Digital Library of the European Council for Modelling and Simulation

Title:	Towards ANN-Based Scalable Hashing Algorithm For Secure Task Processing In Computational Clouds
Authors:	Jacek Tchorzewski, Agnieszka Jakobik, Daniel Grzonka
Published in:	(2019). ECMS 2019 Proceedings Edited by: Mauro Iacono, Francesco Palmieri, Marco Gribaudo, Massimo Ficco, European Council for Modeling and Simulation. DOI: http://doi.org/10.7148/2019 ISSN: 2522-2422 (ONLINE) ISSN: 2522-2414 (PRINT) ISSN: 2522-2430 (CD-ROM) 33rd International ECMS Conference on Modelling and Simulation, Caserta, Italy, June 11^th – June 14^th, 2019
Citation format:	Jacek Tchorzewski, Agnieszka Jakobik, Daniel Grzonka (2019). Towards ANN-Based Scalable Hashing Algorithm For Secure Task Processing In Computational Clouds, ECMS 2019 Proceedings Edited by: Mauro Iacono, Francesco Palmieri, Marco Gribaudo, Massimo Ficco European Council for Modeling and Simulation. doi: 10.7148/2019-0421
DOI:	https://doi.org/10.7148/2019-0421
Abstract:	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 comput-ing load is high. Security models are expected to have an insignificant impact on the performance of the com-puting environment. In this paper, we have proposed the ANN-based model for scalable hashing of tasks re-sults. 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. There-fore, 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 crypto-graphic algorithms that will not significantly affect the makespan of a task batch.
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