Security, Privacy, and Trust in Cloud Computing: An Integrated Survey of Techniques
DOI:
https://doi.org/10.5281/Keywords:
Trust Management, Cloud Computing,, Trust Evaluation, Security, Privacy, Data Protection, Access Control, Federated Learning, Risk Assessment, Regulatory ComplianceAbstract
Cloud computing has emerged as a transformative model for delivering IT services, offering scalable, flexible, and cost-efficient access to computing resources over the internet. It is structured around three primary service models—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)—which delineate varying levels of user control and provider responsibility. Deployment models, including public, private, hybrid, and community clouds, further define ownership, access, and operational scope. Key stakeholders in the cloud ecosystem include service providers, consumers, and intermediaries such as brokers. However, the adoption of cloud technologies introduces significant challenges, particularly in areas of security, privacy, and trust. Threats such as data breaches, insecure APIs, insider risks, and multi-tenancy vulnerabilities compromise cloud integrity, while issues like data ownership, cross-border data flow, and regulatory compliance raise privacy concerns. Trust in cloud environments hinges on transparency, robust service-level agreements (SLAs), auditability, and third-party certifications like ISO 27001 and SOC 2. Addressing these challenges is essential for ensuring secure, privacy-compliant, and trustworthy cloud services that can support mission-critical applications across sectors.
References
[1] S. Stoykova and N. Shakev, “Artificial Intelligence for Management Information Systems: Opportunities, Challenges, and Future Directions,” Algorithms, vol. 16, no. 8, p. 357, Jul. 2023, doi: 10.3390/a16080357.
[2] M. L. Hernandez-Jaimes, A. Martinez-Cruz, K. A. Ramírez-Gutiérrez, and C. Feregrino-Uribe, “Artificial intelligence for IoMT security: A review of intrusion detection systems, attacks, datasets and Cloud–Fog–Edge architectures,” Internet of Things, vol. 23, p. 100887, Oct. 2023, doi: 10.1016/j.iot.2023.100887.
[3] P. C. Jakku, P. Sundaramoorthy, S. C. Kondaparthy, T. Desai, R. Jarubula, and A. Nerella, “Enhancing Cloud Security Via Quantum Computing,” in Proceedings of Data Analytics and Management, A. Swaroop, B. Virdee, S. Correia, and Z. Polkowski, Eds., Cham: Springer Nature Switzerland, 2025, pp. 377-386,November.
[4] V. R. Iyer, K. Babu, and V. R. Guruswamy, “Cyber Security Frameworks through the Lens of Foreign Direct Investment (FDI): A Systematic Literature Review,” Int. J. Intell. Syst. Appl. Eng., 2024.
[5] R. Palwe, “Onboarding for AI features: Reducing friction at the first use,” Int. J. Comput. Artif. Intell., vol. 6, no. 2, pp. 393–400, Jul. 2025, doi: 10.33545/27076571.2025.v6.i2e.227.
[6] H. Makina, A. B. E. N. Letaifa, and A. Rachedi, “Leveraging Edge Computing, Blockchain and IPFS for Addressing eHealth Records Challenges,” in Proceedings of the 2022 15th IEEE International Conference on Security of Information and Networks, SIN 2022, 2022. doi: 10.1109/SIN56466.2022.9970495.
[7] R. Lingam, S. Nagi, M. Chigurupati, and B. T. Myneni, “Resilient DevSecOps: Self-Healing Cloud-Native Systems via SRE-Driven AI Threat Detection and Response,” in 2026 International Conference on Smart Futuristic Technology, IEEE, Jan. 2026, pp. 1–6. doi: 10.1109/ICSFT66733.2026.11508049.
[8] O. C. Obi, S. O. Dawodu, A. I. Daraojimba, and S. Onwusinkwue, “Review Of Evolving Cloud Computing Paradigms: Security, Efficiency, And Innovations,” Comput. Sci. IT Res. J., vol. 5, no. 2, pp. 270–292, Feb. 2024, doi: 10.51594/csitrj.v5i2.757.
[9] A. Atadoga, U. J. Umoga, O. A. Lottu, and E. O. Sodiya, “Evaluating the impact of cloud computing on accounting firms: A review of efficiency, scalability, and data security,” Glob. J. Eng. Technol. Adv., vol. 18, no. 2, pp. 065–075, Feb. 2024, doi: 10.30574/gjeta.2024.18.2.0027.
[10] R. Younis, M. Iqbal, K. Munir, M. A. Javed, M. Haris, and S. Alahmari, “A Comprehensive Analysis of Cloud Service Models: IaaS, PaaS, and SaaS in the Context of Emerging Technologies and Trends,” in 2024 International Conference on Electrical, Communication and Computer Engineering (ICECCE), IEEE, Oct. 2024, pp. 1–6. doi: 10.1109/ICECCE63537.2024.10823401.
[11] M. Alshinwan, A. Y. Shdefat, N. Mostafa, A. A. M. Alsokkar, T. Alsarhan, and D. Almajali, “Integrated cloud computing and blockchain systems: A review,” Int. J. Data Netw. Sci., 2023, doi: 10.5267/j.ijdns.2022.12.016.
[12] T. Shah, “Cloud-Based Data Warehousing for Marketing Agility: Lessons from FinTech Migrations to Snowflake and AWS,” Int. J. Adv. Res. Sci. Commun. Technol., vol. 4, no. 4, March, pp. 642–652, 2024, doi: 10.48175/IJARSCT-16000B.
[13] E. Irmak, E. Kabalci, and Y. Kabalci, “Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity,” 2023. doi: 10.3390/en16124590.
[14] S. Reema, “Cloud Computing as a Solution for Security and Privacy Concerns,” Int. J. Res. Appl. Sci. Eng. Technol., 2023, doi: 10.22214/ijraset. 2023.49375.
[15] T. Esho, O. Ayeni, O. Lasisi, and O. Peter, “The Role of Cloud Computing in Personalized Medicine: A Systematic Review,” Curr. J. Appl. Sci. Technol., 2024, doi: 10.9734/cjast/2024/v43i34355.
[16] M. R. C. Mukkolakkal, “InfraLLM: A Generic Large Language Model Framework for Production-Grade Microservice Auto-Scaling in Cloud Infrastructure,” Int. J. Sci. Res. Mod. Technol., vol. 4, no. 11, pp. 113–123, 2025, doi: 10.38124/ijsrmt.v4i11.1023.
[17] F. Mohd Ali, N. A. Md Yunus, N. N. Mohamed, M. Mat Daud, and E. A. Sundararajan, “A Systematic Mapping: Exploring Internet of Everything Technologies and Innovations,” 2023. doi: 10.3390/sym15111964.
[18] R. Palwe, “Three Layers of Trust in AI Interfaces: Interface, Behaviour, and Organization,” Int. J. Sci. Res., vol. 15, no. 1, pp. 1152–1160, Jan. 2026, doi: 10.21275/SR26112072531.
[19] J. B. Mehta, “AI-Driven Test Engineering for Cloud-Native Systems,” Int. J. Data Sci. IoT Manag. Syst., vol. 5, no. 1, 2026, doi: 10.64751/ijdim. 2026. v5i1.297.
[20] A. Nag et al., “Exploring the applications and security threats of Internet of Things in the cloud computing paradigm: A comprehensive study on the cloud of things,” Trans. Emerg. Telecommun. Technol., 2024, doi: 10.1002/ett.4897.
[21] L. Liu, J. Li, J. Lv, J. Wang, S. Zhao, and Q. Lu, “Privacy-Preserving and Secure Industrial Big Data Analytics: A Survey and the Research Framework,” IEEE Internet Things J., 2024, doi: 10.1109/JIOT.2024.3353727.
[22] A. Katangoori, “The Role of Big Data in Advancing Artificial Intelligence: Methods and Case Studies,” Int. J. Artif. Intell. Mach. Learn., vol. 6, no. 1, pp. 37–54, Jan. 2026, doi: 10.51483/IJAIML.6.1.2026.37-54.
[23] S. K. Chintagunta and S. Amrale, “Enhancing Cloud Database Security Through Intelligent Threat Detection and Risk Mitigation,” Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol., vol. 8, no. 3, pp. 756–768, 2022.
[24] S. Ahmad, S. Mehfuz, and J. Beg, “Assessment on potential security threats and introducing novel data security model in cloud environment,” in Materials Today: Proceedings, 2022. doi: 10.1016/j.matpr.2022.03.536.
[25] T. Ali, M. Al-Khalidi, and R. Al-Zaidi, “Information Security Risk Assessment Methods in Cloud Computing: Comprehensive Review,” J. Comput. Inf. Syst., vol. 66, no. 1, pp. 123–150, Jan. 2026, doi: 10.1080/08874417.2024.2329985.
[26] A. Rahdari et al., “A Survey on Privacy and Security in Distributed Cloud Computing: Exploring Federated Learning and Beyond,” IEEE Open J. Commun. Soc., vol. 6, pp. 3710–3744, 2025, doi: 10.1109/OJCOMS.2025.3560034.
[27] S. A. Kawalkar and D. B. Bhoyar, “Design of an Efficient Cloud Security Model through Federated Learning, Blockchain, AI-Driven Policies, and Zero Trust Frameworks,” Int. J. Intell. Syst. Appl. Eng., 2024.
[28] M. Chauhan and S. Shiaeles, “An Analysis of Cloud Security Frameworks, Problems and Proposed Solutions,” Network, vol. 3, no. 3, pp. 422–450, 2023, doi: 10.3390/network3030018.
[29] N. Soveizi, F. Turkmen, and D. Karastoyanova, “Security and privacy concerns in cloud-based scientific and business workflows: A systematic review,” Futur. Gener. Comput. Syst., vol. 148, pp. 184–200, Nov. 2023, doi: 10.1016/j.future.2023.05.015.
[30] J. J. Ang’udi and S. Awour, “Security challenges in cloud computing: A comprehensive analysis,” World J. Adv. Eng. Technol. Sci., vol. 10, no. 2, pp. 155–181, Dec. 2023, doi: 10.30574/wjaets. 2023.10.2.0304.
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