• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.878-881
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• 2009

As for the technology developed for network security, there is little difference of design ability between the domestic and the foreign studies. Although the development of 2048 RSA processor has been undergone, the processing speed does not meet the requirement due to its long width. These days, an RSA processor architecture with higher speed comsuming less resource is necessary. As for the development of RNG (Random Number Generator), the technology trend is moving from PRNG (Pseudo Random Number Generator) to TRNG (True Random Number Generator), also requiring less area and high speed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.9
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• pp.107-116
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• 1996

In the stochastic structure for doing exact calculationk, an input number must be changed to a pulse stream. Because the performance of random number generator (RNG) is controlled by its initial condition, we suggested newly modified cellular automata (MCA) which is uses a counter for boundary condition. We compared newly suggested MCA RNG to previously reported RNGs using the AND gate passing outputs which have the same meaning of multiplication in the stochastic calculation. In order to use stochastic we studied about the method, one large RNG can generate many small random numbers. In this method, RNG must have large drive capabilities for many input comparator. So we studied about drive capabilities using BiCMOS circuit and CMOS circit by SPICE.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.307-315
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• 2017

Random number generator(RNG) is essential in cryptographic applications. As recently a system using small devices such as IoT, Sensor Network, SmartHome appears, the lightweight cryptography suitable for this system is being developed. However due to resource limitations and difficulties in collecting the entropy, RNG designed for the desktop computer are hardly applicable to lightweight environment. In this paper, we propose a lightweight RNG to produce cryptographically strong random number using sensors. Our design uses a Hankel matrix, block cipher as the structure and sensors values as noise source. Futhermore, we implement the lightweight RNG in Arduino that is one of the most popular lightweight devices and estimate the entropy values of sensors and random number to demonstrate the effectiveness and the security of our design.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.427-440
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• 2003

Many mobile applications, such as games, security software and mathematical applications, use a random number generator(RNG). Since mobile devices operate under a limited battery capacity, the low energy consumption is one of key system requirements. For mobile applications based on an RNG, it is important to use low-power RNGs. In this article, we evaluate the energy efficiency of several well-known RNG algorithms and suggest guidelines for selecting RNGs suitable for mobile application.

• 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.

• Convergence Security Journal
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• v.12 no.4
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• pp.17-23
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• 2012

Recently, the research for cryptographic algorithm, in particular, a stream cipher has been actively conducted for wireless devices as growing use of wireless devices such as smartphone and tablet. LFSR based random number generator is widely used in stream cipher since it has simple architecture and it operates very fast. However, the conventional multi-LFSR RNG (random number generator) suffers from its hardware complexity as well as very closed correlation between the numbers generated. A leap-ahead LFSR was presented to solve these problems. However, it has another disadvantage that the maximum period of the generated random numbers are significantly decreased according to the relationship between the number of the stages of the LFSR and the number of the output bits of the RNG. This paper presents new leap-ahead LFSR architecture to prevent this decrease in the maximum period by applying segmentation technique to the conventional leap-ahead LFSR. The proposed architecture is implemented using VHDL and it is simulated in FPGA using Xilinx ISE 10.1, with a device Virtex 4, XC4VLX15. From the simulation results, the proposed architecture has only 20% hardware complexity but it can increases the maximum period of the generated random numbers by 40% compared to the conventional Leap-ahead archtecture.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.319-324
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• 1996

Using random pulse stream, a number can be transformed to the pulse stream with the probability value. So the digital value are computed by simple digital gates. Thus it will be possible to build a small and strong noise immunity processing element. We propose a faster convergence algorithm using a new methods for better performance of Random Number Generator(RNG) an the nonlinear transfer function(Sigmoid function)in this paper. And a feedback circuit were fitted for pulse stream in this paper. We proposed method is simulated with C program language and conformed by circuit implementation. Finally a system for hand written number recognition is constructed by FPGA and its performance verified.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.344-347
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• 2004

Critical cryptography applications require the production of an unpredictable and unbiased stream of binary data derived from a fundamental noise mechanism. In this paper, we proposed a RNG with Gaussian noise using filter algorithm. The proposed scheme is designed to reduce the statistical property of the biased bit stream in the output of a RNG. Experimental show that we analysis the loss rate according to window size and propose optimum window size.

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.383-392
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• 2018

For prompt gamma ray imaging for biomedical applications and environmental radiation monitoring, we propose herein a multiple-scattering Compton camera (MSCC). MSCC consists of three or more semiconductor layers with good energy resolution, and has potential for simultaneous detection and differentiation of multiple radio-isotopes based on the measured energies, as well as three-dimensional (3D) imaging of the radio-isotope distribution. In this study, we developed an analytic simulator and a 3D image generator for a MSCC, including the physical models of the radiation source emission and detection processes that can be utilized for geometry and performance prediction prior to the construction of a real system. The analytic simulator for a MSCC records coincidence detections of successive interactions in multiple detector layers. In the successive interaction processes, the emission direction of the incident gamma ray, the scattering angle, and the changed traveling path after the Compton scattering interaction in each detector, were determined by a conical surface uniform random number generator (RNG), and by a Klein-Nishina RNG. The 3D image generator has two functions: the recovery of the initial source energy spectrum and the 3D spatial distribution of the source. We evaluated the analytic simulator and image generator with two different energetic point radiation sources (Cs-137 and Co-60) and with an MSCC comprising three detector layers. The recovered initial energies of the incident radiations were well differentiated from the generated MSCC events. Correspondingly, we could obtain a multi-tracer image that combined the two differentiated images. The developed analytic simulator in this study emulated the randomness of the detection process of a multiple-scattering Compton camera, including the inherent degradation factors of the detectors, such as the limited spatial and energy resolutions. The Doppler-broadening effect owing to the momentum distribution of electrons in Compton scattering was not considered in the detection process because most interested isotopes for biomedical and environmental applications have high energies that are less sensitive to Doppler broadening. The analytic simulator and image generator for MSCC can be utilized to determine the optimal geometrical parameters, such as the distances between detectors and detector size, thus affecting the imaging performance of the Compton camera prior to the development of a real system.