Applied Mathematics & Information Sciences
The smart city uses Information and Communication Technologies (ICT) to build, run and sustain the environment, economic methods to overcome the growing problems of urbanization. Security, security, secrecy and validity have all been important factors in smart city applications, and they are also important in smart city infrastructure interfaces.Hence In this research, an Artificial Intelligence-Big Data Model (AIBM) was developed to enhance the data protection elements of information management interfaces in different smart city applications to address these concerns. A divergent evolutionary method has been implemented in AIBM to provide adequate security for the Secret Data Domain Controller for smart city applications.In addition, the differentiated iterative method has been enhanced by the choice security method based on Big Data Analytics (BDA). It improves the flexibility and dissemination of data in an information authority based mostly on their associated storage site.In addition, ability to adapt interferences approach has been implemented and developed to improve the flexibility and security of information management interfaces in different smart city applications.The reliability of the proposed platform has been demonstrated through computer analysis based on security, accuracy, speed and adaptability.
Digital Object Identifier (DOI)
Saravanan, S.; Sivabalakrishnan, M.; Duraimurugan, N.; and Divya, D.
"Artificial Intelligence Security Model For Privacy Renitence In Big Data Analytics,"
Applied Mathematics & Information Sciences: Vol. 16:
5, Article 8.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol16/iss5/8