@article {10.3844/jcssp.2017.702.717,
article_type = {journal},
title = {A New Authentication and Homomorphic Encryption as a Service Model for Preserving Privacy in Clouds},
author = {Zkik, Karim and Tebaa, Maha and Tachihante, Tarik and Orhanou, Ghizlane},
volume = {13},
number = {12},
year = {2017},
month = {Nov},
pages = {702-717},
doi = {10.3844/jcssp.2017.702.717},
url = {https://thescipub.com/abstract/jcssp.2017.702.717},
abstract = {The security as a Service (SECaaS) is a new model which provides security solution to users through Cloud Computing. The maturity of Cloud Computing services makes possible the use of the SECaaS model. This new model offers huge benefits to users, such as Authentication as a Service (AaaS) and Encryption as a Service (ENCaaS). So, it can offer more security features, since it uses the resources of Clouds and it’s connected to the different security policy databases. While SECaaS offers to cloud users and companies a multitude of security services, it still remains very limited and several aspects of security are not covered by this model, especially the part concerning the privacy. In addition, SECaaS is a new model that is not yet correctly deployed and it is not sufficiently solicited by companies. On the other side, Homomorphic encryption is considered as a good solution to ensure the privacy for users using the cloud services because it permits to make calculation on cipher text and data without decrypting them, but this solution suffer from many limitations such as the key size, the high latency and some serious performance problems. The main idea of this paper it’s to propose a new security model to preserving user’s privacy using homomorphic encryption while bypassing its limitations. So, This paper proposes a framework for Authentication and Homomorphic Encryption (A-HEaaS) based on security as a Service model which permits a secure access to the Cloud servers and the use of homomorphic encryption for calculations on encrypted data. The paper describes the design of our model and gives an implementation of our framework on medical Data.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}