International Journal of Artificial Intelligence and Machine Learning
|
Volume 4, Issue 1, January 2024 | |
Research PaperOpenAccess | |
Secure AI Model Sharing: A Cryptographic Approach for Encrypted Model Exchange |
|
Bheema Shanker Neyigapula1* |
|
1Department of Information Technology, Jawaharlal Nehru Technological University, Kukatpally, Hyderabad 500085, Telangana, India. E-mail: bheemashankerneyigapula@gmail.com
*Corresponding Author | |
Int.Artif.Intell.&Mach.Learn. 4(1) (2024) 48-60, DOI: https://doi.org/10.51483/IJAIML.4.1.2024.48-60 | |
Received: 01/09/2023|Accepted: 11/12/2023|Published: 05/01/2024 |
The secure exchange of cryptographic keys is crucial for ensuring the confidentiality and integrity of AI models during sharing and collaboration. This research paper focuses on proposing a secure key exchange approach specifically tailored for encrypted model sharing. By addressing the key distribution problem inherent in AI model sharing, this approach establishes a secure and robust mechanism for exchanging cryptographic keys. The paper provides an overview of secure key exchange techniques, including public key cryptography, Diffie-Hellman key exchange, and elliptic curve cryptography, and discusses their application in the context of AI model sharing. The implementation details and evaluation results demonstrate the effectiveness and security of the proposed secure key exchange approach, offering a reliable solution for ensuring the confidentiality and integrity of shared AI models.
Keywords: Secure key exchange, AI model sharing, Encrypted model sharing, Confidentiality, Integrity, Security, Public key cryptography, Diffie-Hellman key exchange, Elliptic curve cryptography
Full text | Download |
Copyright © SvedbergOpen. All rights reserved