Szczegóły publikacji

Opis bibliograficzny

An ANN-based scalable hashing algorithm for computational clouds with schedulers / Jacek TCHÓRZEWSKI, Agnieszka Jakóbik, Mauro Iacono // International Journal of Applied Mathematics and Computer Science ; ISSN 1641-876X. — 2021 — vol. 31 no. 4, s. 697–712. — Bibliogr. s. 709-711, Abstr. — J. Tchórzewski - dod. afiliacja: Cracow University of Technology

Autorzy (3)

Słowa kluczowe

hashing algorithmcomputational cloudartificial neural networktask schedulerscalable cryptography algorithm

Dane bibliometryczne

ID BaDAP139233
Data dodania do BaDAP2022-02-24
Tekst źródłowyURL
Rok publikacji2021
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Czasopismo/seriaInternational Journal of Applied Mathematics and Computer Science


The significant benefits of cloud computing (CC) resulted in an explosion of their usage in the last several years. From the security perspective, CC systems have to offer solutions that fulfil international standards and regulations. In this paper, we propose a model for a hash function having a scalable output. The model is based on an artificial neural network trained to mimic the chaotic behaviour of the Mackey–Glass time series. This hashing method can be used for data integrity checking and digital signature generation. It enables constructing cryptographic services according to the user requirements and time constraints due to scalable output. Extensive simulation experiments are conduced to prove its cryptographic strength, including three tests: a bit prediction test, a series test, and a Hamming distance test. Additionally, flexible hashing function performance tests are run using the CloudSim simulator mimicking a cloud with a global scheduler to investigate the possibility of idle time consumption of virtual machines that may be spent on the scalable hashing protocol. The results obtained show that the proposed hashing method can be used for building light cryptographic protocols. It also enables incorporating the integrity checking algorithm that lowers the idle time of virtual machines during batch task processing.

Publikacje, które mogą Cię zainteresować

fragment książki
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
fragment książki
Performance of computing hash-codes with chaotically-trained artificial neural networks / Jacek Tchórzewski, Aleksander BYRSKI // W: Computational Science – ICCS 2022 : 22nd international conference : London, UK, June 21–23, 2022 : proceedings, Pt. 2 / eds. Derek Groen, [et al.]. — Cham : Springer Nature Switzerland, cop. 2022. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 13351). — ISBN: 978-3-031-08753-0; e-ISBN: 978-3-031-08754-7. — S. 408–421. — Bibliogr., Abstr. — Publikacja dostępna online od: 2022-06-15. — J. Tchórzewski - afiliacja: Cracow University of Technology, Kraków