Date of Award

12-2024

Document Type

Project

Degree Name

Master of Science in Cybersecurity and Analytics

Department

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First Reader/Committee Chair

Canelon Herrera, Jesus

Abstract

This study investigates cryptographic methods to ensure data integrity within cloud environments, with a particular focus on comparing the security, performance, and efficiency of MD5 and SHA-256 hash algorithms. Data integrity is critical for protecting sensitive information, especially in sectors like healthcare, where cloud storage solutions are increasingly prevalent. Through a theoretical analysis, the study evaluates the advantages and limitations of MD5 and SHA-256, emphasizing SHA-256’s stronger security capabilities in preventing collision attacks compared to MD5, albeit with higher resource consumption.

The literature review draws from recent advancements in cryptography, blockchain, and artificial intelligence (AI) technologies, presenting a comprehensive view of the current landscape. Findings show that while MD5 offers faster processing times, its vulnerability to attacks renders it unsuitable for high-security applications. SHA-256, although more computationally intensive, provides robust protection against data integrity threats and is therefore recommended for applications requiring enhanced security.

The study concludes with recommendations for future research, proposing the exploration of blockchain and AI-driven solutions to further improve data integrity protocols. Additional suggestions include the development of hybrid cryptographic hash functions, systematic reevaluation of existing cryptographic techniques, and the implementation of Data Loss Prevention (DLP) systems tailored for Internet of Things (IoT) devices. These recommendations aim to address emerging cybersecurity challenges and advance the effectiveness of data integrity solutions within cloud computing and beyond.

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