• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.41-45
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• 2002

From the paper which it sees a strong random number generator it uses a fuzzy set from 16 method of the statistical test which is a cryptograph random number test it verifies. 16 statistical test of NIST extends in crptograph and engineering whole it is a scale which is important distinguishes the distinction incapable characterstic of the random numbers which are used. To try introduce a fuzzy set the possibility of having a more strong randomness in order to be, it strengthens the function of the random number generator.

• 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.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.253-257
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• 2012

This paper presents an efficient filtering system for a metastable state-based true random number generator. To output a result with high randomness, we use loop-storage for storing the value of metastability. During the metastable state, the output value is accumulated to the storage. When the non-metastable state arises, the stored metastable value will be used for output instead of the result of the non-metastable state. As a result, we can maintain high entropy together with the original throughput.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.655-657
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• 2008

We suggest the digital voice encryption module using the pseudo random number generator and design the sorority device of a telephone using the module. The proposed method provides encryption method of the telephone against the third party. This encryption method uses pseudo random number generator which computes the encryption key using the shared secret key and the current time value.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1006-1009
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• 2008

We suggest the digital voice encryption module using the pseudo random number generator and design the security device of a telephone using the module. The proposed method provides encryption method of the telephone against the third party. This encryption method uses pseudo random number generator which computes the encryption key using the shared secret key and the current time value.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6161-6176
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• 2018

Pseudorandom numbers are useful in cryptographic operations for using as nonce, initial vector, secret key, etc. Security of the cryptosystem relies on the secret key parameters, so a good pseudorandom number is needed. In this paper, we have proposed a new approach for generation of pseudorandom number. This method uses the three dimensional combinational puzzle Rubik Cube for generation of random numbers. The number of possible combinations of the cube approximates to 43 quintillion. The large possible combination of the cube increases the complexity of brute force attack on the generator. The generator uses cryptographic hash function. Chaotic map is being employed for increasing random behavior. The pseudorandom sequence generated can be used for cryptographic applications. The generated sequences are tested for randomness using NIST Statistical Test Suite and other testing methods. The result of the tests and analysis proves that the generated sequences are random.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.7 no.3
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• pp.130-134
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• 1982

In computer communication network, it is assumed that blocks are served at a rate of u messages per sec. The message blocks will be stayed in the buffer during the service time. In this case, the probability density distribution of the number of message blocks in the buffer space has been studied. When the average buffer space needed is minimum, the average block size will be specified by the relation between the input data and link infromation length. This relation proves to be perfect. The random number generator for this probability distribution is designed. The test result by making use of the random number generator has shown that is has little difference from the theoretical one.

• 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 IKEEE
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• v.24 no.2
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• pp.543-549
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• 2020

As the importance of security increases in various fields, research on a random number generator (RNG) used for generating an encryption key, has been actively conducted. A high-quality RNG is essential to generate a high-performance encryption key, but the initial pseudo-random number generator (PRNG) has the possibility of predicting the encryption key from the outside even though a large amount of hardware resources are required to generate a sufficiently high-performance random number. Therefore, the demand of high-quality true random number generator (TRNG) generating random number through various noises is increasing. This paper examines and compares the representative TRNG methods based on metastable-based and ring-oscillator-based TRNGs. We compare the methods how the random sources are generated in each TRNG and evaluate its performances using NIST SP 800-22 tests.