Cloud data storage security based on cryptographic mechanisms. (La sécurité des données stockées dans un environnement cloud, basée sur des mécanismes cryptographiques)

Recent technological advances have given rise to the popularity and success of cloud. This new paradigm is gaining an expanding interest, since it provides cost efficient architectures that support the transmission, storage, and intensive computing of data. However, these promising storage services bring many challenging design issues, considerably due to the loss of data control. These challenges, namely data confidentiality and data integrity, have significant influence on the security and performances of the cloud system. This thesis aims at overcoming this trade-off, while considering two data security concerns. On one hand, we focus on data confidentiality preservation which becomes more complex with flexible data sharing among a dynamic group of users. It requires the secrecy of outsourced data and an efficient sharing of decrypting keys between different authorized users. For this purpose, we, first, proposed a new method relying on the use of ID-Based Cryptography (IBC), where each client acts as a Private Key Generator (PKG). That is, he generates his own public elements and derives his corresponding private key using a secret. Thanks to IBC properties, this contribution is shown to support data privacy and confidentiality, and to be resistant to unauthorized access to data during the sharing process, while considering two realistic threat models, namely an honest but curious server and a malicious user adversary. Second, we define CloudaSec, a public key based solution, which proposes the separation of subscription-based key management and confidentiality-oriented asymmetric encryption policies. That is, CloudaSec enables flexible and scalable deployment of the solution as well as strong security guarantees for outsourced data in cloud servers. Experimental results, under OpenStack Swift, have proven the efficiency of CloudaSec in scalable data sharing, while considering the impact of the cryptographic operations at the client side. On the other hand, we address the Proof of Data Possession (PDP) concern. In fact, the cloud customer should have an efficient way to perform periodical remote integrity verifications, without keeping the data locally, following three substantial aspects : security level, public verifiability, and performance. This concern is magnified by the client’s constrained storage and computation capabilities and the large size of outsourced data. In order to fulfill this security requirement, we first define a new zero-knowledge PDP proto- col that provides deterministic integrity verification guarantees, relying on the uniqueness of the Euclidean Division. These guarantees are considered as interesting, compared to several proposed schemes, presenting probabilistic approaches. Then, we propose SHoPS, a Set-Homomorphic Proof of Data Possession scheme, supporting the 3 levels of data verification. SHoPS enables the cloud client not only to obtain a proof of possession from the remote server, but also to verify that a given data file is distributed across multiple storage devices to achieve a certain desired level of fault tolerance. Indeed, we present the set homomorphism property, which extends malleability to set operations properties, such as union, intersection and inclusion. SHoPS presents high security level and low processing complexity. For instance, SHoPS saves energy within the cloud provider by distributing the computation over multiple nodes. Each node provides proofs of local data block sets. This is to make applicable, a resulting proof over sets of data blocks, satisfying several needs, such as, proofs aggregation