<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</abstract>

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.

An ANN-based scalable hashing algorithm for computational clouds with schedulers

University of Campania “Luigi Vanvitelli”

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"An ANN-based scalable hashing algorithm for computational clouds with schedulers"}

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...

An ANN-based scalable hashing algorithm for computational clouds with schedulers

Online veröffentlicht: 30. Dez. 2021

Seitenbereich: 697 - 712

Eingereicht: 31. Jan. 2021

Akzeptiert: 10. Aug. 2021

DOI: https://doi.org/10.34768/amcs-2021-0048

Schlüsselwörter
hashing algorithm, artificial neural network, scalable cryptography algorithm, computational cloud, task scheduler

© 2021 Jacek Tchórzewski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

An ANN-based scalable hashing algorithm for computational clouds with schedulers

Online veröffentlicht: 30. Dez. 2021

Seitenbereich: 697 - 712

Eingereicht: 31. Jan. 2021

Akzeptiert: 10. Aug. 2021

DOI: https://doi.org/10.34768/amcs-2021-0048

Schlüsselwörterhashing algorithm, artificial neural network, scalable cryptography algorithm, computational cloud, task scheduler

© 2021 Jacek Tchórzewski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
hashing algorithm, artificial neural network, scalable cryptography algorithm, computational cloud, task scheduler