• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.599-602
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• 2003

A new technique is presented to construct predictive models of plasma etch processes. This was accomplished by combining a backpropagation neural network (BPNN) and a random generator (RC). The RG played a critical role to control neuron gradients in the hidden layer, The predictive model constructed in this way is referred to as a randomized BPNN (RG-BPNN). The proposed scheme was evaluated with a set of experimental plasma etch process data. The etch process was characterized by a 2$^3$ full factorial experiment. The etch responses modeled are 4, including aluminum (Al) etch rate, profile angle, Al selectivity, and do bias. Additional test data were prepared to evaluate model appropriateness. The performance of RC-BPNN was evaluated as a function of the number of hidden neurons and the range of gradient. for given range and hidden neurons, 100 sets of random neuron gradients were generated and among them one best set was selected for evaluation. Compared to the conventional BPNN, the proposed RC-BPNN demonstrated about 50％ improvements in all comparisons. This illustrates that the RG-BPNN of multi-valued gradients is an effective way to considerably improve the predictive ability of current BPNN of single-valued gradient.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.4
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• pp.418-424
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• 2010

Many researchers studied methods for the generation of maximum length pseudo random sequences. Sabater et al. analyzed shrunken sequences which are effectively generated by SG(Shrinking Generator) using CA(Cellular Automata). In this paper we propose a new SG which is called LCSG(LFSR and CA based Shrinking Generator) using an LFSR with control register and CA with generator register. The proposed shrunken sequences generated by LCSG have longer periods and high complexities than the shrunken sequences generated by the known method. And we analyze the generated sequences using LCSG.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.430-432
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• 2004

무선 센서 네트워크는 특정 관심 대상이나 환경으로부터 데이터를 수집하여 사용자에게 전달해 줌으로써 결정수단이나 연구를 목적으로 이용되어 지기 때문에 효과적인 보안이 요구되어 진다. 기존의 존재하는 많은 네트워크 보안은 센서 노드의 특성상 센서 네트워크에 적용될 수 없다 본 논문은 이런 센서 네트워크의 특성을 감안하여 대칭 키(symmetric key)를 기반으로 한 키(key) 관리 프로토콜을 제안한다. 제안 프로토콜은 키의 직접적인 이동 없이 마스터 키(Master Key), 의사 난수 생성기(Pseudo Random Number Generator:PRNG), 난수(Random Number:RN)의 조합을 통해 임의의 키를 생성함으로써 보안성을 강화함과 동시에, 다양한 통신 모델에서 사용되어지는 키들을 생성하고, 또한 통신 모델의 따라 프로토콜 축소와 확장이 가능하며, 다양한 네트워크 모델에 안도록 변형이 용이하게 설계되었다. 그리고 센서 노드의 에너지 소비를 감안하여 프로토콜 수행에 필요한 통신회수를 최소화하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.1001-1008
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• 2019

A high-quality pseudorandom sequence generation is an important part of many cryptographic applications, including encryption protocols. Therefore, a pseudorandom number generator (PRNG) is an essential element for generating key sequences in a cryptosystem. A PRNG must effectively generate a large, high-quality random data stream. It is well known that the bitstreams output by the CA-based PRNG are more random than the bitstreams output by the LFSR-based PRNG. In this paper, we prove that the complemented CA derived from 90/150 maximum length cellular automata(MLCA) is a MLCA to design a PRNG that can generate more secure bitstreams and extend the key space in a secret key cryptosystem. Also we give a method for calculating the cell positions outputting a nonlinear sequence with maximum period in complemented MLCA derived from a 90/150 MLCA and a complement vector.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.179-184
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• 2020

Cellular automata (CA), which is known as a pseudo random number generator due to its excellent randomness, has various applications. Cho et al. designed a CA-based shrinking generator to generate a long period of nonlinear sequence. In addition, chaotic cat maps have been studied by many researchers as the complex nonlinear dynamics systems with sensitivity in initial conditions and unpredictable characteristics. In this paper, we propose a new image encryption method using nonlinear sequence generated by CA-based shrinking generator with maximum period and 3D chaotic cat map for high security.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.11
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• pp.90-100
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• 1997

In this paper, we propose a new optical thresold generator as a key-stream genrator for stream cipher systems. The random key-bit stream is generated by a digital generator that is composed of LFSRs and nonlinear ligics. Digital implementatin of a key-stream generator requires large memory to implement programmable tapping points. This memory problem may be overcome easily by using the proposed optical system which has the proberty of 2D parallel processing.To implement hte threshold generator optically, we use conventional twisted nematic type SLMs (LCDs). This proposed system is based on the shadow casting technique for the AND operation between taps and sregister stages. It is also based on the proposed PMRS method for modulo 2 addition. The proposed PMRS method uses the property of light's polarization on LCD and can be implemented optically using one LCD and some mirrors. One of the major advantages of the proosed system is that there is no limitation of the number of the progarmmable tapping points. Therefore, the proposed system can be applied for the 2D encryption system which processes large amounts of data such as 2D images. We verify the proposed system with some simulation.

• Journal of KIISE
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• v.43 no.8
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• pp.910-918
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• 2016

A tensor is a multi-dimensional array that represents many data such as (user, user, time) in the social network system. A tensor generator is an important tool for multi-dimensional data mining research with various applications including simulation, multi-dimensional data modeling/understanding, and sampling/extrapolation. However, existing tensor generators cannot generate sparse tensors like real-world tensors that obey power law. In addition, they have limitations such as tensor sizes that can be processed and additional time required to upload generated tensor to distributed systems for further analysis. In this study, we propose TeT, a distributed tera-scale tensor generator to solve these problems. TeT generates sparse random tensor as well as sparse R-MAT and Kronecker tensor without any limitation on tensor sizes. In addition, a TeT-generated tensor is immediately ready for further tensor analysis on the same distributed system. The careful design of TeT facilitates nearly linear scalability on the number of machines.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.152-156
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• 2017

This paper introduces the concept of random security amplification to amplify security in a quantum key distribution system. It seems to provide security amplification using the relationship between quantum error correction and security. In addition;we show that random security amplification in terms of security amplification offers better security than using existing universal hash function. We explain how the universal hash function enhances security using the BB84 protocol, which is a typical example of QKD. Finally, the proposed random security amplification and the conventional scheme compare the security according to the key generation rate in the quantum QKD.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1539-1550
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• 2016

In modern society, the number of applications, which needs storage, is increased. Among them, the advance of FinTech increased the importance of storage encryption. FinTech storage, storing sensitive information, should be kept secure. Unless the storage is kept, many users will be damaged monetarily. To prevent this problem, we should encrypt the storage. A EncFS, which is one of the most popular storage encryption application, uses different IVs for each block to provide higher levels of security in the encryption algorithm. However, there is a vulnerability related to the usage of same IVs. In this paper, we propose a technique that decrypts the ciphertexts without knowing the secret key by using the vulnerability. Moreover, we show that the EncFS is not secure under IND-CPA model and propose a new scheme which is secure under IND-CPA model.

• Review of KIISC
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• v.2 no.2
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• pp.25-30
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• 1992

본 논제에서는 원시근과 이차 잉여규를 중심으로 관련되는 암호학에 이용을 언급하기로 한다. 이외에도 이산로그(discrete logarithm), 연분수(conti-nued fraction), 여러 부정방정식(diophantine equation)의 이론등이 암호학에서 빈번히 사용되는 알고리즘의 근간을 이루는 이론들로 알려져 있다. 또한, 유사임의 수열(pseudo-random number sequence)을 만들기 위한 생성자 (generator)들 중에는 정수론에 기초하고 있는 것들이 않이 있다. 제2절에서는 정수의 위수와 원시근에 대한 성질을 논하고, 제 3절에서는 2차 잉여류와 Legender 기호를 소개한 후, 제4절에서 이들이 주로 사용되는 암호학의 분야를 논하기로 한다.