Speculative Encryption on GPU Applied to Cryptographic File Systems

Due to the processing of cryptographic functions, Cryptographic File Systems (CFSs) may require significant processing capacity. Parallel processing techniques on CPUs or GPUs can be used to meet this demand. The CTR mode has two particularly useful features: the ability to be fully parallelizable and to perform the initial step of the encryption process ahead of time, generating encryption masks. This work presents an innovative approach in which the CTR mode is applied in the context of CFSs seeking to exploit these characteristics, including the anticipated production of the cipher masks (speculative encryption) in GPUs. Techniques that demonstrate how to deal with the issue of the generation, storage and management of nonces are presented, an essential component to the operation of the CTR mode in the context of CFSs. Related to GPU processing, our methods work to perform the handling of the encryption contexts and control the production of the masks, aiming to produce them with the adequate anticipation and overcome the extra latency due to encryption tasks. The techniques were applied in the implementation of EncFS++, a user space CFS. Performance analyzes showed that it was possible to achieve significant gains in throughput and CPU efficiency in several scenarios. They also demonstrated that GPU processing can be efficiently applied to CFS encryption workload even when working by encrypting small amounts of data (4 KiB), and in scenarios where higher speed/lower latency storage devices are used, such as SSDs or memory.