K-NN Classification under Homomorphic Encryption: Application on a Labeled Eigen Faces Dataset
Autor: | Nathalie Wehbe, Bechara Al Bouna, Mohamed Nassar |
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Rok vydání: | 2016 |
Předmět: |
Cloud computing security
Database Computer science business.industry Information sharing Data_MISCELLANEOUS Homomorphic encryption 020207 software engineering Context (language use) Cloud computing 02 engineering and technology Computer security computer.software_genre Encryption Server 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business computer |
Zdroj: | CSE/EUC/DCABES |
Popis: | The wide deployment of public cloud computing infrastructures has become an appealing solution for the advantages of flexibility and cost saving, but the risk of being exposed to privacy and security issues refrains a lot of customers from risking their sensitive data to the cloud. The data owners do not want to move to the cloud unless the data confidentiality and the privacy of their queries are guaranteed. How can we structure information sharing in the cloud between different parties and fully realize the benefits of cloud computing, and at the same time sensitive attributes/values are kept confidential except for the parties to whom they belong? In this context, we contribute a privacy preserving scheme for face recognition and classification in which a party willing to classify a face instance against a protected face database at the cloud would have this capability without revealing the instance to the cloud or revealing the database to the party. |
Databáze: | OpenAIRE |
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