Cloud Computing Security: Threats, Risks, and Mitigation Techniques
DOI:
https://doi.org/10.15662/IJARCST.2020.0304001Keywords:
Cloud Computing, Security Threats, Risk Management, Mitigation Techniques, Multi-Tenancy, Encryption, Access ControlAbstract
: Cloud computing has transformed IT by enabling scalable, on-demand resource provisioning. However, its distributed nature brings significant security challenges, spanning confidentiality, integrity, availability, privacy, and regulatory compliance. This paper provides a pre-2019 overview of the primary security threats and risks in cloud environments—including multi-tenancy vulnerabilities, data breaches, insecure APIs, side-channel attacks, denial-ofservice (DoS), insider threats, and compliance issues. We examine mitigation strategies such as hypervisor hardening, encryption (at rest and in transit), identity and access management (IAM), intrusion detection systems (IDS), vulnerability scanning, auditing, and secure API usage. The research methodology involves a systematic literature review, threat-risk mapping, analysis of mitigation efficacy, and case study assessments. Key findings indicate that data encryption and strong IAM frameworks form foundational defenses; additionally, lightweight virtual machine introspection and IDS improve detection of anomalous behavior. However, mitigation is often bounded by performance overhead, key management complexity, and evolving attack surfaces. A typical workflow includes threat modeling, risk assessment, deployment of security controls, monitoring, and feedback-driven improvements. Advantages include scalable security, centralized policy enforcement, and compliance facilitation, while disadvantages encompass complexity, cloud provider trust issues, and potential single points of failure. Results suggest multi-layered defense-indepth frameworks are most effective, though response strategies must adapt to dynamic cloud architectures. The conclusion emphasizes the need for integrated security models and federated trust mechanisms. Future work could explore homomorphic encryption, secure multi-cloud orchestration, AI-based anomaly detection, and privacypreserving data analytics in the cloud. This paper synthesizes early insights and sets the foundation for evolving cloud security paradigms.
References
1. Ristenpart, T., Tromer, E., Shacham, H., & Savage, S. (2009). Hey, You, Get Off of My Cloud: Exploring Information Leakage in Third-Party Compute Clouds. Proceedings of the 16th ACM Conference on Computer and Communications Security.
2. Pfaff, B., Pettit, J., Koponen, T., et al. (2011). The Design and Implementation of Open vSwitch. USENIX Annual Technical Conference.
3. Kemerlis, V. P., Heiser, G., & Keromytis, A. D. (2012). Retrofitting Commodity Operating Systems to Monitor Memory Access. Proceedings of the ACM Symposium on Applied Computing.
4. Kandias, M., Virvilis, N., Gritzalis, S., & Lambrinoudakis, C. (2015). A Framework for Assessing Cloud Risks. IEEE Cloud Computing.
5. Fernandes, D. A. B., Soares, L. F. B., Gomes, J. V., Freire, M. M., & Inácio, P. R. M. (2014). Security Issues in Cloud Environments: a survey. International Journal of Information Security, 13(2), 113–170.
6. Pearson, S., & Benameur, A. (2010). Privacy, Security and Trust Issues Arising from Cloud Computing. 2010 IEEE Second International Conference on Cloud Computing Technology and Science.
7. Kumar, R., & Liu, L. (2012). Cloud Computing for Data-Intensive Applications: - Exploring the Applicability of Cloud to Intrusion Detection. IEEE Cloud Computing, 1(2), 28–39.
8. NIST SP 800-144. (2011). Guidelines on Security and Privacy in Public Cloud Computing.
9. ENISA (2015). Cloud Computing Risk Assessment.
