Survey on Hybrid Cryptographic Models and Algorithm Rotation Strategies for Cloud Data Protection

Abstract

Cloud computing has emerged as a dominant paradigm for data storage and management, offering scalability, accessibility, and cost efficiency. However, the increasing reliance on cloud platforms raises significant concerns regarding data confidentiality, integrity, and resilience against evolving cryptographic attacks. This survey explores secure file storage in cloud environments through the integration of hybrid cryptography combined with algorithm rotation mechanisms. Hybrid cryptography leverages the strengths of symmetric algorithms for high-speed encryption and asymmetric algorithms for secure key exchange, thereby ensuring both efficiency and robustness. To further enhance security, algorithm rotation introduces dynamic switching between multiple encryption schemes, mitigating risks associated with algorithm obsolescence and cryptanalytic breakthroughs. The paper systematically reviews existing approaches to cloud data protection, evaluates the effectiveness of hybrid models, and highlights the role of algorithm rotation in sustaining long-term security. Comparative analysis of prior works demonstrates that combining hybrid cryptography with adaptive rotation significantly reduces vulnerabilities while maintaining performance scalability. This survey concludes by identifying open challenges, including computational overhead, interoperability, and key management complexities, and proposes future research directions toward resilient, adaptive, and standards-compliant secure cloud storage frameworks.

Introduction

The text discusses cloud computing security, emphasizing the importance of hybrid cryptography, algorithm rotation, and AI-driven techniques to protect sensitive data in distributed cloud environments. Traditional cryptographic methods struggle to balance performance, scalability, and resilience, prompting the adoption of combined approaches to ensure confidentiality, integrity, and trust.

Key Points:

1. Cloud Security Challenges:

   • Migration of sensitive data to third-party platforms raises concerns about confidentiality, integrity, and trust management.

   • Traditional cryptography alone may not handle evolving threats efficiently, creating a need for adaptive and hybrid solutions.

2. Hybrid Cryptography:

   • Combines symmetric encryption (e.g., AES) for fast bulk data protection with asymmetric encryption (e.g., RSA, ECC) for secure key management.

   • ECC-AES frameworks offer lightweight, efficient solutions suitable for mobile and edge devices, while RSA-AES balances performance and security in classical cloud environments.

   • Algorithm rotation strengthens security by dynamically switching cryptographic schemes to mitigate risks from outdated or vulnerable algorithms.

3. Algorithm Rotation and Quantum Threats:

   • Regularly updating key sizes and encryption algorithms addresses advances in computing power and cryptanalysis.

   • Shor’s quantum algorithms highlight vulnerabilities in RSA and ECC, emphasizing the need for quantum-resilient and post-quantum cryptography.

   • Bennett & Brassard’s quantum key distribution (QKD) offers secure alternatives but faces scalability challenges.

4. Auxiliary Security Mechanisms:

   • Hashing and authentication: HMAC ensures message integrity and authenticity.

   • Steganography: Conceals sensitive information within benign carriers to enhance security.

   • AI integration: AI models can optimize encryption strategies, detect anomalies, and manage algorithm rotation dynamically.

5. Foundational Contributions:

   • RSA, AES, and ECC provide the basis for hybrid encryption.

   • Identity-Based Encryption (IBE) enables user-specific access control and scalable key management.

   • SafeCurves and key size selection frameworks guide secure parameter selection.

6. Comparative Advantages and Limitations of Key Studies:

   • RSA-AES: Robust and well-established, but computationally intensive and vulnerable to quantum attacks.

   • ECC-AES: Efficient and lightweight for resource-constrained devices, but requires careful curve selection.

   • Algorithm rotation: Maintains long-term security but requires constant monitoring.

   • AI-driven cryptography and steganography: Adaptive and resilient but computationally demanding and potentially privacy-sensitive.

   • Quantum-resistant methods: QKD and post-quantum cryptography offer future-proofing but face practical deployment challenges.

7. Overall Insight:

   • Effective cloud security relies on integrated, multi-layered approaches combining classical cryptography, hybrid encryption, AI-driven optimization, and proactive defenses against quantum threats.

   • Future secure cloud frameworks will require adaptive, intelligent, and standard-compliant systems that balance performance, scalability, and resilience.

This study provides a comprehensive overview of current hybrid cryptography techniques, AI integration, algorithm rotation strategies, and quantum-resistant measures for robust cloud storage security.

Conclusion

Cloud computing has become the backbone of modern data storage and management, yet its widespread adoption continues to raise critical concerns regarding confidentiality, integrity, and resilience against evolving threats. This survey has examined the role of hybrid cryptography and algorithm rotation as complementary strategies for secure file storage in cloud environments. By integrating symmetric algorithms such as AES for efficient bulk encryption with asymmetric schemes like RSA and ECC for secure key exchange, hybrid models achieve a balance between performance and robustness. Furthermore, algorithm rotation introduces cryptographic agility, mitigating risks associated with algorithm obsolescence and preparing systems for quantum-era adversaries. The literature reviewed demonstrates that hybrid frameworks such as RSA–AES [2] and ECC–AES [3] provide scalable and efficient solutions, while key size selection [13] and Safe Curves analysis [12] highlight the importance of adaptive parameterization and secure curve choices. Auxiliary mechanisms including HMAC [10] and identity-based encryption [20] strengthen authentication and access control, while steganographic techniques [9], [19] offer concealment of sensitive metadata. Recent advances in AI-driven cryptographic monitoring [1], [11] further enhance adaptability by enabling intelligent anomaly detection and dynamic algorithm switching. Collectively, these contributions underscore the necessity of layered, adaptive, and intelligent approaches to cloud security. The comparative analysis revealed that while hybrid cryptography significantly improves efficiency and security, reliance on RSA introduces vulnerabilities in the quantum era, and ECC requires careful curve selection to avoid structural weaknesses. Algorithm rotation strategies address these limitations by ensuring long-term resilience, but they also introduce challenges in key management and interoperability. AI-driven enhancements promise automation and adaptability, though they raise concerns about computational overhead and privacy. These trade-offs highlight the importance of designing systems that balance security, performance, and usability. In conclusion, secure file storage in cloud environments demands a multi-faceted framework that combines hybrid cryptography, algorithm rotation, integrity verification, and adaptive intelligence. The integration of classical cryptographic foundations with modern innovations such as AI and steganography positions such systems to withstand both current and future threats. While challenges remain in computational efficiency, interoperability, and quantum resilience, the surveyed approaches collectively point toward a resilient, standards-compliant, and future-proof architecture for secure cloud storage. Future research should focus on optimizing algorithm rotation policies, integrating post-quantum cryptographic primitives, and leveraging AI for real-time security orchestration, thereby advancing the vision of truly adaptive and trustworthy cloud infrastructures.

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Copyright

Copyright © 2025 Mr. Rakesh K, Dr. S. Gunasekaran, Amruth Raj D, Pranith S, Rithik K , Sreyas B. 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.