Towards Ann-Based Scalable Hashing Algorithm For Secure Task Processing In Computational Clouds

Task processing security is a key challenge in large scale distributed environments such as computational clouds. Methods that guarantee the identification and integrity of the data are hash functions. Their computing load is high. Security models are expected to have an insignificant impact on the performance of the computing environment. In this paper, we have proposed the ANN-based model for scalable hashing of tasks results. The model is named Dynamic ANN-based Light Hashing Function. In the presented approach the hash length may be changed. The length of the hash affects the number of cryptographic operations performed and influences time devoted to the task processing. Therefore, applying hash having longer output allows loading the fast computing resources more. Using shorter hash length enables to unload the slow computing units. Our approach allows selecting such parameters of cryptographic algorithms that will not significantly affect the makespan of a task batch.