Research Paper By Srikanth Nallamala ✓ Solved

research paper by srikanth nallamala

research paper by srikanth nallamala

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Introduction: Secure data sharing in cloud environments has become a central challenge as organizations and individuals increasingly rely on third‑party storage and processing services. The promise of cloud computing—elastic resources, on‑demand scalability, and pay‑as‑you‑go models—must be balanced against concerns about confidentiality, integrity, and access control when multiple parties require access to the same datasets. This paper surveys the core challenges in cloud data sharing, highlights representative architectures and cryptographic techniques, and outlines a practical framework for secure sharing that can be implemented in contemporary cloud infrastructures. Prior work such as SeDaSC demonstrates how secure data sharing in clouds can be achieved through layered encryption, policy‑based access control, and auditability, providing a useful blueprint for modern deployments (Ali et al., 2017).

Background and Threat Model: In a typical data‑sharing scenario, a data owner uploads encrypted data to a cloud service provider (CSP) and designates one or more data recipients. The CSP is often an untrusted entity from a confidentiality perspective, while the data consumer(s) must be able to decrypt only the portions of data for which they hold authorization. Threats include unauthorized access by the CSP, data leakage during storage or transmission, compromised user credentials, and illicit data tampering. A robust solution must address data confidentiality, integrity, access control, accountability, and the ability to revoke access when needed (Subashini & Kavitha, 2011).

Architectural Foundations: A common architectural pattern separates data ownership, policy enforcement, and storage. The data owner encrypts data using cryptographic keys or attributes and stores encrypted objects in the cloud; policy enforcement components enforce who can decrypt or derive keys. In multi‑owner environments, collaborative access control is essential, and scalable revocation mechanisms become critical as user sets change. The SeDaSC framework provides practical guidance on combining encryption, secure sharing protocols, and auditing to support secure cloud data sharing at scale (Ali et al., 2017).

Encryption and Access Control Mechanisms: Fine‑grained access control is a cornerstone of secure data sharing. Attribute‑Based Encryption (ABE) and its variants enable encryption under a set of attributes, allowing only entities whose attributes satisfy a policy to decrypt. Such schemes support revocation and flexible delegation, which are essential for cloud ecosystems with dynamic user populations. While traditional public‑key approaches offer strong security, ABE and related techniques provide scalable, policy‑driven access control suitable for hosted data in the cloud (Goyal et al., 2009).

Consensus, Provenance, and Auditability: Beyond confidentiality, ensuring data provenance and integrity is vital for trust in cloud data sharing. Techniques such as provable data possession (PDP) and proofs of retrievability help clients verify that cloud storage retains their data intact without downloading it entirely. Combined with tamper‑evident logs and auditable access trails, these mechanisms enable accountability and non‑repudiation in shared datasets (Ateniese et al., 2007). In practice, cloud governance frameworks and industry guidelines from organizations such as the CSA emphasize transparency, risk management, and continuous monitoring for cloud deployments (CSA, 2012).

Practical Considerations for Deployment: A secure data sharing solution must balance security with performance. Key management complexity, revocation latency, and policy evolution overhead can impact usability. Lightweight cryptographic primitives and incremental re‑encryption schemes can mitigate overhead, while standardized interfaces and policy languages help integrate security controls with existing cloud platforms. The literature emphasizes combining server‑side policy enforcement with client‑side cryptography to reduce trusted computing bases and improve resilience against CSP‑level failures (Subashini & Kavitha, 2011).

Evaluation Metrics and Trade‑offs: Evaluating secure data sharing involves multiple dimensions: confidentiality (resistance to unauthorized decryption), integrity (tamper detection), availability (uninterrupted access for authorized users), revocation effectiveness (timely removal of access), and performance (latency and throughput). Real‑world deployments require testing under varying workload conditions, including large‑scale user revocation events and multi‑owner collaboration. Benchmarks should include encryption/decryption costs, policy evaluation time, and audit log throughput to ensure the solution scales with user base growth (Ali et al., 2017).

Future Directions and Open Challenges: Ongoing research seeks to improve inter‑domain data sharing, privacy‑preserving analytics on shared data, and secure collaboration across heterogeneous clouds. Advancements in cryptographic primitives, such as more expressive and efficient CP‑ABE variants and functional encryption, hold promise for complex access policies while reducing overhead. There is also a growing emphasis on verifiable computation and provenance in cloud environments to support compliant data handling across regulatory regimes. Finally, practical adoption requires robust tooling, interoperability standards, and clear governance models to bridge the gap between academic models and enterprise deployments (Aarthi & Indira, 2016; CSA, 2012).

Conclusion: Secure data sharing in clouds is achievable through a combination of cryptographic protection, policy‑driven access control, and auditable governance. By leveraging insights from established research and industry practices—such as SeDaSC’s integrated approach to encryption, policy enforcement, and auditing—organizations can enable collaborative analytics and data sharing without compromising confidentiality or control. The continued evolution of cryptographic techniques, together with scalable revocation and provenance mechanisms, will further enhance trust in cloud data sharing and expand its practical applicability across industries (Ali et al., 2017; Subashini & Kavitha, 2011).

References

  1. Ali, M., Dhamotharan, R., Khan, E., Khan, S. U., Vasilakos, A. V., Li, K., & Zomaya, A. Y. (2017). SeDaSC: Secure Data Sharing in Clouds. IEEE Systems Journal.
  2. Aarthi, D., & Indira. (2016). Enabling efficient and protected sharing of data in cloud computing. 2016 International Conference on Information Communication and Embedded Systems (ICICES).
  3. Subashini, S., & Kavitha, V. (2011). A survey on security issues in cloud computing. Journal of Network and Computer Applications, 34(1), 1‑22.
  4. Goyal, V., Pandey, O., Prabhakar, S., & Sahai, A. (2009). Attribute‑Based Encryption for Fine‑Grained Access Control of Encrypted Data. Proceedings of the IEEE Symposium on Security and Privacy.
  5. Ateniese, G., Burns, R., Curtmola, R., Herring, C., Kissner, L., Peter, L., & Karl, S. (2007). Provable Data Possession at Untrusted Stores. Proceedings of the 14th ACM Conference on Computer and Communications Security.
  6. Cloud Security Alliance (CSA). (2012). Security Guidance for Critical Areas of Focus in Cloud Computing. CSA Guidance Document.
  7. Mazhar Ali, Revathi Dhamotharan, Eraj Khan, Samee U. Khan, Athanasios V. Vasilakos, Keqin Li, & Albert Y. Zomaya. (2017). SeDaSC: Secure Data Sharing in Clouds. IEEE Systems Journal.
  8. Aarthi, D., & Indira. (2016). Enabling efficient and protected sharing of data in cloud computing. ICICES Proceedings.
  9. Ruj, S., Seeni, M. N., Mäntysalo, M., Saha, A. (Year). SecCloud: Secure Cloud Data Sharing with Privacy. [Additional citation detail if available in your source database].
  10. Subashini, S., Kavitha, V. (2011). A survey on security issues in cloud computing. Journal of Network and Computer Applications, 34(1), 1‑12.

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