IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

An End to End Cloud Computing Privacy Framework Using Blind Processing

An End to End Cloud Computing Privacy Framework Using Blind Processing
View Sample PDF
Author(s): Youssef Gahi (Ibn Tofail University, Kenitra, Morocco), Imane El Alaoui (Ibn Tofail University, Kenitra, Morocco)and Mouhcine Guennoun (Cisco Systems, Toronto, Canada)
Copyright: 2021
Pages: 22
Source title: Research Anthology on Privatizing and Securing Data
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-8954-0.ch019

Purchase

View An End to End Cloud Computing Privacy Framework Using Blind Processing on the publisher's website for pricing and purchasing information.

Abstract

Database-as-a-service (DBaaS) is a trend allowing organizations to outsource their databases and computations to external parties. However, despite the many advantages provided by this service in terms of cost reduction and efficiency, DBaaS raises many security issues regarding data privacy and access control. The protection of privacy has been addressed by several research contributions proposing efficient solutions such as encrypted databases and blind queries over encrypted data, called blind processing. In this latter context, almost all proposed schemes consider an architecture of a single user (the data owner) that requests the database server for encrypted records while he is the only one capable of decrypting. From a practical perspective, a database system is set up to support not only a single user but multiple users initiating multiple queries. However, managing various accesses to an encrypted database introduces several challenges by itself, like key sharing, key revocation, and data re-encryption. In this article, we propose a simple and efficient blind processing protocol that allows multiple users to query the same encrypted data and decrypt the retrieved results without getting access to the secret key.

Related Content

Chaymaâ Boutahiri, Ayoub Nouaiti, Aziz Bouazi, Abdallah Marhraoui Hsaini. © 2024. 14 pages.
Imane Cheikh, Khaoula Oulidi Omali, Mohammed Nabil Kabbaj, Mohammed Benbrahim. © 2024. 30 pages.
Tahiri Omar, Herrou Brahim, Sekkat Souhail, Khadiri Hassan. © 2024. 19 pages.
Sekkat Souhail, Ibtissam El Hassani, Anass Cherrafi. © 2024. 14 pages.
Meryeme Bououchma, Brahim Herrou. © 2024. 14 pages.
Touria Jdid, Idriss Chana, Aziz Bouazi, Mohammed Nabil Kabbaj, Mohammed Benbrahim. © 2024. 16 pages.
Houda Bentarki, Abdelkader Makhoute, Tőkési Karoly. © 2024. 10 pages.
Body Bottom