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Mikhail G. Babenko
Mikhail Grigorevich Babenko
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2020 – today
- 2024
- [j30]Egor M. Shiriaev
, Tatiana Ermakova
Reliablity and Security for Fog Computing Systems. Inf. 15(6): 317 (2024) - [j29]Egor M. Shiriaev
Analytical Review of Confidential Artificial Intelligence: Methods and Algorithms for Deployment in Cloud Computing. Program. Comput. Softw. 50(4): 304-314 (2024) - [j28]Maria A. Lapina, Egor M. Shiriaev, Mikhail G. Babenko, Ismoilzoda Istamov:
High-Speed Convolution Core Architecture for Privacy-Preserving Neural Networks. Program. Comput. Softw. 50(6): 417-424 (2024) - [c25]Bernardo Pulido-Gaytan, Andrei Tchemykh, Mikhail G. Babenko, Jorge M. Cortés-Mendoza, Horacio González-Vélez, Arutyun Avetisyan:
Enhancing Cloud Security through Efficient Polynomial Approximations for Homomorphic Evaluation of Neural Network Activation Functions. CCGridW 2024: 42-49 - 2023
- [j27]Georgii V. Valuev
Digital Filter Architecture Based on Modified Winograd Method F(2× 2, 5× 5) and Residue Number System. IEEE Access 11: 26807-26819 (2023) - [j26]Mikhail G. Babenko
A Comparative Study of Secure Outsourced Matrix Multiplication Based on Homomorphic Encryption. Big Data Cogn. Comput. 7(2): 84 (2023) - [j25]Egor M. Shiriaev
Fast Operation of Determining the Sign of a Number in RNS Using the Akushsky Core Function. Comput. 11(7): 124 (2023) - [j24]Andrei Gladkov, Egor M. Shiriaev, Andrei Tchernykh
DT-RRNS: Routing Protocol Design for Secure and Reliable Distributed Smart Sensors Communication Systems. Sensors 23(7): 3738 (2023) - 2022
- [j23]Mikhail G. Babenko
Improved Modular Division Implementation with the Akushsky Core Function. Comput. 10(1): 9 (2022) - [j22]Andrei Tchernykh
An Efficient Method for Comparing Numbers and Determining the Sign of a Number in RNS for Even Ranges. Comput. 10(2): 17 (2022) - [j21]Nikolay A. Vershkov
Optimization of Artificial Neural Networks using Wavelet Transforms. Program. Comput. Softw. 48(6): 376-384 (2022) - [j20]Andrei Gladkov, Viktor Andreevich Kuchukov, Mikhail G. Babenko, Andrei Tchernykh, Viktor Berezhnoy, Alexander Yu. Drozdov:
Modified Error Detection and Localization in the Residue Number System. Program. Comput. Softw. 48(8): 598-605 (2022) - [j19]Maria V. Valueva, Georgii V. Valuev, Mikhail G. Babenko, Andrei Tchernykh, Jorge M. Cortés-Mendoza
Method for Convolutional Neural Network Hardware Implementation Based on a Residue Number System. Program. Comput. Softw. 48(8): 735-744 (2022) - [c24]Andrei Gladkov
SNS-Based Secret Sharing Scheme for Security of Smart City Communication Systems. ICSC-Cities 2022: 248-263 - 2021
- [j18]Nikolay A. Vershkov
Optimization of Neural Network Training for Image Recognition Based on Trigonometric Polynomial Approximation. Program. Comput. Softw. 47(8): 830-838 (2021) - [j17]Mikhail G. Babenko
Algorithm for Constructing Modular Projections for Correcting Multiple Errors Based on a Redundant Residue Number System Using Maximum Likelihood Decoding. Program. Comput. Softw. 47(8): 839-848 (2021) - [j16]Luis Bernardo Pulido-Gaytan
Privacy-preserving neural networks with Homomorphic encryption: Challenges and opportunities. Peer-to-Peer Netw. Appl. 14(3): 1666-1691 (2021) - [c23]Jorge M. Cortés-Mendoza, Gleb I. Radchenko, Andrei Tchernykh, Bernardo Pulido-Gaytan
LR-GD-RNS: Enhanced Privacy-Preserving Logistic Regression Algorithms for Secure Deployment in Untrusted Environments. CCGRID 2021: 770-775 - [c22]Mikhail G. Babenko, Nikolay Nikolaevich Kucherov, Andrei Tchernykh, Viktor Andreevich Kuchukov, Elena Golimblevskaia, Ekaterina Kuchukova, Irina Vashchenko:
Determining the rank of a number in the residue number system. ICCS-DE 2021: 8-20 - [c21]Mikhail G. Babenko, Andrei Tchernykh, Aziz Redvanov, Anvar Djurabaev:
Comparative analysis of the scalar point multiplication algorithms in the NIST FIPS 186 elliptic curve cryptography. ICCS-DE 2021: 21-31 - [c20]Mikhail G. Babenko
RRNS Base Extension Error-Correcting Code for Performance Optimization of Scalable Reliable Distributed Cloud Data Storage. IPDPS Workshops 2021: 548-553 - [c19]Andrei Tchernykh
Cryptographic Primitives Optimization Based on the Concepts of the Residue Number System and Finite Ring Neural Network. OLA 2021: 241-253 - 2020
- [j15]Vanessa Miranda-López
2Lbp-RRNS: Two-Levels RRNS With Backpropagation for Increased Reliability and Privacy-Preserving of Secure Multi-Clouds Data Storage. IEEE Access 8: 199424-199439 (2020) - [j14]Andrei Tchernykh
Scalable Data Storage Design for Nonstationary IoT Environment With Adaptive Security and Reliability. IEEE Internet Things J. 7(10): 10171-10188 (2020) - [c18]Luis Bernardo Pulido-Gaytan
A Survey on Privacy-Preserving Machine Learning with Fully Homomorphic Encryption. CARLA 2020: 115-129 - [c17]Mikhail G. Babenko, Egor M. Shiriaev, Andrei Tchernykh, Elena Golimblevskaia:
Neural network method for base extension in residue number system. ICCS-DE 2020: 9-22 - [c16]Mikhail G. Babenko, Andrei Tchernykh, Elena Golimblevskaia, Nguyen Viet Hung, Vijay Chaurasiya:
Computationally secure threshold secret sharing scheme with minimal redundancy. ICCS-DE 2020: 23-32 - [c15]Nikolay Nikolaevich Kucherov, Mikhail G. Babenko, Andrei Tchernykh, Viktor Andreevich Kuchukov, Irina Vashchenko:
Increasing reliability and fault tolerance of a secure distributed cloud storage. ICCS-DE 2020: 166-180 - [c14]Jorge M. Cortés-Mendoza
Privacy-Preserving Logistic Regression as a Cloud Service Based on Residue Number System. RuSCDays 2020: 598-610
2010 – 2019
- 2019
- [j13]Andrei Tchernykh
Performance evaluation of secret sharing schemes with data recovery in secured and reliable heterogeneous multi-cloud storage. Clust. Comput. 22(4): 1173-1185 (2019) - [j12]Nikolay I. Chervyakov
AR-RRNS: Configurable reliable distributed data storage systems for Internet of Things to ensure security. Future Gener. Comput. Syst. 92: 1080-1092 (2019) - [j11]Andrei Tchernykh
Towards understanding uncertainty in cloud computing with risks of confidentiality, integrity, and availability. J. Comput. Sci. 36 (2019) - [j10]Mikhail G. Babenko
Positional Characteristics for Efficient Number Comparison over the Homomorphic Encryption. Program. Comput. Softw. 45(8): 532-543 (2019) - [c13]Luis Enrique García-Hernández
Multi-objective Configuration of a Secured Distributed Cloud Data Storage. CARLA 2019: 78-93 - [c12]Maxim Anatolievich Deryabin
Comparative Performance Analysis of Information Dispersal Methods. FRUCT 2019: 67-74 - [c11]Vanessa Miranda-López, Andrei Tchernykh
Weighted Two-Levels Secret Sharing Scheme for Multi-Clouds Data Storage with Increased Reliability. HPCS 2019: 915-922 - [c10]Andrei Tchernykh
Data Reliability and Redundancy Optimization of a Secure Multi-cloud Storage Under Uncertainty of Errors and Falsifications. IPDPS Workshops 2019: 565-572 - 2018
- [j9]Andrei Tchernykh
AC-RRNS: Anti-collusion secured data sharing scheme for cloud storage. Int. J. Approx. Reason. 102: 60-73 (2018) - [j8]Maxim Anatolievich Deryabin, Nikolay I. Chervyakov, Andrei Tchernykh, Mikhail G. Babenko, Maria Nikolaevna Shabalina:
High Performance Parallel Computing in Residue Number System. Int. J. Comb. Optim. Probl. Informatics 9(1): 62-67 (2018) - [j7]Anton S. Nazarov, Nikolay I. Chervyakov, Andrei Tchernykh, Mikhail G. Babenko:
Reliability Improvement of Information Systems by Residue Number System Code. Int. J. Comb. Optim. Probl. Informatics 9(1): 81-84 (2018) - [j6]Nikolay I. Chervyakov
The architecture of a fault-tolerant modular neurocomputer based on modular number projections. Neurocomputing 272: 96-107 (2018) - [j5]Nikolay I. Chervyakov
A new model to optimize the architecture of a fault-tolerant modular neurocomputer. Neurocomputing 303: 37-46 (2018) - [c9]Esteban C. Lopez-Falcon
Bi-objective Analysis of an Adaptive Secure Data Storage in a Multi-cloud. CARLA 2018: 307-321 - [c8]Maxim Anatolievich Deryabin
Secure Verifiable Secret Short Sharing Scheme for Multi-Cloud Storage. HPCS 2018: 700-706 - [c7]Andrei Tchernykh
WA-RRNS: Reliable Data Storage System Based on Multi-cloud. IPDPS Workshops 2018: 666-673 - 2017
- [j4]Nikolay I. Chervyakov
Residue-to-binary conversion for general moduli sets based on approximate Chinese remainder theorem. Int. J. Comput. Math. 94(9): 1833-1849 (2017) - [c6]Vanessa Miranda-López
Experimental Analysis of Secret Sharing Schemes for Cloud Storage Based on RNS. CARLA 2017: 370-383 - [c5]Andrei Tchernykh, Mikhail Grigorevich Babenko
Towards Mitigating Uncertainty of Data Security Breaches and Collusion in Cloud Computing. DEXA Workshops 2017: 137-141 - [c4]Mikhail Grigorevich Babenko
Unfairness Correction in P2P Grids Based on Residue Number System of a Special Form. DEXA Workshops 2017: 147-151 - 2016
- [j3]Nikolay I. Chervyakov
An efficient method of error correction in fault-tolerant modular neurocomputers. Neurocomputing 205: 32-44 (2016) - 2015
- [j2]Nikolay I. Chervyakov
Comparison of modular numbers based on the chinese remainder theorem with fractional values. Autom. Control. Comput. Sci. 49(6): 354-365 (2015) - [c3]Nikolay Ivanovich Chervyakov
The EC Sequences on Points of an Elliptic Curve Realization Using Neural Networks. AECIA 2015: 147-154 - [c2]Nikolay Ivanovich Chervyakov
Researches of Algorithm of PRNG on the Basis of Bilinear Pairing on Points of an Elliptic Curve with Use of a Neural Network. AECIA 2015: 167-173 - [c1]Nikolay Ivanovich Chervyakov
The Effective Neural Network Implementation of the Secret Sharing Scheme with the Use of Matrix Projections on FPGA. ICSI (3) 2015: 3-10 - 2014
- [j1]Nikolay I. Chervyakov
Digital filtering of images in a residue number system using finite-field wavelets. Autom. Control. Comput. Sci. 48(3): 180-189 (2014)
Coauthor Index
Nikolay I. Chervyakov
aka: Nikolay Ivanovich Chervyakov
aka: Nikolay Ivanovich Chervyakov
Maxim Anatolievich Deryabin
aka: Maxim Deryabin
aka: Maxim Deryabin
Luis Bernardo Pulido-Gaytan
aka: Bernardo Pulido-Gaytan
aka: Bernardo Pulido-Gaytan
Egor M. Shiriaev
aka: Egor M. Shiryaev
aka: Egor M. Shiryaev
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last updated on 2024-12-10 20:48 CET by the dblp team
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