Nikolay Nikolaevich Kucherov

AR-RRNS: Configurable reliable distributed data storage systems for Internet of Things to ensure security

Abstract Benefits of Internet of Things and cloud–fog-edge computing are associated with the risks of confidentiality, integrity, and availability related with the loss of information, denial of access for a long time, information leakage, conspiracy and technical failures. In this article, we propose a configurable, reliable, and confidential distributed data storage scheme with the ability to process encrypted data and control results of computations. Our system utilizes Redundant Residue Number System (RRNS) with new method of error correction codes and secret sharing schemes. We introduce the concept of an approximate value of a rank of a number (AR), which allows us to reduce the computational complexity of the decoding from RNS to binary representation, and size of the coefficients. Based on the properties of the approximate value and arithmetic properties of RNS, we introduce AR-RRNS method for error detection, correction, and controlling computational results. We provide a theoretical basis to configure probability of information loss, data redundancy, speed of encoding and decoding to cope with different objective preferences, workloads, and storage properties. Theoretical analysis shows that by appropriate selection of RRNS parameters, the proposed scheme allows not only increasing safety, reliability, and reducing an overhead of data storage, but also processing of encrypted data.

The EC Sequences on Points of an Elliptic Curve Realization Using Neural Networks

This paper shows that pseudorandom number generator based on EC-sequence doesn’t satisfy the condition of Knuth k-distribution. A modified pseudorandom number generator on elliptic curve points built in neural network basis is proposed. The proposed generator allows to improve statistical properties of the sequence based on elliptic curve points so that it satisfies the condition of k-distribution i.e. the sequence is pseudorandom. Application of Neural network over a finite ring to arithmetic operations over finite field allows to increase the speed of pseudorandom number generator on elliptic curve points EC-256 by 1,73 times due to parallel structure.

The Effective Neural Network Implementation of the Secret Sharing Scheme with the Use of Matrix Projections on FPGA

In this paper neural network implementation of the modified secret sharing scheme based on a matrix projection is offered. Transition from a finite simple Galois field to a complex field allows to reduce by 16 times memory size, necessary for storage of the precalculated constants. Implementation of the modified secret sharing scheme based on a matrix projection with use of the neural network of a finite ring for execution of modular arithmetical addition and multiplication operations in a finite field allows to save on average 30% of the device area and increases the speed of scheme’s work on average by 17%.

Towards reliable low cost distributed storage in multi-clouds

We address the construction of a distributed cloud-based storage based on residual number system with modules of a special kind {2ⁿ − 3, 2ⁿ − 1, 2ⁿ + 1, 2ⁿ + 3} to provide reliability and safety of stored data. We show that the proposed scheme allows obtaining an improvement of the coding and decoding rates, and the speed of data loading and data access comparing with the fastest cloud service. The costs associated with data encoding and decoding are minimal.

Towards Mitigating Uncertainty of Data Security Breaches and Collusion in Cloud Computing

Cloud computing has become a part of peoples lives. However, there are many unresolved problems with security of this technology. According to the assessment of international experts in the field of security, there are risks in the appearance of cloud collusion in uncertain conditions. To mitigate this type of uncertainty, and minimize data redundancy of encryption together with harms caused by cloud collusion, modified threshold Asmuth-Bloom and weighted Mignotte secret sharing schemes are used. We show that if the villains do know the secret parts, and/or do not know the secret key, they cannot recuperate the secret. If the attackers do not know the required number of secret parts but know the secret key, the probability that they obtain the secret depends the size of the machine word in bits that is less than 1/2 ((l-1)). We demonstrate that the proposed scheme ensures security under several types of attacks. We propose four approaches to select weights for secret sharing schemes to optimize the system behavior based on data access speed: pessimistic, balanced, and optimistic, and on speed per price ratio. We use the approximate method to improve the detection, localization and error correction accuracy under cloud parameters uncertainty.

AC-RRNS: Anti-collusion secured data sharing scheme for cloud storage

Abstract Cloud security issues are important factors for data storage and processing. Apart from the existing security and reliability problems of traditional distributed computing, there are new security and reliability problems. They include attacks on a virtual machine, attacks on the synchronization keys, and so on. According to the assessment of international experts in the field of cloud security, there are risks of cloud collusion under uncertain conditions. To mitigate this type of uncertainty and reduce harms it can cause, we propose AC-RRNS algorithm based on modified threshold Asmuth–Bloom and Mignotte secret sharing schemes. We prove that the algorithm satisfies the formal definition of computational security. If the adversary coalition knows the secret shares, but does not know the secret key, the probability to obtain the secret is less than 1 / ( 2 l ⋅ ( k − 1 ) ( 2 l − k − 1 ) ) . The probability is less than 1 / 2 ( l − 1 ) with unknown secret shares and known secret key, and 1 / 2 l ⋅ k with unknown secret key. Its complexity is equal to brute-force method. We demonstrate that the proposed scheme ensures security under several types of attacks. We propose approaches for selection of parameters for AC-RRNS secret sharing scheme to optimize the system behavior and data redundancy of encryption.

The Data Transfer Development in MANET Networks on the Base of Chinese Remainder Theorem

In the paper the data transmission scheme in MANET networks constructed on the threshold secret sharing scheme (SSS) possessing the computation capability similar to Asmuth-Blum SSS, however code with the speed of t times more is proposed. The proposed SSS constructed on residue number system (RNS) allows to detect errors in communication channels using the error correction codes in RNS. From results of simulation it is possible to draw the conclusion that in case of identical occupied space the time delay of the approximate method when using modules of size to 64 bits is 20 % less, and when using modules of size more than 64 bits the time delay is 30 % less in comparison with method of orthogonal bases. The use of SSS constructed on RNS allows to develop reliable data transfer protocols in MANET networks. The neural network implementation of the approximate method is 10 % more effective than classical implementation of the approximate method.

Researches of Algorithm of PRNG on the Basis of Bilinear Pairing on Points of an Elliptic Curve with Use of a Neural Network

In this paper pseudorandom number generator based on elliptic curve bilinear pairing is developed. Residue number system and approximate method are used for effictive realization of modular operations over finite field that allows to increase the speed of pseudorandom number generator for \(-\)256 by 2,15 times compared to similar PRNG that uses positional notation. The developed pseudorandom number generator based on neural network has as good statistical properties as random sequences from site random.org and passes Diehard tests.