Adaptive encrypted cloud storage model

E. Lopez-Falcon; A. Tchernykh; N. Chervyakov; M. Babenko; E. Nepretimova; V. Miranda-López; A.Y. Drozdov; G. Radchenko; A. Avetisyan; Shaposhnikov S.

doi:10.1109/EIConRus.2018.8317099

Adaptive encrypted cloud storage model

E. Lopez-Falcon, A. Tchernykh, N. Chervyakov, M. Babenko, E. Nepretimova, V. Miranda-López, A.Y. Drozdov, G. Radchenko, A. Avetisyan, Shaposhnikov S.

Publikation: Konferenzbeitrag › Papier › Begutachtung

Abstract

In this paper, we propose an adaptive model of data storage in a heterogeneous distributed cloud environment. Our system utilizes the methods of secret sharing schemes and error correction codes based on Redundant Residue Number System (RRNS). We consider data uploading, storing and downloading. To minimize data access, we use data transfer mechanism between cloud providers. We provide theoretical analysis and experimental evaluation of our scheme with six real data storage providers. We show how dynamic adaptive strategies not only increase security, reliability, and reduction of data redundancy but allow processing encrypted data. We also discuss potentials of this approach, and address methods for mitigating the risks of confidentiality, integrity, and availability associated with the loss of information, denial of access for a long time, and information leakage. © 2018 IEEE.

Originalsprache	Englisch
Seiten	329-334
Seitenumfang	6
DOIs	https://doi.org/10.1109/EIConRus.2018.8317099
Publikationsstatus	Veröffentlicht - 2018
Veranstaltung	2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering - Saint Petersburg, Russland Dauer: 29 Jän. 2018 → 1 Feb. 2018

Konferenz

Konferenz	2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering
Kurztitel	ElConRus 2018
Land/Gebiet	Russland
Ort	Saint Petersburg
Zeitraum	29/01/18 → 1/02/18

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10.1109/EIConRus.2018.8317099

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Lopez-Falcon, E., Tchernykh, A., Chervyakov, N., Babenko, M., Nepretimova, E., Miranda-López, V., Drozdov, A. Y., Radchenko, G., Avetisyan, A., & S., S. (2018). Adaptive encrypted cloud storage model. 329-334. Beitrag in 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, Saint Petersburg, Russland. https://doi.org/10.1109/EIConRus.2018.8317099

@conference{4883289df97b4163baeea53c70e737b3,

title = "Adaptive encrypted cloud storage model",

abstract = "In this paper, we propose an adaptive model of data storage in a heterogeneous distributed cloud environment. Our system utilizes the methods of secret sharing schemes and error correction codes based on Redundant Residue Number System (RRNS). We consider data uploading, storing and downloading. To minimize data access, we use data transfer mechanism between cloud providers. We provide theoretical analysis and experimental evaluation of our scheme with six real data storage providers. We show how dynamic adaptive strategies not only increase security, reliability, and reduction of data redundancy but allow processing encrypted data. We also discuss potentials of this approach, and address methods for mitigating the risks of confidentiality, integrity, and availability associated with the loss of information, denial of access for a long time, and information leakage. {\textcopyright} 2018 IEEE.",

keywords = "cloud storage, Redundant Residue Number System, reliability, secret sharing schemes, security, Cryptography, Data handling, Data transfer, Error correction, Numbering systems, Redundancy, Reliability, Cloud storages, Error correction codes, Experimental evaluation, Information leakage, Redundant residue number systems, Secret sharing schemes, Transfer mechanisms, Digital storage",

author = "E. Lopez-Falcon and A. Tchernykh and N. Chervyakov and M. Babenko and E. Nepretimova and V. Miranda-L{\'o}pez and A.Y. Drozdov and G. Radchenko and A. Avetisyan and Shaposhnikov S.",

note = "Conference code: 135266 Cited By :5 Export Date: 27 August 2021 Funding details: Russian Foundation for Basic Research, RFBR, 18-07-01224 Funding details: Council on grants of the President of the Russian Federation, SP-1215.2016 Funding text 1: ACKNOWLEDGMENT The work is partially supported by Russian Federation President Grant SP-1215.2016, and Russian Foundation for Basic Research (RFBR) 18-07-01224.; 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2018 ; Conference date: 29-01-2018 Through 01-02-2018",

year = "2018",

doi = "10.1109/EIConRus.2018.8317099",

language = "English",

pages = "329--334",

}

Lopez-Falcon, E, Tchernykh, A, Chervyakov, N, Babenko, M, Nepretimova, E, Miranda-López, V, Drozdov, AY, Radchenko, G, Avetisyan, A & S., S 2018, 'Adaptive encrypted cloud storage model', Beitrag in 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, Saint Petersburg, Russland, 29/01/18 - 1/02/18 S. 329-334. https://doi.org/10.1109/EIConRus.2018.8317099

TY - CONF

T1 - Adaptive encrypted cloud storage model

AU - Lopez-Falcon, E.

AU - Tchernykh, A.

AU - Chervyakov, N.

AU - Babenko, M.

AU - Nepretimova, E.

AU - Miranda-López, V.

AU - Drozdov, A.Y.

AU - Radchenko, G.

AU - Avetisyan, A.

AU - S., Shaposhnikov

N1 - Conference code: 135266 Cited By :5 Export Date: 27 August 2021 Funding details: Russian Foundation for Basic Research, RFBR, 18-07-01224 Funding details: Council on grants of the President of the Russian Federation, SP-1215.2016 Funding text 1: ACKNOWLEDGMENT The work is partially supported by Russian Federation President Grant SP-1215.2016, and Russian Foundation for Basic Research (RFBR) 18-07-01224.

PY - 2018

Y1 - 2018

N2 - In this paper, we propose an adaptive model of data storage in a heterogeneous distributed cloud environment. Our system utilizes the methods of secret sharing schemes and error correction codes based on Redundant Residue Number System (RRNS). We consider data uploading, storing and downloading. To minimize data access, we use data transfer mechanism between cloud providers. We provide theoretical analysis and experimental evaluation of our scheme with six real data storage providers. We show how dynamic adaptive strategies not only increase security, reliability, and reduction of data redundancy but allow processing encrypted data. We also discuss potentials of this approach, and address methods for mitigating the risks of confidentiality, integrity, and availability associated with the loss of information, denial of access for a long time, and information leakage. © 2018 IEEE.

AB - In this paper, we propose an adaptive model of data storage in a heterogeneous distributed cloud environment. Our system utilizes the methods of secret sharing schemes and error correction codes based on Redundant Residue Number System (RRNS). We consider data uploading, storing and downloading. To minimize data access, we use data transfer mechanism between cloud providers. We provide theoretical analysis and experimental evaluation of our scheme with six real data storage providers. We show how dynamic adaptive strategies not only increase security, reliability, and reduction of data redundancy but allow processing encrypted data. We also discuss potentials of this approach, and address methods for mitigating the risks of confidentiality, integrity, and availability associated with the loss of information, denial of access for a long time, and information leakage. © 2018 IEEE.

KW - cloud storage

KW - Redundant Residue Number System

KW - reliability

KW - secret sharing schemes

KW - security

KW - Cryptography

KW - Data handling

KW - Data transfer

KW - Error correction

KW - Numbering systems

KW - Redundancy

KW - Reliability

KW - Cloud storages

KW - Error correction codes

KW - Experimental evaluation

KW - Information leakage

KW - Redundant residue number systems

KW - Secret sharing schemes

KW - Transfer mechanisms

KW - Digital storage

U2 - 10.1109/EIConRus.2018.8317099

DO - 10.1109/EIConRus.2018.8317099

M3 - Paper

SP - 329

EP - 334

T2 - 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering

Y2 - 29 January 2018 through 1 February 2018

ER -

Adaptive encrypted cloud storage model

Abstract

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