Title: Exploring the possibilities of integration of cyber-psychology for human behaviour in a smart city

Authors: Liping Wen; Zhou Ting; Huang Zheng; J. Alfred Daniel; A. Antonidoss

Addresses: Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100101, China; Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China ' Department of Medical Psychology, School of Health Humanities, Peking University, Beijing, 100191, China ' Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100101, China ' Department of Computer Science & Engineering, SNS College of Technology, India ' Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, India

Abstract: The smart city idea differs between cities and nations. In all meanings and characteristics of a smart city, public involvement is the only thing that remains common. Therefore, it is a very significant field to study human behaviour and development in smart cities. This paper presents a framework for identifying qualities necessary for people to be classified as intelligent persons and to integrate these human behavioural characteristics in cyber technology. Human behaviour in a smart city has been analysed using the machine learning algorithm and big data analytics. The integrated machine learning and big data analytics framework (iML-BD) classifies the cyber behaviour of intelligent persons in a smart city by observing the cyber activities performed by the individuals. Furthermore, this paper handles the risk factors for cyber-acquired and cyber-dependant crime violence and abuse that vulnerable internet and public access devices using blockchain technology. Blockchain is a method of storing data that takes too long to alter, modify, or manipulate. A blockchain is an electronic accounting system that is reproduced and spread through the Bitcoin protocol's entire communication network. The case study performed on iML-BD has resulted in the highest performance in terms of prediction accuracy of 94.98%.

Keywords: cyber crime; human behaviour; machine learning; smart city; vulnerability.

DOI: 10.1504/IJICT.2024.140321

International Journal of Information and Communication Technology, 2024 Vol.25 No.2, pp.150 - 167

Received: 18 Mar 2021
Accepted: 24 Aug 2021
Published online: 02 Aug 2024 *

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