Cloud Cybersecurity

dc.contributor.advisorHerraiz, Martinez
dc.contributor.advisorJavier, Jose
dc.contributor.authorBokhari, Nabil
dc.date.accessioned2024-11-25T06:55:18Z
dc.date.issued2024
dc.description.abstractThe rapid evolution of cloud computing has revolutionized modern business operations, from hosting applications to storing data in high-security environments. Competitive businesses are leveraging cloud computing solutions to maximize the benefits, including cost-effectiveness, flexibility, and scalability. Cloud computing enables enterprises to access on-demand and scalable computing resources, specifically computational power and vast data storage. Despite the immense benefits, the security of data transmitted and stored in a cloud computing environment is vulnerable to multiple cybersecurity attacks, including data manipulation, loss, and theft. The study aims to develop a security model for enhanced data privacy and security in the cloud by leveraging a hybrid of cryptographic algorithms and steganography image-based techniques. The security model innovatively combines Advanced Encryption Standard (AES), Rivest Shamir Adleman (RSA), and the Least Significant Bit (LSB) technique to enhance data privacy and security of data in motion in a cloud computing environment. The three-step security model was designed, developed, and evaluated using the Design Science Research (DSR) methodology. The model secures data through cryptographic algorithms, adds an extra security layer using steganography, and implements backup and data recovery. The methodology was selected because of its practicality and philosophical underpinnings on addressing contemporary challenges by developing novel and relevant artifacts using scientifically rigorous procedures. The findings show that a hybrid of cryptography and steganography provides unbeatable security for data in a cloud computing environment. Implementing the security model will enhance data privacy and security in the cloud by revolutionizing how data is encrypted and decrypted. In the future, the integration of Machine Learning and Artificial Intelligence methodologies and algorithms will quadruple the effectiveness and robustness of this data security model for the cloud.
dc.format.extent126
dc.identifier.urihttps://hdl.handle.net/20.500.14154/73735
dc.language.isoen_US
dc.publisherUniversidad de Al cala
dc.subjectCryptography
dc.subjectsteganography
dc.subjectsecurity
dc.subjectdata privacy
dc.subjectcybersecurity
dc.subjectAdvanced Encryption Standard
dc.subjectRivest Shamir Adleman
dc.subjectLeast Significant Bit
dc.subjectencryption
dc.subjectcloud computing
dc.subjectdesign science research
dc.subjectcyber-attacks
dc.titleCloud Cybersecurity
dc.typeThesis
sdl.degree.departmentINFORMATION AND KNOWLEDGE ENGINEERING
sdl.degree.disciplineComputer Science
sdl.degree.grantorUniversidad de Al cala
sdl.degree.nameDoctor of Philosophy

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