A Secure Random Number Generator with Immunity and Propagation Characteristics for Cryptography Functions

Saha, Rahul; Geetha, G.; Kumar, Gulshan; Buchanan, William J.; Kim, Tai-hoon

doi:10.3390/app11178073

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…Random numbers are required in multiple scientific fields, such as artificial neural networks [1-3], or evolutionary computing [4][5][6], but particularly in the case of cryptography, random numbers are crucial elements since their level of unpredictability can be used to determine the robustness of the security protocols implemented in a given communication system to prevent information from being compromised by attacks from a third party [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

True Random Number Generation Capability of a Ring Oscillator PUF for Reconfigurable Devices

et al. 2022

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This paper presents the validation of a novel approach for a true-random number generator (TRNG) based on a ring oscillator–physical unclonable function (RO-PUF) for FPGA devices. The proposal takes advantage of the different noise sources that affect the electronic implementation of the RO-PUF to extract the entropy required to guarantee its function as a TRNG, without anything more than minimal changes to the original design. The new RO-PUF/TRNG architecture has been incorporated within a hybrid HW/SW embedded system designed for devices from the Xilinx Zynq-7000 family. The degree of randomness of the generated bit streams was assessed using the NIST 800-22 statistical test suite, while the validation of the RO-PUF proposal as an entropy source was carried out by fulfilling the NIST 800-90b recommendation. The features of the hybrid system were exploited to carry out the evaluation and validation processes proposed by the NIST publications, online and on the same platform. To establish the optimal configuration to generate bit streams with the appropriate entropy level, a statistical study of the degree of randomness was performed for multiple TRNG approaches derived from the different implementation modes and configuration options available on the original RO-PUF design. The results show that the RO-PUF/TRNG design is suitable for secure cryptographic applications, doubling its functionality without compromising the resource–efficiency trade-off already achieved in the design.

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Section: Introductionmentioning

confidence: 99%

True Random Number Generation Capability of a Ring Oscillator PUF for Reconfigurable Devices

et al. 2022

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Design and Implementation of True Random Number Test Pattern Generator for Enhanced BIST Performance in Integrated Circuits

Mamatha,

Prithivirajan

2024

2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS)

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Application of Randomness for Security and Privacy in Multi-Party Computation

Saha,

Kumar,

Geetha

et al. 2024

IEEE Trans. Dependable and Secure Comput.

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A secure Multi-Party Computation (MPC) is one of the distributed computational methods, where it computes a function over the inputs given by more than one party jointly and keeps those inputs private from the parties involved in the process. Randomization in secret sharing leading to MPC is a requirement for privacy enhancements; however, most of the available MPC models use the trust assumptions of sharing and combining values. Thus, randomization in secret sharing and MPC modules is neglected. As a result, the available MPC models are prone to information leakage problems, where the models can reveal the partial values of the sharing secrets.In this paper, we propose the first model of utilizing a random function generator as an MPC primitive. More specifically, we analyze our previous development of the Symmetric Random Function Generator (SRFG) for information-theoretic security, where the system is considered to have unconditional security if it is secure against adversaries with unlimited computing resources and time. Further, we apply SRFG to eradicate the problem of information leakage in the general MPC model. Through a set of experiments, we show that SRFG is a function generator that can generate the combined functions (combination of logic GATEs) with n/2 -private to n-private norms. As the main goal of MPC is privacy preservation of the inputs, we analyze the applicability of SRFG properties in secret sharing and MPC and observe that SRFG is eligible to be a cryptographic primitive in MPC developments. We also measure the performance of our proposed SRFG-based MPC framework with the other randomness generation-based MPC frameworks and analyze the comparative attributes with the state-of-the-art models. We observe that our posed SRFG-based MPC is ≈ 30% better in terms of throughput and also shows 100% privacy attainment.

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A Secure Random Number Generator with Immunity and Propagation Characteristics for Cryptography Functions

Cited by 3 publications

References 38 publications

True Random Number Generation Capability of a Ring Oscillator PUF for Reconfigurable Devices

True Random Number Generation Capability of a Ring Oscillator PUF for Reconfigurable Devices

Design and Implementation of True Random Number Test Pattern Generator for Enhanced BIST Performance in Integrated Circuits

Application of Randomness for Security and Privacy in Multi-Party Computation

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