Mechanisms and Challenges in Public Auditing for Cloud Computing

Abstract

Cloud computing has revolutionized data storage and processing by offering scalable, on-demand access to computing resources. However, outsourcing sensitive information to cloud service providers (CSPs) introduces critical challenges in ensuring data security and integrity. Public auditing mechanisms enable third-party auditors (TPAs) to verify the integrity of cloud-stored data without compromising data privacy. This paper explores public auditing in cloud computing, highlighting mechanisms, challenges, and recent developments, including blockchain integration, artificial intelligence (AI), and quantum-resistant cryptography. A comprehensive review of cryptographic techniques, auditing protocols, and privacy-preserving mechanisms is presented, along with an analysis of future trends and open research areas.

Introduction

1. Overview

Cloud computing offers scalable, flexible, and cost-effective access to computing resources, eliminating the need for large on-premise infrastructure. However, outsourcing data to cloud service providers (CSPs) introduces privacy and security risks, such as data breaches, unauthorized access, and server-side attacks. Users lose direct control over their data, making data integrity and trust critical issues.

2. Public Auditing: A Solution

Public auditing allows a Trusted Third-Party Auditor (TPA) to verify the integrity of cloud-stored data without exposing its content. It offers benefits like:

• Offloading verification from users.

• Ensuring data integrity without full data downloads.

• Maintaining performance and trust in CSPs.

3. Key Challenges

1. Data Integrity + Confidentiality: Ensuring correctness of data without revealing content.

2. Protection from Breaches: Detecting tampering or server misbehavior.

3. Efficiency: Auditing must be lightweight for low-power or IoT devices.

4. Dynamic Data: Supporting updates, insertions, and deletions efficiently.

5. Batch Auditing: Verifying multiple users’ data simultaneously.

6. Anti-Collusion: Preventing cooperation between CSPs and TPAs to falsify audits.

4. Public Auditing Models

• Traditional Auditing: User-verification, impractical for large-scale systems.

• TPA-Based Auditing: Delegated verification while maintaining privacy and efficiency.

• Public Auditing Types:

  • Privacy-Preserving: Uses cryptography to protect data content.

  • Batch Auditing: Efficient auditing for multiple datasets/users.

  • Dynamic Auditing: Maintains correctness during data changes.

  • Homomorphic Authenticators: Enable integrity checks on encrypted data.

5. Cryptographic Techniques

6. Recent Advancements

• AI-Driven Auditing: Detects anomalies using machine learning.

• Quantum-Resistant Cryptography: Prepares for future quantum threats.

• Edge/IoT Lightweight Auditing: Auditing protocols for resource-constrained environments.

• Blockchain for Group Auditing: Ensures privacy and accountability in shared data environments.

• Entangled Merkle Forests: Dynamic auditing with version control.

• Certificateless Cryptography: Solves key escrow issues in CPS and IIoT.

7. Remaining Challenges

• Efficiency vs. Privacy Trade-off: Balancing performance with privacy safeguards.

• Audit Log Integrity: Securing logs against tampering.

• Dynamic Data Handling: Ensuring real-time updates don’t require full re-audits.

• TPA Trust Issues: Preventing fraud or collusion with cloud providers.

• Scalability: Handling multi-user environments and large data volumes effectively.

8. Future Directions

• Decentralized Auditing: Using blockchain + federated learning to eliminate single points of failure.

• Audit-as-a-Service (AaaS): Modular, on-demand auditing tools in cloud environments.

• Confidential Computing Integration: Use of Trusted Execution Environments (TEEs) like Intel SGX for secure audit processing.

• Standardization & Interoperability: Creating unified frameworks for CSPs to ensure cross-platform auditability and compliance.

Conclusion

Public auditing is vital for maintaining trust, integrity, and transparency in cloud computing environments. With growing adoption of cloud services, the need for robust, privacy-preserving, and efficient auditing mechanisms has become increasingly important. Through advanced cryptographic techniques, integration with emerging technologies like blockchain and AI, and continued research into lightweight and scalable solutions, public auditing is evolving into a cornerstone of secure cloud computing. However, significant challenges remain, particularly in balancing privacy, performance, and security in large-scale, multi-user environments. Continued innovation and standardization will be key to ensuring trust and security in future cloud ecosystems.

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Copyright

Copyright © 2025 Abu Salim, Rajesh Kumar Tiwari, Aasif Aftab, Shams Tabrez Siddiqui. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.