Saudi Cultural Missions Theses & Dissertations
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Item Restricted Cloud Cybersecurity(Universidad de Al cala, 2024) Bokhari, Nabil; Herraiz, Martinez; Javier, JoseThe 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.11 0Item Restricted Barriers to adoption of cloud computing faced by SMEs across Saudi Arabia: A quantitative study(University of Portsmouth, 2024-09) Alsubaiy, Eman Shabib; Kagalidis, IoannisThis research investigates the barriers to cloud computing adoption among small and medium enterprises (SMEs) in Saudi Arabia, a critical focus given the country's Vision 2030 objectives to enhance contribution of SMEs to GDP. The rationale originates from the low cloud adoption rate among Saudi SMEs, despite the significant benefits cloud technology offers in improving operational efficiency and competitiveness. The study aims to identify the key barriers to cloud adoption, assess how demographic factors such as industry type, gender, and education level influence these barriers, and develop targeted recommendations to increase adoption rates. The literature review highlighted several potential barriers, including knowledge gaps, lack of management support, information security concerns, insufficient IT capabilities, and provider lock-in risks. Hypotheses were developed to test these barriers using quantitative methods. A survey was conducted among 84 Saudi SME owners and managers, and the data were analysed using descriptive statistics, correlation, regression, and independent sample t-tests. The findings reveal that information security concerns and lack of skilled IT staff are the most significant barriers to cloud adoption. Additionally, manufacturing SMEs and less educated owners are less likely to adopt cloud technologies. Gender, however, does not significantly impact adoption decisions. The study concludes that addressing these key barriers, particularly through enhanced cybersecurity measures and targeted IT training, is essential for increasing cloud adoption among Saudi SMEs. Recommendations include tailored security solutions, skill development programs, and sector-specific support, particularly for the manufacturing industry.27 0