Security and Privacy in Cloud Computing: Technical Review

Abstract

Advances in the usage of information and communication technologies (ICT) has given rise to the popularity and success of cloud computing. Cloud computing offers advantages and opportunities for business users to migrate and leverage the scalability of the pay-as-you-go price model. However, outsourcing information and business applications to the cloud or a third party raises security and privacy concerns, which have become critical in adopting cloud implementation and services. Researchers and affected organisations have proposed different security approaches in the literature to tackle the present security flaws. The literature also provides an extensive review of security and privacy issues in cloud computing. Unfortunately, the works provided in the literature lack the flexibility in mitigating multiple threats without conflicting with cloud security objectives. The literature has further focused on only highlighting security and privacy issues without providing adequate technical approaches to mitigate such security and privacy threats. Conversely, studies that offer technical solutions to security threats have failed to explain how such security threats exist. This paper aims to introduce security and privacy issues that demand an adaptive solution approach without conflicting with existing or future cloud security. This paper reviews different works in the literature, taking into account its adaptiveness in mitigating against future reoccurring threats and showing how cloud security conflicts have invalidated their proposed models. The article further presents the security threats surrounding cloud computing from a user perspective using the STRIDE approach. Additionally, it provides an analysis of different inefficient solutions in the literature and offers recommendations in terms of implementing a secure, adaptive cloud environment.

Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach

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IOT-Based Medical Informatics Farming System with Predictive Data Analytics Using Supervised Machine Learning Algorithms

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“…Computational and Mathematical Methods in Medicine security and privacy in cloud computing can be implemented to design prototype for cloud layer devices [15][16][17]. and the demonstration of space time coding for MDL mitigation and capacity enhancement of FTS gives right direction for transmission criteria [18][19][20].…”

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