Cloud Storage Cost Modeling for Cryptographic File Systems

Nowadays, data security is a demand for companies when adopting storage services on public clouds. From long term persistence services, such as Amazon Glacier, to online block storage systems for virtual machines disks, security principles can be part of the cloud context, especially for customer's sensitive data. The confidentiality of storage services considers aspects such as data life-cycle, location, and size, besides that, this principle is often provided by a cryptography mechanism applied in one of the persistence layers, such as in the File-System (FS). However, to add cryptography for data security demands extra CPU cycles for ciphering the data during its persistence. Although these extra CPU cycles are not considered on current cloud costs estimations, it should be part of the total application execution's costs. This paper presents the architectures for Cryptography File Systems (CFS) adoption for data storing in cloud computing. Furthermore, a mathematical model is presented and discussed as an estimation tool of cryptography overhead when using CFSs in the cloud storage stack. The model is verified in a real scenario for estimating the total cost when adding security for storage in a cloud environment. As main result, the model could estimate the overhead within 90% to 92% of accuracy for the AES algorithm, according to real cases traces, considering available memory, {I/O} throughput and workload size.