• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.541-546
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• 2003

We present a random bit generator that uses fingerprint image as the source of random, and the random bit generator is the first generator in the world that uses biometric information for the source of random in the world. The generator produces, on the average, 9,334 bits a fingerprint image in 0.03 second, and the produced bit sequence passes all 16 statistical tests that are recommended by NIST for testing the randomness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.4
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• pp.321-325
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• 2004

It is quite difficult to create an unbiased and stable random bit stream, as required for statistical randomness, when using a random generator with only a hardware component. In this paper, we studied to reduce the statistical property of the biased bit stream in the output of a real random number generator. The proposed scheme is enhanced the randomness of output bitstream, these test items are used by FIPS 140-1.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.3
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• pp.1-4
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• 2010

RS-485, communication bases from small network system must prepare in collision. The collision is that mean the data transfer breaks. For a stabilized communication chooses 1:N polling methods. But polling is low speed in addition to maybe overload Master device. So, usual N:N Prefers a communication. In this case, must be preparing to avoid collision or some solutions. Generally, to after collision retransmits after short time. It's called delay time for short time. When making a delay time, uses address of each systems. (Address of each node) If the many nodes collided, the each node has different delay time. When making a delay time, uses a usual random number. Making a random number is hard job. So uses a usual pseudorandom number. It is more difficult from small size MCU. The Chaos random number provides stabled value. Finally, when uses the Chaos random number, the stability and reliability of system get better.

• 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 Institute of Information Security & Cryptology
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• v.12 no.3
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• pp.77-85
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• 2002

A Research of binary random sequence generator that uses a linear shift register had been studied since the 1970s. These generators were used in stream cipher. In general, the binary random sequence generator consists of linear shift registers that generate sequences of maximum period and a nonlinear filter function or a nonlinear combination function to generate a sequence of high linear complexity. Therefore, To generate a sequence that have long period as well as high linear complexity becomes an important factor to estimate safety of stream cipher. Usually, the maximum period of the sequence generated by a linear feedback shift register with L resistors is less than or equal to $2^L$-1. In this paper, we propose new binary random sequence generator that consist of L registers and 2 sub-characteristic polynomials. According to an initial state vector, the least period of the sequence generated by the proposed generator is equal to or ions than it of the sequence created by the general linear feedback shift register, and its linear complexity is increased too.

• Convergence Security Journal
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• v.24 no.2
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• pp.123-132
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• 2024

In the era of the Internet of Things, 7 billion diverse devices have been interconnected worldwide. Ensuring information security across these varied devices is crucial in this hyper-connected age. To achieve essential security functions such as confidentiality, integrity, and authentication, it is imperative to implement true random number generators (TRNGs). Therefore, this study proposes a method to rapidly characterize the randomness of TRNGs. While there are international standards for formally characterizing the randomness of TRNGs, adhering to these standards often requires significant time and resources. This study aims to help TRNG developers enhance efficiency in both time and cost by characterizing rough randomness and unpredictability. Firstly, we propose applying auto-correlation and cross-correlation metrics for analog signals. Secondly, we suggest adopting joint entropy and mutual information metrics for digital signals.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.237-246
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• 1998

We put the pseudo-random number generator into catagories like MiCG, MuCG, URG, ICG, EICG, and test uniformity and independency by 10,000 times through n empirical trial after selecting this random number generator. Here, from a fraction of data(20, 40, 60, 80, 100) with a significance level of 0.1, 0.05 and 0.01, we drive cumulative frequency with K-S, $X^{2}$, poker, run, autocorrelation test. As a result from the uniformity and independency among five random number generators based on all these data, all random number generator except EICG passed uniformity and independency test, and the URG turn out to be excellent in periodicity.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.47-60
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• 2010

Randomness is a basic security evaluation item for the most cryptographic algorithms. NIST has proposed a statistical test suit for random number generators for cryptographic applications in the process of AES project. However the test suit of NIST is customized to block ciphers which have the same input and output lengths. It needs to revise NIST's test suit for key derivation functions which have multiple output blocks. In this paper we propose a revised method of NIST's statistical randomness test adequate to the most key derivation functions and some experimental results for key derivation functions of 3GSM and NIST.

• Journal of KIISE
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• v.42 no.12
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• pp.1467-1473
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• 2015

In this paper, we implemented a parallel random number generation program on GPU's, which are known for high performance computing, using LCG (Linear Congruential Generator). Random numbers are important in all fields requiring the use of randomness, and LCG is one of the most widely used methods for the generation of pseudo-random numbers. We explained the parallel program using the NVIDIA CUDA model and MPI(Message Passing Interface) and showed uniform distribution and performance results. We also used a Monte Carlo algorithm to calculate pi(${\pi}$) comparing the parallel random number generator with cuRAND, which is a CUDA library function, and showed that our program is much more efficient. Finally we compared performance results using multi-GPU's with those of ideal speedups.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1997.11a
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• pp.332-341
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• 1997

본 논문에서는 여러 난수열 발생기들의 안전성 평가를 위한 새로운 통계적 검정법을 소개한다. 검정에서 구현된 기본 개념은 다음 비트 검정 이론을 바탕으로 하였으며 전체 스트링과 스트링의 일부분에 관한 확률적 통계치가 주어진다면 이를 이용하여 추측할 수 있는 다음 비트들에 관한 정보를 얻을 수 있게 된다는 점을 이용하였다. 본 검정에서는 난수 발생기의 랜덤성 평가시 입력되는 스트링 크기의 크고 작음에 관계없이 모든 임의 길이의 스트링에 적용될 수 있도록 하였으며 이는 난수 발생기를 이용한 암호 시스템의 안전성 평가에 있어서 매우 유용하게 사용될 수 있을 것이다.