Improved Security for Multimedia Data Visualization Using Hierarchical Clustering Algorithm

Author:

S. Shitharth1,Manoharan Hariprasath2ORCID,Khadidos Alaa O.3ORCID,Shankar Achyut4ORCID,Maple Carsten5ORCID,Khadidos Adil O.6ORCID,Mumtaz Shahid78ORCID

Affiliation:

1. Department of Computer Science, Kebri Dehar University, Kebri Dehar, Ethiopia

2. Department of Electronics and Communication Engineering, Panimalar Engineering College, Poonamallee, Chennai

3. Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

4. WMG, University of Warwick, Coventry, United Kingdom

5. Secure Cyber Systems Research Group (SCSRG), WMG, University of Warwick, Coventry, UK

6. Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

7. Department of Applied Informatics Silesian University of Technology, Akademicka 16 44-100 Gliwice, Poland

8. Nottingham Trent University, Engineering department, UK

Abstract

In this paper, a realization technique is designed with unique analytical model for transmitting multimedia data to appropriate end users. Transmission of multimedia data to all end users through a variety of visualization methods is the foundation of future computer systems. Yet, highly limited system resources prevent the updating of the methods used to manage multimedia data. Hence, a high-end visualization technique where uncertainties are eliminated is required for the visualization process with a multimedia system. As a result, the suggested system incorporates a clustering technique utilizing an analytical framework to ensure a high degree of transmission for all multimedia data. The technical contribution of the proposed method depend on multimedia visualization process that takes place with high security features by including necessary parametric relationships such as occurrence of jitter, data density points, time period, multimedia storage, data smoothness and distance. For the established parametric relationship the validation methodology is integrated with hierarchical clustering algorithm thereby transmitting every clustered data with high security feature thereby the examined outcomes under five scenarios proves that data security which is represented by simulation outcomes is improved to 88% as compared to existing approach.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture

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4. Adil O. Khadidos , Abdulrhman M. Alshareef , Hariprasath Manoharan , Alaa O. Khadidos , and S Shitharth . 2023 . Application Of Improved Support Vector Machine For Pulmonary Syndrome Exposure With Computer Vision Measures . Curr. Bioinform. 18 , (2023), 1–13. DOI:https://doi.org/10.2174/1574893618666230206121127 10.2174/1574893618666230206121127 Adil O. Khadidos, Abdulrhman M. Alshareef, Hariprasath Manoharan, Alaa O. Khadidos, and S Shitharth. 2023. Application Of Improved Support Vector Machine For Pulmonary Syndrome Exposure With Computer Vision Measures. Curr. Bioinform. 18, (2023), 1–13. DOI:https://doi.org/10.2174/1574893618666230206121127

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