Enhancing Security in Mobile Cloud Computing: An Analysis of Authentication Protocols and Innovation
Journal Title: International Journal of Innovations in Science and Technology - Year 2024, Vol 6, Issue 2
Abstract
Introduction/Importance of Study: Cloud computing is a model facilitating ubiquitous, convenient, and on-demand network access to a shared pool of computing resources, offering flexibility, reliability, and scalability . Objective: This study investigates authentication mechanisms in Mobile Cloud Computing (MCC) to enhance security and address emerging challenges. Novelty statement: Our research contributes novel insights into authentication protocols in MCC, offering solutions to security issues not previously addressed. Material and Method: The study analyzed various authentication mechanisms in MCC using NIST evaluation criteria, considering their alignment with security needs and resource constraints. Result and Discussion: Our findings underscore the importance of selecting authentication mechanisms that balance security and performance in MCC environments, highlighting the need for ongoing innovation in security measures. Concluding Remarks: The study emphasizes the significance of robust authentication protocols tailored to MCC's unique security requirements for ensuring data integrity and privacy.
Authors and Affiliations
Amna Shahzadi, Kashif Ishaq, Naeem A. Nawaz, Ghulam Mustafa, Fawad Ali Khan
Lightweight Cryptography Algorithms for Internet of ThingsEnabled Networks.A Comparative Study
The rapid advancement of technology has facilitated the interconnection of numerous devices, enabling the collection of vast amounts of data. Consequently, ensuring security within IoT networks has become a top priorit...
Designing an AI-Based Greenhouse Plant Monitoring System to Detect and Classify Plant Diseases from Leaf Images
Plant diseases can significantly hinder food crop production, leading to substantial economic losses and posing a threat to global food security. Machine learning, particularly deep learning, plays a crucial role in ob...
Enabling Early Treatment: A Deep Learning Approach to Multi-Class Potato Leaf Disease Identification
Over 60% of the world's population largely depends on the agricultural sector for food, as indicated by previous studies, demonstrating the historical significance of agriculture as a means of survival. Plant infection...
AI-Driven Weed Classification for Improved Cotton Farming in Sindh, Pakistan
This research study proclaims the combination of artificial intelligence and also IoT in precision agriculture, highlighting weed discovery plus cotton plant monitoring in Sindh, Pakistan. The uniqueness lies in creati...
Python Based Estimation ofGroundwater Quality Along Hudaira Drain
During periods of restricted access to fresh surface water, enterprises depend on underground water reserves to meet their growing demands. Groundwater is crucial for fulfilling the growing demands of families, agricul...