• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1998.12a
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• pp.421-441
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• 1998

본 논문에서는 스트림 암호 알고리즘과 블록 암호 알고리즘과 같은 비밀키 암호 시스템의 통계적 특성을 측정하기 위하여 사용된 여러 가지 randomness 테스트 방법들을 구현하여 그 성능을 randomness test의 power측면에서 서로 비교하였다. 여기서, power란 randomness test가 nonrandom한 비트 스트림을 얼마나 정확하게 검정할 수 있는 가를 나타내는 적도이다. 그리고, 스트림 암호 알고리즘과 블록 암호 알고리즘의 통계적 특성을 측정하기 위해 가장 효율적이라고 생각되는 테스트 방법들을 찾아 이 방법들을 사용할 것을 제안한다. 끝으로 제안된 방법들을 이용하여, DES, AES후보 알고리즘, SEED의 통계적 특성을 분석하였다.

• 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 Korea Game Society
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• v.21 no.1
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• pp.43-54
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• 2021

This study deals with the changes in negative emotions a player feels upon defeat according to the intensity of randomness. By changing the interface related to randomness, we checked how the interaction between the user and the game affects the user's experience. The subjects of this study were 30 students of the Dept. of Game Engineering. The research tool used randomness and negative emotion measurement tools. For the experiment, a board game called "12Janggi" was used, and randomness was added to the 'board' and 'piece' of the game. The analysis shows that proper randomness reduces negative emotions, but excessive randomness increases negative emotions. Although randomness can reduce the negative emotion of defeat, it can be seen that it should be applied to the context of the game.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1153-1165
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• 2009

There are many traditional statistical tests for randomness. We can consider recurrence plots as an exploratory graphical tool for evaluating randomness.

• School Mathematics
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• v.12 no.4
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• pp.455-471
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• 2010

Understanding of randomness is essential for learning and teaching of probability and statistics. Understanding of randomness prompts to understand natural and social phenomena from the point of view of mathematics, and plays a role of base in understanding of judgments based on rational interpretation on these phenomena. This study examined whether pre-service teachers recognize this, and they understand randomness included in various contexts. According to results, they did not have a understanding of randomness in the context related to measuring, while they grasped randomness in simple and joint events. This implies that they lack the understanding of variability which is essential in the context of measuring. This study, therefore, suggests that the settings of measuring should be introduced into probability and statistics education, especially that data from measuring should be analyzed focusing on the variability in the data set.

• Journal of the Korean Geosynthetics Society
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• v.21 no.3
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• pp.1-10
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• 2022

In this paper, the spatial randomness and probability characteristics of material properties are inversely estimated by using a set of the stochastic fields for the material properties of geotechnical structures. By using the probability distribution and probability characteristics of these estimated material properties, topology optimization is performed on structure shape, and the results are compared with the existing deterministic topology optimization results. A set of stochastic fields for material properties is generated, and the spatial randomness of material properties in each field is simulated. The probability distribution and probability characteristics of actual material properties are estimated using the partial values of material properties in each stochastic field. The probability characteristics of the estimated actual material properties are compared with those of the stochastic field set. Also, response variability of the ground structure having a modulus of elasticity with randomness is compared with response variability of the ground structure having a modulus of elasticity without randomness. Therefore, the quantified stochastic topology optimization result can be obtained with considering the spatial randomness of actual material properties.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.742-746
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• 2010

In this paper, we propose new randomness testing methods based on approximate periods in order to improve the previous randomness testing method using exact pattern matching. Finding approximate periods of random sequences enables us to search similarly repeated parts, but it has disadvantages since it takes long time. In this paper we propose randomness testing methods whose time complexity is O($n^2$) by reducing the time complexity of computing approximate periods from O($n^3$) to O($n^2$). Moreover, we perform some experiments to compare pseudo random number generated by AES cryptographic algorithms and true random number.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.6
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• pp.67-76
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• 2001

In this paper, we investigate criteria for evaluating cryptographic strength based on randomness testing of the advanced encryption standard candidates, which have conducted by NIST(National Institute of Standards & Technology). It is difficult to prove that a given cryptographic algorithm meets sufficient conditions or requirements for provable security. The statistical testing of random number generators is one of methods to evaluate cryptographic strength and is based on statistical properties of random number generators. We apply randomness testing on several cryptographic algorithms that have not been tested by NIST and find criteria for evaluating cryptographic strength from the results of randomness testing. We investigate two criteria, one is the number of rejected samples and the other is the p-value from p-values of the samples.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.979-983
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• 1989

This paper proposes a new concept, called merit factor Fr, for evaluating the randomness of binary random sequences. The merit factor Fr is obtained from the expected values of the autocorrelation function of the binary random sequence. Using this merit factor Fr, randomness of the binary random sequences generated by the random sampling method is evaluated.

• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.189-195
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• 1998

In this paper, we are concerned with the problem of testing the randomness of the coefficients in a first order autoregressive model. A consistent test based on prediction error is suggested. It is shown that under the null hypothesis, the test statistic is asymptotically normal.