Szczegóły publikacji
Opis bibliograficzny
Towards ANN-based scalable hashing algorithm for secure task processing in computational clouds / Jacek TCHÓRZEWSKI, Agnieszka Jakóbik, Daniel Grzonka // W: ECMS 2019 : 33rd international ECMS conference on Modelling and simulation : June 11th–14th, 2019, Caserta, Italy / ed. by Mauro Iacono, [et al.]. — [Pontypridd] : European Council for Modelling and Simulation, cop. 2019. — (Proceedings (European Council for Modelling and Simulation) ; ISSN 2522-2414). — ISBN: 978-3-937436-65-4; e-ISBN: 978-3-937436-66-1. — S. 421–427. — Bibliogr. s. 427, Abstr. — Toż na dołączonym CD-ROMie. — J. Tchórzewski - dod. afiliacja: Cracow University of Technology
Autorzy (3)
- AGHTchórzewski Jacek
- Jakóbik Agnieszka
- Grzonka Daniel
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 124804 |
|---|---|
| Data dodania do BaDAP | 2019-09-30 |
| Rok publikacji | 2019 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Czasopismo/seria | Proceedings (European Council for Modelling and Simulation) |
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 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.