Assuring BetterTimes
We present a privacy-assured multiplication protocol using which an arbitrary arithmetic formula with inputs from two parties over a finite field can be jointly computed on encrypted data using an additively homomorphic encryption scheme. Our protocol is secure against malicious adversaries. To moti...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/22313
- Acceso en línea:
- https://doi.org/10.3233/JCS-171085
https://repository.urosario.edu.co/handle/10336/22313
- Palabra clave:
- Data privacy
Geometric applications
Ho-momorphic encryptions
Homomorphic Encryption Schemes
Location privacy
Malicious adversaries
Privacy enhancing technologies
Prototypical implementation
Secure multi-party computation
Cryptography
Location privacy
Privacy-enhancing technologies
Secure multi-party computation
- Rights
- License
- Abierto (Texto Completo)
| Summary: | We present a privacy-assured multiplication protocol using which an arbitrary arithmetic formula with inputs from two parties over a finite field can be jointly computed on encrypted data using an additively homomorphic encryption scheme. Our protocol is secure against malicious adversaries. To motivate and illustrate applications of this technique, we demonstrate an attack on a class of known protocols showing how to compromise location privacy of honest users by manipulating messages in protocols with additively homomorphic encryption. We demonstrate how to apply the technique in order to solve different problems in geometric applications. We evaluate our approach using a prototypical implementation. The results show that the added overhead of our approach is small compared to insecure outsourced multiplication. © 2018-IOS Press and the authors. All rights reserved. |
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