{"title":"Secure AI Model Sharing: A Cryptographic Approach for Encrypted Model Exchange","authors":"Bheema Shanker Neyigapula","doi":"10.51483/ijaiml.4.1.2024.48-60","DOIUrl":null,"url":null,"abstract":"The secure exchange of cryptographic keys is crucial for ensuring the conden-tiality and integrity of AI models during sharing and collaboration. This research paper focuses on proposing a secure key exchange approach speci�cally 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, Die-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 con�dentiality and integrity of shared AI models.","PeriodicalId":486534,"journal":{"name":"International Journal of Artificial Intelligence and Machine Learning","volume":"46 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Artificial Intelligence and Machine Learning","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.51483/ijaiml.4.1.2024.48-60","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The secure exchange of cryptographic keys is crucial for ensuring the conden-tiality and integrity of AI models during sharing and collaboration. This research paper focuses on proposing a secure key exchange approach speci�cally 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, Die-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 con�dentiality and integrity of shared AI models.