• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2298-2304
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• 2017

Online signature verification is one of the simple and efficient method of identity verification and has less resistance than other biometric technologies. In training to build a verification model, negative samples are required to build the model, but in most practical applications it is not easy to get negative samples - forgery signatures. In this paper, proposed is a method using someone else's signatures as negative samples. In verification, shape-based features extracted from the time-sequenced signature data are extracted and a support vector machine is used to verify. SVM tries to map a feature vector to a high dimensional space and to draw a linear boundary in the high dimensional space. SVM is one of the best classifiers and has been applied to various applications. Using general handwriting data, i.e., someone else's signatures which have little in common with positive samples improved the verification rate experimentally, which means that signature verification without negative samples is possible.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.129-137
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• 2004

This paper presents a signature verification method that uses Gabor filter in computing similarity between signatures. In computing similarity to compare two on-line signatures, the temporal relationship between two signatures should be computed in advance. However, conventional point matching method using DP(dynamic programming) matching consumes much computation. In this paper, we propose a fast method for computing the temporal relationship between two on-line signatures by using the phase output of Gabor Inter applied on the on-line signature signals. Two similarity measures are defined in the method: Temporal Similarity and Temporally Arranged Feature Profile Similarity. With the proposed method, Ive could compare signatures 30 times faster than conventional method using DP matching.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1435-1441
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• 2018

Online signature verification is one of the simple and efficient methods of identity verification and has less resistance than other biometric technologies. To handle signature verification as a classification problem, it is necessary to gather forgery signatures, which is not easy in most practical applications. It is not easy to obtain a large number of genuine signatures either. In this paper, one class SVM is used to tackle the forgery signature problem and someone else's signatures are used as general handwriting data to solve the genuine signature problem. Someone else's signature does not share shape-based features with the signature to be verified, but it contains the general characteristics of a signature and useful in verification. Verification rate can be improved by using the general handwriting data, which can be confirmed through the experimental results.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2884-2896
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• 1998

For on-line signature verification, the local shape of a signature is an important information. The current approaches, in which signatures are represented into a function of time or a feature vector without regarding of local shape, have not used the various features of local shapes, for example, local variation of a signer, local complexity of signature or local difficulty of forger, and etc. In this paper, we propose a new technique for on-line signature verification based on a structural signature representation so as to analyze local shape and to make a selection of important local parts in matching process. That is. based on a structural representation of signature, a technique of important of local weighting and personalized decision threshold is newly introduced and its experimental results under different conditions are compared.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.169-172
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• 2003

본 논문에서는 기존의 분절 단위 비교방법에서 참조서명과 비교서명간에 분할점 개수와 위치에 대한 불일치 문제를 개선하기 위해 구간 분할 매칭 방법을 제안한다. 제안된 분할방법은 시간에 대한 x와 y좌표 상에서 서명마다 변하지 않는 특징점을 구간 분할점으로 선택하여 구간별로 매칭시킴으로서 분절의 안정적인 분할을 통해 인식률을 높이고자 한다. 실험 결과에서 진서명과 위조서명을 포함한 기타서명에 대해 FAR이 0.06%일 때 FRR 1.25%의 오류율을 확인하였으며 FAR이 0%일 때의 평균인식율이 98.7%를 보임으로써 제안한 서명 검증 기법이 우수함을 확인 할 수 있었다.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1065-1074
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• 2007

Among various methods to compare reference signatures with an input signature, the segment-to-segment matching method has more advantages than global and point-to-point methods. However, the segment-to-segment matching method has the problem of having lower recognition rate according to the variation of partitioning points. To resolve this drawback, this paper proposes a signature verification method by considering linear discriminant analysis as well as segment-to-segment matching method. For the final decision step, we adopt statistical based Bayesian classifier technique to effectively combine two individual systems. Under the various experiments, the proposed method shows better performance than segment-to-segment based matching method.

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.261-267
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• 2004

In undeniable digital signature scheme, the signature can not be verified without the signer's cooperation. The undeniable signature scheme can be used to computerize many applications which can not be done by a conventional digital signature scheme. In this study, we propose the undeniable digital multi-signature scheme which requires many signers and designated verifier. The multi-signature can be verified only in cooperation with all signers. The proposed scheme satisfies undeniable property and it is secure against active attacks such as modification and denial of the multi-signature by signers. We also discuss practical applications such as joint copyright protection on digital contents.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.540-543
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• 2020

본 논문에서는 대표적인 이미지 분류 모델인 CNN(Convolutional Neural Network)과 시간에 따른 이미지의 변화를 학습할 수 있는 LSTM(Long Short-Term Memory) 기반의 온라인 서명인식 모델을 제안한다. 실제로는 위조서명을 미리 구하기 어렵다는 사실을 고려해 서명검증 대상자가 아닌 타인의 진서명과 대상자의 일반 필기 데이터를 음의 데이터로서 학습에 사용하였다. 실험 결과, 전체 이미지 중 서명 부분의 비율에 따라 좋은 성능을 보이는 검증 모델이 다르며 Accuracy 성능지표를 통해 이 비율이 높거나 낮을 경우 CNN-LSTM 이, 중간일 경우 CNN 이 적합하다는 것을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.1949-1952
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• 2003

실생황에서 권한의 위임을 동한 대리 서명 기법들이 최근 많이 연구되고 있다. 대리서명은 원서명자가 그의 서명 권한을 대리서명자에게 위임하여 대리서명자가 원서명자를 대신해서 서명을 생성하는 것을 말한다. 이러한 대리서명을 온라인 상에서 사용하기 위해서는 위임자의 권한 위임장이 위 변조와 오남용의 위험으로부터 안전하게 보호되어야 한다. 또한 대리서명의 수행을 위해서는 원서명자의 위임에 대한 정보가 명확해야 한다. 대리서명의 기본적인 방법은 원서명자가 위임 정보에 대한 서명을 생성하고 이를 위임자에게 전달하여 위임자가 위임키로서 사용하게 하는 것이다. 위임키쌍이 위임 정보에 기반한 원서명자의 서명으로부터 생성되기 때문에 어떠한 검증절차에서도 원서명자의 동의를 확인 할 수 있다. 본 논문에서는 원서명자와 대리서명자가 기존의 인증서를 발급 받은 환경에서 원서명자가 대리서명자에 대하여 검증자에게 위임정보를 등록하는 프로토콜을 제안한다. 위임내용에 대해 원서명자가 전자서명을 하고 검증자는 이에 해당하는 내용을 검증한 후 위임서명자에 대한 권한 기간 등의 제약사항을 설정한다. 이후 위임서명자는 위임내용에 대해 고지를 받고 허가된 범위 내에서 위임 서명을 한다. 마지막으로 본 논문에서는 기존의 방법들과 비교 분석하여 제안하는 위임 등륵 프로토콜에 대한 효율성을 제시한다.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.385-396
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• 2005

In this paper, a new structural approach to on-line signature verification is presented. A primitive pattern is defined as a part segmented by a local minimal position of speed. And a structural description of signature is composed of subpatterns which are defined as such forms as rotation shape, cusp shape and bell shape, acquired by composition of the primitives regarding the directional changes. As the matching method to find identical parts between two signatures, a modified DP(dynamic programming) matching algorithm is presented. And also, variation and complexity of local parts are computed from the training samples, and reference model and decision boundary are derived from these. Error rate, execution time and memory usage are compared among the functional approach, the parametric approach and the proposed structural approach. It is found that the average error rate can be reduced from 14.2% to 4.05% when the local parts of a signature are weighted and the complexity is used as a factor of decision threshold. Though the error rate is similar to that of functional approaches. time consumption and memory usage of the proposed structural approach are shown to be very effective.