• Title/Summary/Keyword: Point Signature

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A Public-Key Crypto-Core supporting Edwards Curves of Edwards25519 and Edwards448 (에드워즈 곡선 Edwards25519와 Edwards448을 지원하는 공개키 암호 코어)

  • Yang, Hyeon-Jun;Shin, Kyung-Wook
    • Journal of IKEEE
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    • v.25 no.1
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    • pp.174-179
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    • 2021
  • An Edwards curve cryptography (EdCC) core supporting point scalar multiplication (PSM) on Edwards curves of Edwards25519 and Edwards448 was designed. For area-efficient implementation, finite field multiplier based on word-based Montgomery multiplication algorithm was designed, and the extended twisted Edwards coordinates system was adopted to implement point operations without division operation. As a result of synthesizing the EdCC core with 100 MHz clock, it was implemented with 24,073 equivalent gates and 11 kbits RAM, and the maximum operating frequency was estimated to be 285 MHz. The evaluation results show that the EdCC core can compute 299 and 66 PSMs per second on Edwards25519 and Edwards448 curves, respectively. Compared to the ECC core with similar structure, the number of clock cycles required for 256-bit PSM was reduced by about 60%, resulting in 7.3 times improvement in computational performance.

Novelty Detection on Web-server Log Dataset (웹서버 로그 데이터의 이상상태 탐지 기법)

  • Lee, Hwaseong;Kim, Ki Su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.10
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    • pp.1311-1319
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    • 2019
  • Currently, the web environment is a commonly used area for sharing information and conducting business. It is becoming an attack point for external hacking targeting on personal information leakage or system failure. Conventional signature-based detection is used in cyber threat but signature-based detection has a limitation that it is difficult to detect the pattern when it is changed like polymorphism. In particular, injection attack is known to the most critical security risks based on web vulnerabilities and various variants are possible at any time. In this paper, we propose a novelty detection technique to detect abnormal state that deviates from the normal state on web-server log dataset(WSLD). The proposed method is a machine learning-based technique to detect a minor anomalous data that tends to be different from a large number of normal data after replacing strings in web-server log dataset with vectors using machine learning-based embedding algorithm.

Improvement in efficiency on ID-based Delegation Network (ID 기반 위임 네트워크의 성능 개선방안)

  • Youn, Taek-Young;Jeong, Sang-Tae;Park, Young-Ho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.17 no.3
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    • pp.17-25
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    • 2007
  • Delegation of signing capability is a common practice in various applications. Mambo et al. proposed a proxy signatures as a solutions for delegation of signing capability. Proxy signatures allow a designated proxy signer to sign on behalf of an original signer. After the concept of proxy signature scheme is proposed, many variants are proposed to support more general delegation setting. To capture all possible delegation structures, the concept of delegation network was proposed by Aura. ID-based cryptography, which is suited for flexible environment, is desirable to construct a delegation network. Chow et al proposed an ID-based delegation network. In the computational point of view, their solution requires E pairing operations and N elliptic curve scalar multiplications where E and N are the number of edges and nodes in a delegation structure, respectively. In this paper, we proposed an efficient ID-based delegation network which requires only E pairing operations. Moreover, we can design a modified delegation network that requires only N pairing operations.

Inter-Domain Verifiable Self-certified public keys (상이한 도메인에서 검증 가능한 자체 인증 공개키)

  • 정영석;한종수;오수현;원동호
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.13 no.4
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    • pp.71-84
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    • 2003
  • Self-certified public keys need not be accompanied with a separate certificate to be authenticated by other users because the public keys are computed by both the authority and the user. At this point, verifiable self-certified public keys are proposed that can determine which is wrong signatures or public keys if public keys are used in signature scheme and then verification of signatures does not succeed. To verify these public keys, key generation center's public key trusted by users is required. If all users trust same key generation center, public keys can be verified simply. But among users in different domains, rusty relationship between two key generation centers must be accomplished. In this paper we propose inter-domain verifiable self-certified public keys that can be verified without certificate between users under key generation centers whose trusty relationship is accomplished. Also we present the execution of signature and key distribution between users under key generation centers use different public key parameters.

POSSIBLE MERGER SIGNATURE IN SZ MAPS

  • KOCH PATRICK
    • Journal of The Korean Astronomical Society
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    • v.37 no.5
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    • pp.471-476
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    • 2004
  • We propose an analytical model to estimate the influence of a merger on the thermal SZ effect. Following observations we distinguish between subsonic and transonic mergers. Using analytical velocity fields and the Bernoulli equation we calculate the excess pressure around a moving subcluster for an incompressible subsonic gas. Positive excess around the stagnation point and negative excess on the side of the subcluster lead to characteristic signatures in the SZ map, of the order of $10\%$ compared to the unperturbed signal. For a transonic merger we calculate the change in the thermal spectral SZ function, resulting from bow shock accelerated electrons. The merger shock compression factor determines the power law tail of the new non-thermal electron population and is directly related to a shift in the crossover frequency. This shift is typically a few percent towards higher frequencies.

A Study On Three-dimensional Face Recognition Model Using PCA : Comparative Studies and Analysis of Model Architectures (PCA를 이용한 3차원 얼굴인식 모델에 관한 연구 : 모델 구조 비교연구 및 해석)

  • Park, Chan-Jun;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.1373-1374
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    • 2015
  • 본 논문은 복잡한 비선형 모델링 방법인 다항식 기반 RBF 뉴럴 네트워크(Radial Basis Function Neural Network)와 벡터공간에서 임의의 비선형 경계를 찾아 두 개의 집합을 분류하는 방법으로 주어진 조건하에서 수학적으로 최적의 해를 찾는 SVM(Support Vector Machine)를 사용하여 3차원 얼굴인식 모델을 설계하고 두 모델의 3차원 얼굴 인식률을 비교한다. 3D스캐너를 통해 3차원 얼굴형상을 획득하고 획득한 영상을 전처리 과정에서 포인트 클라우드 정합과 포즈보상을 수행한다. 포즈보상 통해 정면으로 재배치한 영상을 Multiple Point Signature기법을 이용하여 얼굴의 깊이 데이터를 추출한다. 추출된 깊이 데이터를 RBFNN과 SVM의 입력패턴과 출력으로 선정하여 모델을 설계한다. 각 모델의 효율적인 학습을 위해 PCA 알고리즘을 이용하여 고차원의 패턴을 축소하여 모델을 설계하고 인식 성능을 비교 및 확인한다.

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Object Cataloging Using Heterogeneous Local Features for Image Retrieval

  • Islam, Mohammad Khairul;Jahan, Farah;Baek, Joong Hwan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.11
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    • pp.4534-4555
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    • 2015
  • We propose a robust object cataloging method using multiple locally distinct heterogeneous features for aiding image retrieval. Due to challenges such as variations in object size, orientation, illumination etc. object recognition is extraordinarily challenging problem. In these circumstances, we adapt local interest point detection method which locates prototypical local components in object imageries. In each local component, we exploit heterogeneous features such as gradient-weighted orientation histogram, sum of wavelet responses, histograms using different color spaces etc. and combine these features together to describe each component divergently. A global signature is formed by adapting the concept of bag of feature model which counts frequencies of its local components with respect to words in a dictionary. The proposed method demonstrates its excellence in classifying objects in various complex backgrounds. Our proposed local feature shows classification accuracy of 98% while SURF,SIFT, BRISK and FREAK get 81%, 88%, 84% and 87% respectively.

3D face recognition based on facial surface information (얼굴 표면의 형태정보를 이용한 3차원 얼굴인식)

  • Lee, Dong-Joo;Shin, Hyoung-Chul;Sohn, Kwang-Hoon
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.423-424
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    • 2006
  • This paper describes a 3D face recognition using different devices for 3D faces and input faces which include several different pose. Before the recognition stage, through the EC-SVD, all data have to be preprocessed and normalized. At recognition stage, we propose the multi-point signature method for measuring facial surface information. And we use the root mean square error for matching. From the experiment results, we have 92.5% recognition rate.

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Robust pattern watermarking using wavelet transform and multi-weights (웨이브렛 변환과 다중 가중치를 이용한 강인한 패턴 워터마킹)

  • 김현환;김용민;김두영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.3B
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    • pp.557-564
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    • 2000
  • This paper presents a watermarking algorithm for embedding visually recognizable pattern (Mark, Logo, Symbol, stamping or signature) into the image. first, the color image(RGB model)is transformed in YCbCr model and then the Y component is transformed into 3-level wavelet transform. Next, the values are assembled with pattern watermark. PN(pseudo noise) code at spread spectrum communication method and mutilevel watermark weights. This values are inserted into discrete wavelet domain. In our scheme, new calculating method is designed to calculate wavelet transform with integer value in considering the quantization error. and we used the color conversion with fixed-point arithmetic to be easy to make the hardware hereafter. Also, we made the new solution using mutilevel threshold to robust to common signal distortions and malicious attack, and to enhance quality of image in considering the human visual system. the experimental results showed that the proposed watermarking algorithm was superior to other similar water marking algorithm. We showed what it was robust to common signal processing and geometric transform such as brightness. contrast, filtering. scaling. JPEG lossy compression and geometric deformation.

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A Study on Loose Part Monitoring System in Nuclear Power Plant Based on Neural Network

  • Kim, Jung-Soo;Hwang, In-Koo;Kim, Jung-Tak;Moon, Byung-Soo;Lyou, Joon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.2 no.2
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    • pp.95-99
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    • 2002
  • The Loose Part Monitoring System(LPMS) has been designed to detect. locate and evaluate detached or loosened parts and foreign objects in the reactor coolant system. In this paper, at first, we presents an application of the back propagation neural network. At the preprocessing step, the moving window average filter is adopted to reject the reject the low frequency background noise components. And then, extracting the acoustic signature such as Starting point of impact signal. Rising time. Half period. and Global time, they are used as the inputs to neural network . Secondly, we applied the neural network algorithm to LPMS in order to estimate the mass of loose parts. We trained the impact test data of YGN3 using the backpropagation method. The input parameter for training is Rising clime. Half Period amplitude. The result shored that the neural network would be applied to LPMS. Also, applying the neural network to thin practical false alarm data during startup and impact test signal at nuclear power plant, the false alarms are reduced effectively.