• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.225-228
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• 2021

동형암호를 이용한 통계 분석은 기존의 개인정보보호 문제로 수행할 수 없었던 데이터에 대해서 통계분석이 가능하게 만든다. 본 논문에서는 대용량 데이터에 사용되는 대표적 통계 수치인 평균, 분산, 왜도, 첨도를 병렬처리를 사용하여 구하는 방법을 제안한다. 또한, 연산이 비교적 제한적인 동형암호에서도 통계적 수치를 구하기 위하여 동형암호문끼리의 뺄셈, 나눗셈, 제곱근 연산을 제안한다. 이를 통해, 분산된 대용량 데이터에 대해서도 동형암호를 통해 다양한 통계 연산이 가능할 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.137-139
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• 2023

양자 컴퓨터가 현대 암호 시스템의 보안성을 위협하고 있음에 따라, 최근 잠재적인 양자 공격들에 대한 분석 연구들이 다수 발표되고 있다. 공개키 암호인 RSA와 ECC의 경우, Shor 알고리즘에 의해 다항시간 내에 해결됨으로써 보안성이 완전히 붕괴되는 반면, 대칭키 암호는 Grover 알고리즘에 의해 보안 강도가 제곱근으로 감소하기 때문에 키 길이를 증가시킴으로써 기존 보안성을 복구할 수 있다. 이론적으로 Grover 알고리즘은 보안성을 훼손시키지만, 현실적인 공격 난이도가 매우 높음에 따라 대상 암호에 대한 양자 회로 최적화 구현이 중요하다. 이에 본 논문에서는 블록암호 RC5를 양자 회로 상에서 최적화하고 이를 기반으로 Grover 공격 비용을 추정한다. 마지막으로, 추정한 비용을 NIST의 양자 후 보안 강도 평가와 함께 비교함으로써 RC5에 대한 양자 암호 분석을 수행한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.119-122
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• 2023

양자 컴퓨터가 현대 암호 시스템의 보안성을 위협하고 있음에 따라, 최근 잠재적인 양자 공격들에 대한 분석 연구들이 다수 발표되고 있다. 공개키 암호인 RSA와 ECC의 경우, Shor 알고리즘에 의해 다항시간 내에 해결됨으로써 보안성이 완전히 붕괴되는 반면, 대칭키 암호는 Grover 알고리즘에 의해 보안 강도가 제곱근으로 감소하기 때문에 키 길이를 증가시킴으로써 기존 보안성을 복구할 수 있다. 이론적으로 Grover 알고리즘은 보안성을 훼손시키지만, 현실적인 공격 난이도가 매우 높음에 따라 대상 암호에 대한 양자 회로 최적화 구현이 중요하다. 이에 본 논문에서는 블록암호 RC5를 양자 회로 상에서 최적화하고 이를 기반으로 Grover 공격 비용을 추정한다. 마지막으로, 추정한 비용을 NIST의 양자 후 보안 강도 평가와 함께 비교함으로써 RC5에 대한 양자 암호 분석을 수행한다.

• Review of KIISC
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• v.34 no.2
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• pp.49-55
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• 2024

고전 컴퓨터에서 풀기 어려운 난제를 효율적으로 모델링하고 해결할 수 있는 양자 컴퓨터는 현재암호들을 위협하고 있다. 특히, 공개키 암호에 해당하는 RSA와 Elliptic Curve Cryptography (ECC)는 Shor의 양자 알고리즘에 의해 해당 암호들의 안전성이 기반이 되는 난제들을 다항 시간 내에 해결하여 새로운 양자 내성 암호가 필요한 상황이다. 이에 NIST는 양자내성암호 표준화 공모전을 주최함으로써 현재까지 표준화 작업을 이어나가고 있다. 대칭키 암호의 경우, Grover의양자 검색 알고리즘에 의해 고전 컴퓨터상에서 보장하던 보안 강도가 제곱근으로 감소되게 된다. 기존, 신규 암호 알고리즘 모두 양자 컴퓨터상에서의 보안 강도를 평가해야 되는 상황이며, 이에 NIST는 양자 후 보안 강도 기준을 도입하였다. 양자 후 보안 강도는 레벨 1에서 5로 정의되며, 각 레벨에는 AES 및 SHA-2/3에 대한 양자 해킹 비용이 지정되어있다. 본 논문에서는 이러한 암호 학계 상황에 따라, 대칭키 AES 및 해시 함수 SHA-2/3에 대한 해킹, 특히 양자 회로 구현 동향에 대해 살펴보고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.37-38
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• 2024

본 연구에서는 순천향대학교 천안병원에서 제2형 당뇨병 입원 환자를 대상으로 연속 혈당 측정기(CGM)를 통해 일주일 동안 수집된 101명의 혈당치 데이터를 사용하였다. 혈당치의 120분 동안 수집된 데이터를 기반으로 30분 후의 혈당치를 예측하는 트랜스포머 모델을 제안한다. 이는 트랜스포머의 인코더 모델만을 사용한 거보다 성능이 평균 제곱근 오차 (RMSE) 기준 약 4배 정도 향상하였으며, 이는 트랜스포머의 디코더 모델이 성능 향상에 효과적임을 보인다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.175-185
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• 2020

Three-dimensional registration is a process of matching data with or without a coordinate system to a reference coordinate system, which is used in various fields such as the absolute orientation of photogrammetry and data combining for producing precise road maps. Three-dimensional registration is divided into a method using points and a method using linear features. In the case of using points, it is difficult to find the same conjugate point when having different spatial resolutions. On the other hand, the use of linear feature has the advantage that the three-dimensional registration is possible by using not only the case where the spatial resolution is different but also the conjugate linear feature that is not the same starting point and ending point in point cloud type data. In this study, we proposed a method to determine the scale and the three-dimensional translation after determining the three-dimensional rotation angle between two data using quaternion to perform three-dimensional registration using linear features. For the verification of the proposed method, three-dimensional registration was performed using the linear features constructed an indoor and the linear features acquired through the terrestrial mobile mapping system in an outdoor environment. The experimental results showed that the mean square root error was 0.001054m and 0.000936m, respectively, when the scale was fixed and if not fixed, using indoor data. The results of the three-dimensional transformation in the 500m section using outdoor data showed that the mean square root error was 0.09412m when the six linear features were used, and the accuracy for producing precision maps was satisfied. In addition, in the experiment where the number of linear features was changed, it was found that nine linear features were sufficient for high-precision 3D transformation through almost no change in the root mean square error even when nine linear features or more linear features were used.

• Journal of the Korea Concrete Institute
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• v.21 no.3
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• pp.291-302
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• 2009

A compression lap splice can be calculated longer than a tension lap splice in high strength concrete according to current design codes. New criteria for the compression lap splice including the effects of concrete strength are required for practical purpose of ultra-high strength concrete. Characteristics of compression lap splice have been extensively investigated and main parameters are derived. In addition, an experimental study has been conducted with column specimens in concrete strength of 40 and 60 MPa. The strength of the compression lap splice consists of bond and end bearing and two contributors are combined. Therefore, combined action of bond and end bearing should be assessed. Compared with tension splices, concrete strength significantly affects the strength of compression splices due to short splice length and existence of end bearing. Test results show that the splice strength can be evaluated to be proportional to square root of compressive strength of concrete. The stress states of concrete surrounding spliced bars govern the strengths of bond and end bearing. Because the axial stress of the concrete is relatively high, the splice strength is not dependent on clear spacing. End bearing strength is not affected by splice length and clear spacing and is expressed with a function of the square root of concrete strength. The failure mode of specimens is similar to side-face blowout of pullout test of anchors and the strength of end bearing can be evaluated using the equation of side-face blowout strength. Because the stresses developed by bond in compression splices are nearly identical to those in tension splices, strength increment of compression splices is attributed to end bearing only.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.125-140
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• 2017

Until recently, regression based spatial interpolation methods and Kriging based spatial interpolation methods have been largely used to estimate land price or housing price, but less attention has been paid on comparing the performance of these spatial interpolation methods. In this regard, this research applied regression based spatial interpolators and Kriging based spatial interpolators for estimating the land prices in Dalseo-gu, Daegu metropolitan city and evaluated the accuracy of eight spatial interpolators. OLS, SLM, SEM, and GWR were used as regression based spatial interpolators while SK, OK, UK, and CK were employed as Kriging based spatial interpolators. The global accuracy was statistically evaluated by RMSE, adjusted RMSE, and COD. The relative accuracy was visually compared by three-dimensional residual error map and scatterplot. Results from statistical and visual analyses indicate that GWR reflecting the spatial non-stationarity was a relatively more accurate spatial predictor to estimate land prices in the study area than SAR and Kriging based spatial interpolators considering the spatial dependence. The findings from this research will contribute to the secondary research into analyzing the urban spatial structure with land prices.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.81-94
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• 2010

Input variable selection is one of the various techniques for improving the performance of artificial neural network. In this study, mutual information is applied for input variable selection technique instead of correlation coefficient that is widely used. Among 152 variables of RDAPS (Regional Data Assimilation and Prediction System) output results, input variables for artificial neural network are chosen by computing mutual information between rainfall records and RDAPS' variables. At first the rainfall forecast variable of RDAPS result, namely APCP, is included as input variable and the other input variables are selected according to the rank of mutual information and correlation coefficient. The input variables using mutual information are usually those variables about wind velocity such as D300, U925, etc. Several statistical error estimates show that the result from mutual information is generally more accurate than those from the previous research and correlation coefficient. In addition, the artificial neural network using input variables computed by mutual information can effectively reduce the relative errors corresponding to the high rainfall events.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.811-821
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• 2007

The intensity-duration-frequency (IDF) curves by Talbot, Sherman and Japanese type formulas are widely used in South Korea since the parameters are easily estimated. However, these IDF curves' accuracies are relatively worse than those of the IDF curves developed by Lee et al. (1993) and Heo et al. (1999), and different parameters for the given return periods should be computed. In this study, parameter estimation method for the IDF curve by Heo et al. (1999) is suggested using genetic algorithm (GA). Quantiles computed by at-site frequency analysis using the rainfall data of 22 rainfall gauges operated by Korea Meteorological Administration are employed to estimate the parameters of IDF curves and minimizing root mean squared error (RMSE) and relative RMSE (RRMSE) of observed and computed quantiles are used as objective functions of GA. The comparison of parameter estimation methods between the empirical regression analysis and the suggested method show that the IDF curve in which the parameters are estimated by GA using RRMSE as an objective function is superior to the IDF curves using RMSE.