modern, solid and rigid cybersecurity system to stay safe from harm's way. Our research includes recent IoT data security issues and a robust security model that ensures the IoT devices' data security based on a smart city's perspective. According to the recent research data on the vulnerable IoT devices we propose an intelligent and effective security approach to tackle the modern IoT security issues because our data needs to be protected as the IoT devices or 'things' as we call it needs to have proper security. A few areas of future research indicate the use of blockchain to resolve the cybersecurity issues of IoT devices are the most promising and exciting.

Description

Type

Conference Proceeding