OPTIMIZING DATA PROTECTION ON CLOUD NETWORK USING PASSWORD BASED IDENTIFICATION AND AUTHENTICATION TECHNIQUES

Subject Area: ENGINEERING

This paper addresses the crucial issue of data protection in cloud networks through the utilization of password-based identification and authentication techniques. A case study of a secondary school's local area network was conducted, revealing vulnerabilities that allowed unauthorized access to the school server. As the school lacked a central server and relied solely on a network provider for back-end storage, identifying intruders or students accessing the network became challenging. Consequently, the school's ICT personnel faced continuous stress from managing student login issues caused by hackers attempting to gain unauthorized access. To tackle these security challenges, the paper introduces a 4-phase approach consisting of registration, login, authentication, and password agreement phases. An empirical research approach was adopted, involving information gathering, hypothesis formation, data analysis, and conclusion drawing. The proposed methods were designed using a mathematical approach and implemented with SIMULINK. The results demonstrated that the real-time software and IP addresses registered in the database facilitated accurate user identification, leading to 0.7499% intrusion rate, effectively approaching zero, and an overall authentication accuracy of 98%. By adopting this approach, cloud networks can significantly enhance their data security and safeguard valuable resources from compromise and fraudulent access by unauthorized users.