True random number generator based on ring oscillator PUF circuit

Buchovecká, Simona; Lórencz, Róbert; Kodýtek, Filip; Buček, Jiří

doi:10.1016/j.micpro.2017.06.021

Cited by 35 publications

(25 citation statements)

References 5 publications

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“…Liu, et al propose RO-based approach to generate true random numbers and show analysis of these numbers. Buchovecká, et al have produce and analyse real random numbers with a RO-based approach [18], [19]. Chen, et.…”

Section: R4mentioning

confidence: 99%

Secure and Efficient Hybrid Random Number Generator Based on Sponge Constructions for Cryptographic Applications

Yakut¹,

Tuncer²,

Özer³

2019

ELEKTRON ELEKTROTECH

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Random numbers constitute the most important part of many applications and have a vital importance in the security of these applications, especially in cryptography. Therefore, there is a need for secure random numbers to provide their security. This study is concerned with the development of a secure and efficient random number generator that is primarily intended for cryptographic applications. The generator consists of two subsystems. The first is algorithmic structure, Keccak, which is the latest standard for hash functions. The structure provides to generate secure random numbers. The second is additional input that generates with ring oscillators that are implemented on the FPGA. The additional inputs prevent reproduction and prediction of the subsequent random numbers. It is shown that the proposed generator is satisfies security requirements for cryptographic applications. In addition, NIST 800-22 test suite and autocorrelation test are used to demonstrate that generated random numbers have no statistical weaknesses and relationship among itself, respectively. Successful results from these tests show that generated numbers have no statistical weaknesses. Moreover, important advantage of the proposed generator is that it is more efficient than existing RNGs in the literature.

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Section: R4mentioning

confidence: 99%

Secure and Efficient Hybrid Random Number Generator Based on Sponge Constructions for Cryptographic Applications

Yakut¹,

Tuncer²,

Özer³

2019

ELEKTRON ELEKTROTECH

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“…For providing these basic requirements, FPGA hardware, in which cryptosystems can be applied as a whole, is a popular platform. Therefore, obtaining the noise source, which is the most critical design component of a TRNG, on these devices is a desired feature [9,10].…”

Section: Related Workmentioning

confidence: 99%

Implementation of a Digital TRNG Using Jitter Based Multiple Entropy Source on FPGA

Gari̇pcan

Erdem

2019

Informacije MIDEM

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In this study, hardware implementation and evaluation of a true random number generator (TRNG) is presented. For the implementation, Field Programmable Gate Array (FPGA) hardware, in which numerical processes based on an algorithmic basis are carried out, was used. In the system, ring oscillators (ROs) with similar structures were used as a noise source, and true randomness was obtained by sampling the jitter signals originating from the oscillators. However, the most critical cryptographic disadvantage of jitterbased TRNGs is the statistical inadequacy of the system. At this point, in contrast to existing designs, entropy sources derived from the subsets of ROs were used in the sampling and post-processing stage. The statistical quality of the system was improved by using true random numbers/inputs obtained from these entropy sources in the sampling and post-processing stage. With sampling and postprocessing inputs, the use of complex post-processing techniques that limit the output bit rate of the generator in the system was not required. Thus, a high-performance adaptable TRNG model with reduced hardware resource consumption is obtained. The statistical validation of the TRNG, which was tested in 6 different scenarios for two separate ring oscillator (RO) architectures and three different operating frequencies, was performed with the NIST 800-22 and AIS31 test packages.

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“…PRNG produces deterministic output by using algorithm whereas TRNG produces non-deterministic outputs that are based on entropy sources realized in hardware. The entropy can be extracted from hardware in a lot of ways and an example of it is by occurrence that are physically-based such as thermal noise and clock jitter [11].…”

Section: True Random Number Generatormentioning

confidence: 99%

Performance of Memristor Based Ring Oscillators True Random Number Generator for Energy Technology

Hashim,

Loong,

Hamid

2019

IJEAT

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We are living in an era where everything is trying to be more connected in terms of the different physical entities and its surrounding environment. This new concept that is developing called the Internet of Things (IoT) has garnered a lot of attention [Bodei, 2019 #45]. There are various of applications and smart objects associates with the IoT and this leads to an increase in security challenges. IoT security is very important but getting harder to achieve. One example of utilization of IoT is in the smart grid infrastructure and this in turn increases the need for network security. An integrated internet-based smart grid and energy resources also called Energy Internet (EI) has a lot of security challenges that comes with the current smart grid. Smart grid infrastructure and any means of energy that implements the internet system also known as Energy Internet (EI) has many security challenges that come with the current smart grid. A memristor based ring oscillator True Random Number Generator design has been proposed in this research as a solution that can combat security challenges that existed in the hardware implementation of devices. Inputs based on non-deterministic methods are being used in TRNGs to generate outputs that possessed randomness characteristics in applications of IoT that makes it secure. Complementary metal oxide semiconductor (CMOS) technology of 0.18 µm are being used in the TRNG design and a software of LT SPICE IV helps to realized it.The proposed TRNG design produced output that passed 10 out of the 15 NIST tests, therefore showed that the TRNG produce a fairly random output.

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True random number generator based on ring oscillator PUF circuit

Cited by 35 publications

References 5 publications

Secure and Efficient Hybrid Random Number Generator Based on Sponge Constructions for Cryptographic Applications

Secure and Efficient Hybrid Random Number Generator Based on Sponge Constructions for Cryptographic Applications

Implementation of a Digital TRNG Using Jitter Based Multiple Entropy Source on FPGA

Performance of Memristor Based Ring Oscillators True Random Number Generator for Energy Technology

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