• Title/Summary/Keyword: SEA 알고리즘

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On the SEA algorithm used in finding secure elliptic curves with an early-abort strategy (Early-abort 전략을 이용한 타원곡선 생성 알고리즘에 사용되는 SEA 알고리즘 연구)

  • 정배은;류희수
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.12 no.5
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    • pp.75-85
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    • 2002
  • In using elliptic curves in cryptography, it is important to find a secure elliptic curve. The security of elliptic curve cryptosystem is dependent on the cardinality of the given curve. So, it is necessary to count the number of points of a given elliptic curve to obtain secure curve. It is hewn that when the charateristic is two, the most efficient algorithm finding secure curves is combining the Satoh-FGH algorithm with early-abort strategy$^[1]$. In[1], the authors wrote that they modified SEA algorithm used in early-abort strategy, but they didn't describe the varaint of SEA algorithm. In this paper, we present some modifications of SEA algorithm and show the result of our implementation.

A Study on Efficient Signing Methods and Optimal Parameters Proposal for SeaSign Implementation (SeaSign에 대한 효율적인 서명 방법 및 최적 파라미터 제안 연구)

  • Suhri Kim
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.34 no.2
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    • pp.167-177
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    • 2024
  • This paper proposes optimization techniques for SeaSign, an isogeny-based digital signature algorithm. SeaSign combines class group actions of CSIDH with the Fiat-Shamir with abort. While CSIDH-based algorithms have regained attention due to polynomial time attacks for SIDH-based algorithms, SeaSiogn has not undergone significat optimization because of its inefficiency. In this paper, an efficient signing method for SeaSign is proposed. The proposed signing method is simple yet powerful, achived by repositioning the rejection sampling within the algorithm. Additionally, this paper presnts parameters that can provide optimal performance for the proposed algorithm. As a result, by using the original parameters of SeaSign, the proposed method is three times faster than the original SeaSign. Additonally, combining the newly suggested parameters with the signing method proposed in this paper yields a performance that is 290 times faster than the original SeaSign and 7.47 times faster than the method proposed by Decru et al.

Adaptive Sea Level Prediction Method Using Measured Data (관측치를 이용한 적응적 조위 예측 방법)

  • Park, Sang-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.5
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    • pp.891-898
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    • 2017
  • Climate changes consistently cause coastal accidents such as coastal flooding, so the studies on monitoring the marine environments are progressing to prevent and reduce the damage from coastal accidents. In this paper, we propose a new method to estimate the sea level which can be applied to the tidal sensors to monitor the variation of sea level. Existing sea level models are very complicated and need a lot of tidal data, so they are not proper for tidal sensors. On the other hand, the proposed algorithm is very simple but precise since we use the measured data from the sensor to estimate the sea level value in short period such as one or two hours. It is shown by experimental results that the proposed method is simple but predicts the sea level accurately.

A Development for Sea Surface Salinity Algorithm Using GOCI in the East China Sea (GOCI를 이용한 동중국해 표층 염분 산출 알고리즘 개발)

  • Kim, Dae-Won;Kim, So-Hyun;Jo, Young-Heon
    • Korean Journal of Remote Sensing
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    • v.37 no.5_2
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    • pp.1307-1315
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    • 2021
  • The Changjiang Diluted Water (CDW) spreads over the East China Sea every summer and significantly affects the sea surface salinity changes in the seas around Jeju Island and the southern coast of Korea peninsula. Sometimes its effect extends to the eastern coast of Korea peninsula through the Korea Strait. Specifically, the CDW has a significant impact on marine physics and ecology and causes damage to fisheries and aquaculture. However, due to the limited field surveys, continuous observation of the CDW in the East China Sea is practically difficult. Many studies have been conducted using satellite measurements to monitor CDW distribution in near-real time. In this study, an algorithm for estimating Sea Surface Salinity (SSS) in the East China Sea was developed using the Geostationary Ocean Color Imager (GOCI). The Multilayer Perceptron Neural Network (MPNN) method was employed for developing an algorithm, and Soil Moisture Active Passive (SMAP) SSS data was selected for the output. In the previous study, an algorithm for estimating SSS using GOCI was trained by 2016 observation data. By comparison, the train data period was extended from 2015 to 2020 to improve the algorithm performance. The validation results with the National Institute of Fisheries Science (NIFS) serial oceanographic observation data from 2011 to 2019 show 0.61 of coefficient of determination (R2) and 1.08 psu of Root Mean Square Errors (RMSE). This study was carried out to develop an algorithm for monitoring the surface salinity of the East China Sea using GOCI and is expected to contribute to the development of the algorithm for estimating SSS by using GOCI-II.

Development $K_d({\lambda})$ and Visibility Algorithm for Ocean Color Sensor Around the Central Coasts of the Yellow Sea (황해 중부 연안 해역에서의 해색센서용 하향 확산 감쇠계수 및 수중시계 추정 알고리즘 개발)

  • Min, Jee-Eun;Ahn, Yu-Hwan;Lee, Kyu-Sung;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.23 no.4
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    • pp.311-321
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    • 2007
  • The diffuse attenuation coefficient for down-welling irradiance $K_d({\lambda})$, which is the propagation of down-welling irradiance at wavelength ${\lambda}$ from surface to a depth (z) in the ocean, and underwater visibility are important optical parameters for ocean studies. There have been several studies on $K_d({\lambda})$ and underwater visibility around the world, but only a few studies have focused on these properties in the Korean sea. Therefore, in the present study, we studied $K_d({\lambda})$ and underwater visibility around the coastal area of the Yellow Sea, and developed $K_d({\lambda})$ and underwater visibility algorithms for ocean color satellite sensor. For this research we conducted a field campaign around the Yellow Sea from $19{\sim}22$ September, 2006 and there we obtained a set of ocean optical and environmental data. From these datasets the $K_d({\lambda})$ and underwater visibility algorithms were empirically derived and compared with the existing NASA SeaWiFS $K_d({\lambda})$ algorithm and NRL (Naval Research Laboratory) underwater visibility algorithm. Such comparisons over a turbid area showed small difference in the $K_d({\lambda})$ algorithm and constants of our result for underwater visibility algorithm showed slightly higher values.

Comparison of Algorithms for Sea Surface Current Retrieval using Himawari-8/AHI Data (Himawari-8/AHI 자료를 활용한 표층 해류 산출 알고리즘 비교)

  • Kim, Hee-Ae;Park, Kyung-Ae;Park, Ji-Eun
    • Korean Journal of Remote Sensing
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    • v.32 no.6
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    • pp.589-601
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    • 2016
  • Sea surface currents were estimated by applying the Maximum Cross Correlation (MCC), Zero-mean Sum of Absolute Distances (ZSAD), and Zero-mean Sum of Squared Distances (ZSSD) algorithms to Himawari-8/Advanced Himawari Imager (AHI) thermal infrared channel data, and the comparative analysis was performed between the results of these algorithms. The sea surface currents of the Kuroshio Current region that were retrieved using each algorithm showed similar results. The ratio of errors to the total number of estimated surface current vectors had little difference according to the algorithms, and the time required for sea surface current calculation was reduced by 24% and 18%, relative to the MCC algorithm, for the ZSAD and ZSSD algorithms, respectively. The estimated surface currents were validated against those from satellite-tracked surface drifter and altimeter data, and the accuracy evaluation of these algorithms showed results within similar ranges. In addition, the accuracy was affected by the magnitude of brightness temperature gradients and the time interval between satellite image data.

Comparison of the water leaving radiance of SeaWiFS with the IEODO ocean research station observation (이어도 해양과학기지 관측 자료와 SeaWiFS 수출광량의 비교)

  • Moon Jeong-Eon;Ryu Joo-Hyung;Ahn Yu-Hwan;Yang Chan-Su;Choi Joong-Ki
    • Proceedings of the KSRS Conference
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    • 2006.03a
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    • pp.83-86
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    • 2006
  • 이어도 종합해양과학기지의 스펙트로미터로 측정된 해색 스펙트럼 자료들과 SeaWiFS 해색센서로부터 측정된 스펙트럼 자료들을 계절별로 비교 분석하여 해색영상 자료를 처리하는데 사용된 대기보정 알고리즘이 제주도 남쪽 해역과 동중국해 해역에서 어느 정도의 오차를 가지고 있는지 연구하였다. 또한 분석된 자료들을 이용하여 SeaWiFS에서 측정한 스펙트럼 자료들을 보정하고자 하였으며, 이것은 인공위성에서 측정한 클로로필 농도값이 현장관측자료와 비교했을 때 갖는 오차의 범위를 줄여줄 수 있을 것으로 생각된다. 이와 같은 연구결과들은 차후 운용될 COMS 위성의 GOCI 해색센서에 사용될 대기보정 알고리즘과 해양환경 분석 알고리즘을 개발하는데 많은 도움이 될 것으로 생각한다.

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Microwave Radiation Characteristics of Glacial Ice in the AMSR-E NASA Team2 Algorithm (AMSR-E NASA Team2 알고리즘에서 빙하빙의 마이크로파 복사특성)

  • Han, Hyang-Sun;Lee, Hoon-Yol
    • Korean Journal of Remote Sensing
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    • v.27 no.5
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    • pp.543-553
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    • 2011
  • Sea ice concentration calculated from the AMSR-E onboard Aqua satellite by using NASA Team2 sea ice algorithm has proven to be very accurate over sea ice in Antarctic Ocean. When glacial ice such as icebergs and ice shelves are dominant in an AMSR-E footprint, the accuracy of the ice concentration calculated from NASA Team2 algorithm is not well maintained due to the different microwave characteristics of the glacial ice from sea ice. We extracted the concentrations of sea ice and glacial ice from two ENVISAT ASAR images of George V coast in southern Antarctica, and compared them with NASA Team2 sea ice concentration. The result showed that the NASA Team2 algorithm underestimates the concentration of glacial ice. To interpret the large deviation of estimation over glacial ice, we analyzed the characteristics of microwave radiation of the glacial ice in PR(polarization ratio), GR(spectral gradient ratio), $PR_R$(rotated PR), and ${\Delta}GR$ domain. We found that glacial ice occupies a unique region in the PR, GR, $PR_R$, and ${\Delta}GR$ domain different from other types of ice such as ice type A, B, and C, and open water. This implies that glacial ice can be added as a new category of ice to the AMSR-E NASA Team2 sea ice algorithm.

Block Matching Motion Estimation Using Fast Search Algorithm (고속 탐색 알고리즘을 이용한 블록정합 움직임 추정)

  • 오태명
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.36T no.3
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    • pp.32-40
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    • 1999
  • In this paper, we present a fast block matching motion estimation algorithm based on successive elimination algorithm (SEA). Based on the characteristic of center-biased motion vector distribution in the search area, the proposed method improves the performance of the SEA with a reduced the number of the search positions in the search area, In addition, to reduce the computational load, this method is combined with both the reduced bits mean absolute difference (RBMAD) matching criterion which can be reduced the computation complexity of pixel comparison in the block matching and pixel decimation technique which reduce the number of pixels used in block matching. Simulation results show that the proposed method provides better performance than existing fast algorithms and similar to full-search block motion estimation algorithm.

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Multiple Sensor Fusion Algorithm for the Altitude Estimation of Deep-Sea UUV, HEMIRE (심해무인잠수정 해미래의 고도정보 추정을 위한 다중센서융합 알고리즘)

  • Kim, Dug-Jin;Kim, Ki-Hun;Lee, Pan-Mook;Cho, Sung-Kwon;Park, Yeoun-Sik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.7
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    • pp.1202-1208
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    • 2008
  • This paper represents the multiple sensor fusion algorithm for the deep-sea unmanned underwater vehicles (UUV), composed of a remotely operated vehicle (ROV) 'Hemire' and a depressor 'Henuvy'. The performance of underwater positioning system usually highly depend on that of acoustic sensors such as ultra short base line(USBL), long base line(LBL) and altimeter. A practical sensor fusion algorithm is proposed in the sense of a moving window concept. The performance of the proposed algorithm can be observed by applying the algorithm to the Hemire sea trial data which was measured at the East Sea.