Articles Open Access
Blockchain-Based Identity and Access Management for Secure Enterprise Cloud Applications
API Developer, France
Abstract
The rapid adoption of cloud computing in enterprise environments has increased the demand for secure, scalable, and reliable Identity and Access Management (IAM) systems. Traditional IAM solutions often rely on centralized architectures, which are vulnerable to cyberattacks, data breaches, insider threats, and single points of failure. Blockchain technology has emerged as a transformative solution capable of enhancing security, transparency, and decentralization in enterprise cloud applications. This research explores the implementation of blockchain-based IAM frameworks for secure enterprise cloud environments. The study examines how blockchain technology enables decentralized identity verification, immutable access records, and smart contract-based authentication mechanisms. By integrating blockchain with cloud-based IAM systems, enterprises can improve user authentication, ensure data integrity, and strengthen access control policies while reducing dependency on centralized authorities. The research further investigates various blockchain platforms, consensus mechanisms, and cryptographic techniques used in IAM solutions. Additionally, the paper evaluates the benefits, limitations, and implementation challenges associated with blockchain-enabled IAM models. The findings suggest that blockchain-based IAM systems provide enhanced security, trust, privacy protection, and operational efficiency for enterprise cloud applications. However, scalability, regulatory compliance, and integration complexity remain significant concerns that require further research and optimization for large-scale enterprise deployment.
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Publication Information
| Journal | International Research Journal of Innovative Engineering |
|---|---|
| Volume | 2 |
| Number | 2 |
| Pages | 1441-1450 |
| Published | 2018-03-05 |
| Issue | Vol. 2 No. 2 (2018): International Research Journal of Innovative Engineering (IRJIE) |
References
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35. Mathew, A. R. (2017). Cloud Technology and the Challenges for Forensics Investigators. DEStech Transactions on Computer Science and Engineering.
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39. Sugumar, R., Rengarajan, A., & Jayakumar, C. (2018). Trust based authentication technique for cluster based vehicular ad hoc networks (VANET). Wireless Networks, 24(2), 373-382.
40. Sudhan, S. K. H. H., & Kumar, S. S. (2015). An innovative proposal for secure cloud authentication using encrypted biometric authentication scheme. Indian Journal of Science and Technology, 8(35), 1-5.
41. Priya, P. S., & Sugumar, R. (2014). Multi Keyword Searching Techniques over Encrypted Cloud Data. In IJSR.
42. Chiranjeevi, K. G., Latha, R., & Kumar, S. S. (2016). Enlarge Storing Concept in an Efficient Handoff Allocation during Travel by Time Based Algorithm. Indian Journal of Science and Technology, 9, 40.
43. Amutha, M., & Sugumar, R. (2015). A survey on dynamic data replication system in cloud computing. International Journal of Innovative Research in Science, Engineering and Technology, 4(4), 1454-1467.
44. Sugumar, R. (2014). A technique to stock market prediction using fuzzy clustering and artificial neural networks.
45. Brijet, Z., Kumar, B. S., & Bharathi, N. (2017). Vehicle anti-theft system using fingerprint recognition technique. Open Academic Journal of Advanced Science and Technology, 1(1), 36-41.
46. Z. Brijet, N. Bharathi, G. Shanmugapriya. (2015). Design of Model Predictive Controller for Fluid Catalytic Cracking Unit. Fluid-IJCTA, 8(5), 1917-1926.
2. Ateniese, G., Mancini, L. V., Spognardi, A., Villani, A., Vitali, D., & Felici, G. (2014). Identity management and authentication in cloud computing. Computer Networks, 57(5), 145–156.
3. Bamiah, M., & Brohi, S. (2011). Seven deadly threats and vulnerabilities in cloud computing. International Journal of Advanced Engineering Sciences and Technologies, 9(1), 87–90.
4. Barker, E. (2016). Guideline for digital identity management. National Institute of Standards and Technology.
5. Benantar, M. (2011). Access control systems: Security, identity management and trust models. Springer.
6. Bhargavan, K., Fournet, C., Gordon, A., & Swamy, N. (2010). Verified implementations of authorization protocols. IEEE Symposium on Security and Privacy, 123–137.
7. Buyya, R., Broberg, J., & Goscinski, A. (2011). Cloud computing: Principles and paradigms. Wiley.
8. Cachin, C. (2016). Architecture of the Hyperledger blockchain fabric. IBM Research, 310.
9. Conti, M., Kumar, E. S., Lal, C., & Ruj, S. (2018). A survey on security and privacy issues of blockchain technology. IEEE Communications Surveys and Tutorials, 20(4), 3416–3452.
10. Ferraiolo, D., Kuhn, R., & Chandramouli, R. (2013). Role-based access control. Artech House.
11. Gai, K., Qiu, M., & Zhao, H. (2016). Privacy-preserving authentication schemes in cloud computing. Journal of Network and Computer Applications, 59, 12–22.
12. Hardjono, T., & Smith, N. (2016). Cloud-based commissioning of constrained devices using permissioned blockchains. ACM International Workshop on IoT Privacy, Trust, and Security, 29–36.
13. Hwang, K., Kulkarni, S., & Hu, Y. (2013). Cloud security with virtualized defense and reputation-based trust management. IEEE Transactions on Dependable and Secure Computing, 9(4), 545–560.
14. Juels, A., & Oprea, A. (2013). New approaches to security and availability for cloud data. Communications of the ACM, 56(2), 64–73.
15. Kshetri, N. (2017). Can blockchain strengthen the internet of things? IT Professional, 19(4), 68–72.
16. Li, M., Yu, S., Ren, K., & Lou, W. (2010). Securing personal health records in cloud computing. IEEE Transactions on Parallel and Distributed Systems, 24(1), 69–78.
17. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system.
18. Pahl, C., Zhang, X., & Helmer, S. (2012). Layered security for cloud applications. IEEE Transactions on Services Computing, 5(3), 341–355.
19. Ruj, S., Nayak, A., & Stojmenovic, I. (2011). Decentralized access control with anonymous authentication for securing cloud storage. IEEE Transactions on Parallel and Distributed Systems, 25(2), 384–394.
20. Zyskind, G., Nathan, O., & Pentland, A. (2015). Decentralizing privacy: Using blockchain to protect personal data. IEEE Security and Privacy Workshops, 180–184.
21. Mathew, A., & Asari, V. K. (2014, March). Rotation-invariant histogram features for threat object detection on pipeline right-of-way. In Video Surveillance and Transportation Imaging Applications 2014 (Vol. 9026, pp. 19-26). SPIE.
22. Sugumar, R., Rengarajan, A., & Jayakumar, C. (2015). Design a Weight Based Sorting Distortion Algorithm for Privacy Preserving Data Mining. Middle-East Journal of Scientific Research, 23(3), 405-412.
23. Karthika, V., Brijet, Z., & Bharathi, N. (2012). Design of optimal controller for fluid catalytic cracking unit. Procedia Engineering, 38, 1150-1160.
24. Amutha, M., & Sugumar, R. (2015). A survey on dynamic data replication system in cloud computing. International Journal of Innovative Research in Science, Engineering and Technology, 4(4), 1454-1467.
25. Sugumar, R. B., & Anandharaj, K. (2016). Assessment of Bacterial Load in the Fresh Water Lake System of Tamil Nadu. Interl J Curr Microbiol App Sci, 5(6), 236-246.
26. Rengarajan, R. S. A. (2016). Secure verification technique for defending IP spoofing attacks.
27. Mathew, A. R., & Al Hajj, A. (2017). Secure communications on IoT and big data. Indian Journal of Science and Technology, 10(11).
28. Alex, A. T., Asari, V. K., & Mathew, A. (2012, October). Gradient feature matching for expression invariant face recognition using single reference image. In 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 851-856). IEEE.
29. Sasidevi, J., Sugumar, R., & Priya, P. S. (2015). New-Multi-Phase Distribution Network Intrusion Detection. International Journal, 5(3).
30. Mathew, A., & Asari, V. K. (2013, March). Tracking small targets in wide area motion imagery data. In Video Surveillance and Transportation Imaging Applications (Vol. 8663, pp. 69-78). SPIE.
31. Sudhan, S. K. H. H., & Kumar, S. S. (2016). Gallant Use of Cloud by a Novel Framework of Encrypted Biometric Authentication and Multi Level Data Protection. Indian Journal of Science and Technology, 9, 44.
32. Alex, A. T., Asari, V. K., & Mathew, A. (2013, March). Gradient feature matching for in-plane rotation invariant face sketch recognition. In Image Processing: Machine Vision Applications VI (Vol. 8661, pp. 46-58). SPIE.
33. Natarajan, R., & Sugumar, R. (2014). A survey on attacks in web usage mining. International Journal of Innovative Research in Computer and Communication Engineering, 2(5), 4470-5.
34. Satyanarayana, D., Mathew, A. R., & Sathyashree, S. (2016). An Architecture for Wireless Communication Systems using Li-Fi technology. In 8th International Conference on Latest Trends in Engineering and Technology (ICLTET’2016) (pp. 37-41).
35. Mathew, A. R. (2017). Cloud Technology and the Challenges for Forensics Investigators. DEStech Transactions on Computer Science and Engineering.
36. Begum, R. S., & Sugumar, R. (2015). A Conceptual Comparison of Artificial Bee Colony and Particle Swarm Optimization.
37. Soundappan, S. J., & Sugumar, R. (2016). Optimal knowledge extraction technique based on hybridisation of improved artificial bee colony algorithm and cuckoo search algorithm. International Journal of Business Intelligence and Data Mining, 11(4), 338-356.
38. Singh, T. J., & Sugumar, R. (2012, December). An extensibility of THEMIS billing system for the cloud computing environment. In 2012 Fourth International Conference on Advanced Computing (ICoAC) (pp. 1-6). IEEE.
39. Sugumar, R., Rengarajan, A., & Jayakumar, C. (2018). Trust based authentication technique for cluster based vehicular ad hoc networks (VANET). Wireless Networks, 24(2), 373-382.
40. Sudhan, S. K. H. H., & Kumar, S. S. (2015). An innovative proposal for secure cloud authentication using encrypted biometric authentication scheme. Indian Journal of Science and Technology, 8(35), 1-5.
41. Priya, P. S., & Sugumar, R. (2014). Multi Keyword Searching Techniques over Encrypted Cloud Data. In IJSR.
42. Chiranjeevi, K. G., Latha, R., & Kumar, S. S. (2016). Enlarge Storing Concept in an Efficient Handoff Allocation during Travel by Time Based Algorithm. Indian Journal of Science and Technology, 9, 40.
43. Amutha, M., & Sugumar, R. (2015). A survey on dynamic data replication system in cloud computing. International Journal of Innovative Research in Science, Engineering and Technology, 4(4), 1454-1467.
44. Sugumar, R. (2014). A technique to stock market prediction using fuzzy clustering and artificial neural networks.
45. Brijet, Z., Kumar, B. S., & Bharathi, N. (2017). Vehicle anti-theft system using fingerprint recognition technique. Open Academic Journal of Advanced Science and Technology, 1(1), 36-41.
46. Z. Brijet, N. Bharathi, G. Shanmugapriya. (2015). Design of Model Predictive Controller for Fluid Catalytic Cracking Unit. Fluid-IJCTA, 8(5), 1917-1926.
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