• Journal of Internet of Things and Convergence
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• v.2 no.1
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• pp.23-27
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• 2016

There is Generated Moire fringe by fresnel diffraction that explains one of light's physical phenomenon and interference. In this paper, we propose to generate true random numbers by Moire fringe should be used by not pseudo-random number in cryptosystem.

• Journal of IKEEE
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• v.24 no.1
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• pp.52-58
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• 2020

This paper describes a hardware implementation of a true random number generator (TRNG) for information security applications. A new approach for TRNG design was proposed by adopting random transition rules in cellular automata and applying different transition rules at every time step. The TRNG circuit was implemented on Spartan-6 FPGA device, and its hardware operation generating random data with 100 MHz clock frequency was verified. For the random data of 2×10⁷ bits extracted from the TRNG circuit implemented in FPGA device, the randomness characteristics of the generated random data was evaluated by the NIST SP 800-22 test suite, and all of the fifteen test items were found to meet the criteria. The TRNG in this paper was implemented with 139 slices of Spartan-6 FPGA device, and it offers 600 Mbps of the true random number generation with 100 MHz clock frequency.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.19-26
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• 2008

In this paper, we propose a dynamic prediction algorithm to predict the bond price using actual data set of treasure note (T-Note). The proposed algorithm is based on term structure model of the interest rates, which takes place in various financial modelling, such as the standard Gaussian Wiener process. To obtain cumulative distribution functions (CDFs) of actual data for the interest rate measurement used, we use the natural cubic spline (NCS) method, which is generally used as numerical methods for interpolation. Then we also use the random number generation scheme (RNGS) to calculate the pricing of bond through the obtained CDF. In empirical computer simulations, we show that the lower values of precision in the proposed prediction algorithm corresponds to sharper estimates. It is very reasonable on prediction.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1295-1299
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• 1990

A new method called random sampling method has been proposed for generation of binary random sequences. In this paper, a new concept, called merit factor Fn, is proposed for evaluating the randomness of the binary random sequences generated by the random sampling method. Using this merit factor Fn, some desirable conditions are investigated for uniform random numbers used in the random sampling method.

• Journal of the Korean Mathematical Society
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• v.50 no.4
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• pp.879-897
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• 2013

Shannon entropy is one of the widely used randomness measures especially for cryptographic applications. However, the conventional entropy tests are less sensitive to the inter-bit dependency in random samples. In this paper, we propose new online randomness test schemes for true random number generators (TRNGs) based on the mutual information between consecutive ${\kappa}$-bit output blocks for testing of inter-bit dependency in random samples. By estimating the block entropies of distinct lengths at the same time, it is possible to measure the mutual information, which is closely related to the amount of the statistical dependency between two consecutive data blocks. In addition, we propose a new estimation method for entropies, which accumulates intermediate values of the number of frequencies. The proposed method can estimate entropy with less samples than Maurer-Coron type entropy test can. By numerical simulations, it is shown that the new proposed scheme can be used as a reliable online entropy estimator for TRNGs used by cryptographic modules.

• ETRI Journal
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• v.42 no.6
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• pp.951-964
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• 2020

This paper presents a lightweight true random number generator (TRNG) using beta radiation that is useful for Internet of Things (IoT) security. In general, a random number generator (RNG) is required for all secure communication devices because random numbers are needed to generate encryption keys. Most RNGs are computer algorithms and use physical noise as their seed. However, it is difficult to obtain physical noise in small IoT devices. Since IoT security functions are required in almost all countries, IoT devices must be equipped with security algorithms that can pass the cryptographic module validation programs of each country. In this regard, it is very cumbersome to embed security algorithms, random number generation algorithms, and even physical noise sources in small IoT devices. Therefore, this paper introduces a lightweight TRNG comprising a thin-film beta-radiation source and integrated circuits (ICs). Although the ICs are currently being designed, the IC design was functionally verified at the board level. Our random numbers are output from a verification board and tested according to National Institute of Standards and Technology standards.

• Convergence Security Journal
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• v.15 no.7
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• pp.21-29
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• 2015

As the number of malicious Android applications increases rapidly, many automatic analysis systems are proposed. Hoping to trigger as many malicious behaviors as possible, the automatic analysis systems are adopting random touch generation modules. In this paper, we propose how to differentiate real human touches and randomly generated touches. Through experiments, we figured out that the distance between two consecutive human touches is shorter than that of random generation module. Also we found that the touch speed of human is also limited. In addition, humans rarely touch the outer area of smartphone screen. By using statistics of human smartphone touch, we developed an algorithm to differentiate between human touches and randomly generated touches. We hope this research will help enhance automatic Android app analysis systems.

• JOURNAL OF ELECTRICAL WORLD
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• no.4 s.124
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• pp.54-59
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• 1987

• JOURNAL OF ELECTRICAL WORLD
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• no.3 s.123
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• pp.44-48
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• 1987

• Journal of Animal Science and Technology
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• v.48 no.2
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• pp.143-150
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• 2006

The data were collected in the dairy herd improvement program from January 2000 to July 2005. Test data included 825,157 records of first parity and animals with both parents known were included. This study aimed to describe the effect of incomplete lactation records of latest generation to the change in sire's breeding value using Random Regression model (RRM) in genetic evaluation. Estimation of genetic parameter and breeding value for sire used REMLF90 and BLUPF90 program. The phenotypic value on the number of test day records between group TD11, TD8, TD5, TD2 showed no large differences. For all the group heritability of test day milk yield range from 0.30 to 0.36. However TD2 group showed low heritability the least test day recode on the latest generation. The correlation of above 50% between test day and TD11(0.610), TD8(0.616), TD5(0.661) and TD2(0.682) with different records in latest generation. Sire's rank of breeding value varied widely depending on the records on the number of lactation from start to the latest generation. Study showed that change in breeding value ranked if daughter's test recode more so it should have at least 5 test day records. The use of RRM in dairy cattle genetic evaluation would be desirable if complete lactation records for latest generation daughters of young bulls when selection for proven bulls. Random Regression model (RRM) require at least 5 test-day lactation recode.