Improving Fault Tolerance in Ad-Hoc Networks by Using Residue Number System

Barati, Ali; Dehghan, Mostafa; Movaghar, Ali; Barati, Hamid

doi:10.3923/jas.2008.3273.3278

Cited by 7 publications

(8 citation statements)

References 13 publications

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“…An alternative approach is to use 2L-RRNS. Given that the second-level modules act as an independent error correction code, this approach allows you to correct a larger number of errors [20] [21], as well as reduce the computational complexity of decoding [22] [23].…”

Section: B Error Correction Codementioning

confidence: 99%

“…Tchernykh et al [33] show how the security of stored data depends on the RRNS parameters. 2L-RRNS can increase the number of detected and correctable errors compared to 1L-RRNS [23]. Therefore, 2L-RRNS can ensure the reliability and integrity of stored data better than 1L-RRNS (see Sections III, IV).…”

Section: Distributed Storage Securitymentioning

confidence: 99%

“…The second aim is related to the reduction in the computational complexity of the error correction algorithm [37] [38] [17]. The third objective is associated with an increase in the number of correctable errors in RRNS [37] [38] [23].…”

mentioning

confidence: 99%

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2Lbp-RRNS: Two-Levels RRNS With Backpropagation for Increased Reliability and Privacy-Preserving of Secure Multi-Clouds Data Storage

et al. 2020

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Cloud storage as service is the mainstream technology used to retain digital data. However, there are significant risks for confidentiality, integrity, and availability violation associated with the loss of information, denial of access, technical failures, etc. In this article, we propose a two-level 2Lbp-RRNS scheme based on a Redundant Residue Number System with a backpropagation and hamming distance mechanisms for increasing reliability of a configurable and secure multi-cloud data storage. We provide a theoretical analysis of the 2Lbp-RRNS solution as an extension of the classical 2L-RRNS and a variant of fully homomorphic encryption for privacy-preserving, parallel processing, and scalability. We formulate, explain, and prove its main properties to extend existing knowledge within the limits of the critical bounding RRNS assumptions. We show that 2Lbp-RRNS can identify and recover more errors than traditional 2L-RRNS. We provide the upper bounds of the traditional threshold 2L-RRNS and our solution to estimate the number of detectable and correctable errors. We study various data access scenarios and show that it detects 1.58x and corrects 3.37x more errors than 2L-RRNS, on average. We also provide efficient implementations of encoding and decoding algorithms MRC8, and MRC16 based on the Mixed-Radix system, Finite Ring Neuronal Network, and signed binary window method. We evaluate encoding/decoding speeds using three algorithms: Mignotte, MRC8, and MRC16. The experimental system includes seven cloud storages: DropBox, GoogleDrive, OneDrive, Sharefile, Box, Egnyte, and Salesforce. To assess the efficiency of the system on real data, we vary scenarios of the first and second levels. The results show that our solution outperforms MRC8 by 2.53x (1.78x), and Mignotte by 4.83x (11.43x) for the encoding (decoding) speed, respectively.

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Section: B Error Correction Codementioning

confidence: 99%

Section: Distributed Storage Securitymentioning

confidence: 99%

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2Lbp-RRNS: Two-Levels RRNS With Backpropagation for Increased Reliability and Privacy-Preserving of Secure Multi-Clouds Data Storage

et al. 2020

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“…In statistical based approaches, the mean, variance and robust statistical parameters like mean of absolute deviation (MAD) are computed and then compared with a threshold to identify the status of a node [2]. The residue number system (RNS) is used as an error detection and correction tool in ad-hoc network [14]. In order to diagnose the intermittent faults, these testing processes need to be repeated as many times as data collected during the observation period.…”

Section: Introductionmentioning

confidence: 99%

Distributed Intermittent Fault Diagnosis in Wireless Sensor Network Using Likelihood Ratio Test

et al. 2023

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In current days, sensor nodes are deployed in hostile environments for various military and commercial applications. Sensor nodes are becoming faulty and having adverse effects in the network if they are not diagnosed and inform the fault status to other nodes. Fault diagnosis is difficult when the nodes behave faulty some times and provide good data at other times. The intermittent disturbances may be random or kind of spikes either in regular or irregular intervals. In literature, the fault diagnosis algorithms are based on statistical methods using repeated testing or machine learning. To avoid more complex and time consuming repeated test processes and computationally complex machine learning methods, we proposed a one shot likelihood ratio test (LRT) here to determine the fault status of the sensor node. The proposed method measures the statistics of the received data over a certain period of time and then compares the likelihood ratio with the threshold value associated with a certain tolerance limit. The simulation results using a real time data set shows that the new method provides better detection accuracy (DA) with minimum false positive rate (FPR) and false alarm rate (FAR) over the modified three sigma test. LRT based hybrid fault diagnosis method detecting the fault status of a sensor node in wireless sensor network (WSN) for real time measured data with 100% DA, 0% FAR and 0% FPR if the probability of the data from faulty node exceeds 25%.INDEX TERMS Wireless sensor network, intermittent fault, likelihood ratio test, fault diagnosis, distributed algorithm.

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“…The residue number system is a well studied number theory system, utilized in the field of computer arithmetic [ 20 ], and digital signal processing [ 21 , 22 ] applications to achieve performance upgrades through parallel computation.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation of Power Side-Channel Resistance for RNS Secure Logic

Selvam

Tyagi

2022

Sensors

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In this paper, residue number system (RNS) based logic is proposed as a protection against power side-channel attacks. Every input to RNS logic is encrypted as a share of the original input in the residue domain through modulus values. Most existing countermeasures enhance side-channel privacy by making the power trace statistically indistinguishable. The proposed RNS logic provides cryptographic privacy that also offers side-channel resistance. It also offers side-channel privacy by mapping different input bit values into similar bit encodings for the shares. This property is also captured as a symmetry measure in the paper. This side-channel resistance of the RNS secure logic is evaluated analytically and empirically. An analytical metric is developed to capture the conditional probability of the input bit state given the residue state visible to the adversary, but derived from hidden cryptographic secrets. The transition probability, normalized variance, and Kullback–Leibler (KL) divergence serve as side-channel metrics. The results show that our RNS secure logic provides better resistance against high-order side-channel attacks both in terms of power distribution uniformity and success rates of machine learning (ML)-based power side-channel attacks. We performed SPICE simulations on Montgomery modular multiplication and Arithmetic-style modular multiplication using the FreePDK 45 nm Technology library. The simulation results show that the side-channel security metrics using KL divergence are 0.0204 for Montgomery and 0.0020 for the Arithmetic-style implementation. This means that Arithmetic-style implementation has better side-channel resistance than the Montgomery implementation. In addition, we evaluated the security of the AES encryption with RNS secure logic on a Spartan-6 FPGA Board. Experimental results show that the protected AES circuit offers 79% higher resistance compared to the unprotected AES circuit.

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Improving Fault Tolerance in Ad-Hoc Networks by Using Residue Number System

Cited by 7 publications

References 13 publications

2Lbp-RRNS: Two-Levels RRNS With Backpropagation for Increased Reliability and Privacy-Preserving of Secure Multi-Clouds Data Storage

2Lbp-RRNS: Two-Levels RRNS With Backpropagation for Increased Reliability and Privacy-Preserving of Secure Multi-Clouds Data Storage

Distributed Intermittent Fault Diagnosis in Wireless Sensor Network Using Likelihood Ratio Test

An Evaluation of Power Side-Channel Resistance for RNS Secure Logic

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