Cloud Security Vulnerabilities: A Comprehensive Survey and Analysis of Risks in IaaS, PaaS, and SaaS Models with Practical Data and Methodology for Mitigating Breaches
Keywords:
Cloud computing, vulnerabilities, data security, cloud service models, mitigation strategiesAbstract
: Cloud computing has become integral to modern IT infrastructure, offering scalability, flexibility, and cost efficiency. However, its multi-tenant nature and reliance on shared resources present unique security challenges. This study aims to assess the security risks associated with three major cloud service models—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)—through both qualitative and quantitative methods. A survey was conducted to gather risk scores from 100 IT professionals, which were then analyzed statistically. The results revealed that the mean risk scores for IaaS, PaaS, and SaaS were 6.21, 6.69, and 7.11, respectively. Descriptive statistics showed that IaaS exhibited greater variability in risk scores compared to PaaS and SaaS. Correlation analysis indicated a moderate positive correlation between IaaS and SaaS (0.72), while the correlations between IaaS and PaaS (0.43) and PaaS and SaaS (0.42) were lower. An ANOVA test revealed no significant differences in the risk scores across the three cloud models (F = 2.53, p = 0.107), suggesting that risk levels were similar. However, regression analysis indicated that cloud model type significantly predicted risk scores (R² = 0.219, p = 0.032), with SaaS exhibiting the highest risk scores. These findings underscore the need for tailored security strategies based on the specific characteristics of each cloud service model, while highlighting the potential of statistical methods in analyzing cloud security risks.
Downloads
Published
Issue
Section
License
Authors retain copyright and grant the journal the right of first publication. Articles published in this journal are licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), permitting unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to Cite
Similar Articles
- Amarachi Nelly Charles, Oluwabukola Victoria Akinyemi, Chinyan Blessing, AI-Enabled Marketing Communication and Machine Learning Analytics for Consumer Insights, Brand Positioning, and Business Growth , Applied Science, Computing, and Energy: Vol. 1 No. 1 (2024): VOLUME 1 ISSUE 1
- Temitope Akinwunmi, Artificial Intelligence (AI) and Firm Survival of Deposit Money Banks , Applied Science, Computing, and Energy: Vol. 2 No. 1 (2025): VOLUME 2 ISSUE 1
- Onaara Enitan Obamuwagun , Innovative Strategies in Fan Engagement and Revenue generation for Collegiate Athletics Programs , Applied Science, Computing, and Energy: Vol. 3 No. 1 (2025): VOLUME 3 ISSUE 1
- Nana Fatima Abdulmalik, Bello, Ayoola Yusuf, Mu’awiya Baba Aminu, Christopher Simon Dalom, Integrating Satellite Imagery and Aero-radiometric Datasets in Lithological Discrimination and Detection of Hydrothermal Zones at Ikara and its Environs, North-Central of the Basement Complex, Nigeria , Applied Science, Computing, and Energy: Vol. 2 No. 1 (2025): VOLUME 2 ISSUE 1
- Anthony I. G. Ekedegwa, Integrated Optimization of Nuclear Energy Transmission Systems to Minimize Grid and Data Center Power Losses , Applied Science, Computing, and Energy: Vol. 4 No. 3 (2026): Volume 4, Issue 3
- Uduak Irene Aletan, Sunday Adenekan, Phytochemical Profiling of Opa eyin, a Traditional Nigerian Herbal Preparation, by GC–MS and Its Potential Pharmacological Implications , Applied Science, Computing, and Energy: Vol. 3 No. 2 (2025): VOLUME 3 ISSUE 2
- Shehu Usman Gulumbe, Aminu Bello Zoramawa, Halilu Buhari Kware, Abdulkarim Bello, PKRIDS: A Real-Time Hybrid Host-Based Intrusion Detection System Using PCAmix, Kernel PCA, and Random Forest , Applied Science, Computing, and Energy: Vol. 3 No. 1 (2025): VOLUME 3 ISSUE 1
- Amos Abba, Data, Democracy, and Deep Learning: The Transformative Role of AI in Digital Journalism , Applied Science, Computing, and Energy: Vol. 3 No. 3 (2025): Volume 3, Issue 3
- Oliver U. Ekwueme, Samuel E. Edu, Segun O. Olayemi, Application of Magnetic Geophysical Techniques in Investigating Subsurface Deposits in Parts of Kogi State, North-Central Nigeria , Applied Science, Computing, and Energy: Vol. 4 No. 1 (2026): Volume 4 Issue 1
- Mu’awiya Baba Aminu, Sangodiji Enoch Ezekiel, Rebecca Juliet Ayanwunmi, Anako Shefawu Onize, Daniel Chukwunonso Chukwudi, Changde Andrew Nanfa, A Review of the Hydrogeological Framework and Groundwater Resources Management in Nigeria: Current Status and Future Trend , Applied Science, Computing, and Energy: Vol. 2 No. 2 (2025): VOLUME 2 ISSUE 2
You may also start an advanced similarity search for this article.