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Mansi Ahirwar,
Dr. Manoj Tyagi,
- M.Tech scholar, Department of Computer Science and Engineering, Technocrats Institute of Technology, Anandnagar, Bhopal, Madhya Pradesh, India
- Professor, Department of Computer Science and Engineering, Technocrats Institute of Technology, Anandnagar, Bhopal, Madhya Pradesh, India
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The reliance of cloud computing on the data processing and storage structure creates serious security risks. Ensuring availability, security, and integrity of data in cloud settings becomes a challenge for both the individual and the enterprise. This paper will, therefore, introduce a novel Hybrid Cryptographic Framework that combines RSA, One-Time Pad (OTP), and AES as a means of enhancing data security in cloud storage. It employs RSA for secure key exchange, OTP for added entropy and security, and AES for efficient symmetric encryption. Another technique that enhances the security of data is a time-limited access control, limiting the access within some temporal bound. Such an approach is challenged with other cryptographic methods, such as RSA and AES, to prove how much more secure and performant it is, especially working with big information. All in all, a thorough analysis of encryption timings for various file sizes is provided, and utility of the framework in a cloud environment is proven. This hybrid approach is very suitable for secure storage of cloud data because the experimental results have established how much it reduces the execution time while enhancing security.
Keywords: Hybrid Cryptography, AES-OTP, RSA, Cloud Data Security, Temporal Access Control
[This article belongs to Current Trends in Signal Processing (ctsp)]
Mansi Ahirwar, Dr. Manoj Tyagi. A Novel Secure Cloud Storage Solution: Combining AES-OTP, RSA, and Time-Limited Access Control with Adaptive Key Management. Current Trends in Signal Processing. 2024; 14(03):11-20.
Mansi Ahirwar, Dr. Manoj Tyagi. A Novel Secure Cloud Storage Solution: Combining AES-OTP, RSA, and Time-Limited Access Control with Adaptive Key Management. Current Trends in Signal Processing. 2024; 14(03):11-20. Available from: https://journals.stmjournals.com/ctsp/article=2024/view=0
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Current Trends in Signal Processing
| Volume | 14 |
| Issue | 03 |
| Received | 28/09/2024 |
| Accepted | 14/10/2024 |
| Published | 18/11/2024 |