A Security Framework for Data Migration over the Cloud
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ID: 312910
2024
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Abstract
The adoption of cloud services has ushered in a new era of business efficiency. However, major organizations' migration of critical software and data has encountered unanticipated obstacles, chiefly driven by concerns regarding data privacy and security. This article highlights the profound ramifications of migration delays, emphasising their potential to disrupt the uninterrupted flow of information, particularly in public and hybrid cloud environments. Our study reveals a well-organized framework that highlights essential security measures, such as the use of SSL/TLS protocols, which provide a secure channel of communication over the internet, data confidentiality and integrity (transmitted between a user's web browser and a website's server), encryption, authentication, building trust, and supporting data transmission integrity. In addition, we support the thoughtful application of restricted migration tickets, which effectively control access privileges and thwart unauthorized access. An innovative addition to this framework is the incorporation of Prediction-Based Encryption (PBE), a cutting-edge methodology uniquely suited to the intricacies of the healthcare and e-commerce sectors. PBE inherently segregates sensitive data, isolating it for separate storage, thereby mitigating the risk of data breaches during migration. It also refers to a theory wherein encryption techniques combine models or prediction algorithms to improve security. This could entail anticipating possible security risks or modifying encryption settings in response to expected shifts in the security environment. In conclusion, by embracing these meticulously devised security measures, organisations can surmount the challenges posed by migration delays and fortify their data protection strategies in the digital age.
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| Authors | Muhammad Azam, Fawad Nasim, Jawad Ahmad, Sohail Masood Bhatti |
| Journal | Journal of Computing & Biomedical Informatics |
| Year | 2024 |
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| Keywords | Keywords not found |
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