• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 1997년도 한국전자거래학회 종합학술대회지
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• pp.355-364
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• 1997

. 통합자원은 AP등 다른 분야에서의 요구에 따라 지속적인 개정 작업이 이루어지고 새로운 Part가 추가될 것임. . AIC는 조만간 국제표준화가 완료될 것임. (현재 CD 문서에 대 한 voting 중) . Parametrics 그룹 활동은 STEP에 수용될 것임. ㆍParametrics에는 history based model을 exchange 할 수 있는 data model이 채택될 것임. . Parametrics는 곧 NWI으로 등록되어 개발의 속도가 빨라질 전망임.(중략)

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 춘계학술발표대회
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• pp.834-837
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• 2009

There is a growing need for ad-hoc analysis of extremely large data sets, especially at e-Commerce companies which depend on recommender application. Nowadays, as the number of e-Commerce web pages grow to a tremendous proportion; vertical recommender services can help customers to find what they need. Recommender application is one of the reasons for e-Commerce success in today's world. Compared with general e-Commerce recommender application, obviously, general e-Commerce recommender application's processing scope is greatly narrowed down. MapReduce is emerging as an important programming model for large-scale data-parallel applications such as web indexing, data mining, and scientific simulation. The objective of this paper is to explore MapReduce framework for the e-Commerce recommender application on major general and dedicated link analysis for e-Commerce recommender application, and thus the responding time has been decreased and the recommender application's accuracy has been improved.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.970-986
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• 2017

Certificateless public key cryptography (CL-PKC) is a new benchmark in modern cryptography. It not only simplifies the certificate management problem of PKC, but also avoids the key escrow problem of the identity based cryptosystem (ID-PKC). In this article, we propose a certificateless blind signature protocol which is based on elliptic curve cryptography (CLB-ECC). The scheme is suitable for the wireless communication environment because of smaller parameter size. The proposed scheme is proven to be secure against attacks by two different kinds of adversaries. CLB-ECC is efficient in terms of computation compared to the other existing conventional schemes. CLB-ECC can withstand forgery attack, key only attack, and known message attack. An e-cash framework, which is based on CLB-ECC, has also been proposed. As a result, the proposed CLB-ECC scheme seems to be more effective for applying to real life applications like e-shopping, e-voting, etc., in handheld devices.

• Journal of information and communication convergence engineering
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• 제22권1호
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• pp.7-13
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• 2024

User preferences and ratings may be anticipated by recommendation systems, which are widely used in social networking, online shopping, healthcare, and even energy efficiency. Constructing trustworthy recommender systems for various applications, requires the analysis and mining of vast quantities of user data, including demographics. This study focuses on holding elections with vague voter and candidate preferences. Collaborative user ratings are used by filtering algorithms to provide suggestions. To avoid information overload, consumers are directed towards items that they are more likely to prefer based on the profile data used by recommender systems. Better interactions between governments, residents, and businesses may result from studies on recommender systems that facilitate the use of e-government services. To broaden people's access to the democratic process, the concept of "e-democracy" applies new media technologies. This study provides a framework for an electronic voting advisory system that uses machine learning.

• Journal of Contemporary Eastern Asia
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• 제8권2호
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• pp.27-43
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• 2009

A ban on political podcasting during the General Elections 2006 in Singapore was justified by the Singaporean government on the grounds that the new medium had a greater power to influence voters than traditional modes of political discourse. A between-subjects controlled experiment was conducted to test whether podcasts of political speeches had a greater power to influence voters' evaluations of political candidates and likelihood of voting for them than online text-based transcripts of the same speeches. The study also examined whether mere exposure to political speeches online, irrespective of the modality, had an effect on voters' more general political preferences, i.e. the likelihood of support and voting for the opposition. The findings suggest that political podcasts were no more persuasive than text-based websites and that the effects on political preferences, if any, were likely due the exposure to political content online, not because of the nature of the medium. The implications of the findings are discussed.

• Smart Structures and Systems
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• 제5권1호
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• pp.43-54
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• 2009

This study introduces a novel approach for locating damage in a structure using wireless sensor system with local level computational capability to alleviate data traffic load on the centralized computation. Smart wireless sensor systems, capable of iterative damage-searching, mimic an optimization process in a decentralized way. The proposed algorithm tries to detect damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides a reasonably effective sensor placement within a structure. Sensor clustering also assigns a certain number of master sensors in each cluster so that they can constantly monitor the structural health of a structure. By adopting a voting system, a group of wireless sensors iteratively forages for a damage location as they can be activated as needed. Since all of the damage searching process occurs within a small group of wireless sensors, no global control or data traffic to a central system is required. Numerical simulation demonstrates that the newly developed searching algorithm implemented on wireless sensors successfully localizes stiffness damage in a plate through the local level reconfigurable function of smart sensors.

• Journal of Information Processing Systems
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• 제8권4호
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• pp.567-574
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• 2012

This paper presents a strong designated verifiable signcryption scheme, in which a message is signcrypted by a signcryptor and only a specific receiver, who called a "designated verifier", verifies it using his own secret key. The scheme is secure, as an adversary can not verify the signature even if the secret key of the signer is compromised or leaked. The security of the proposed scheme lies in the complexity of solving two computationally hard problems, namely, the Discrete Logarithm Problem (DLP) and the Integer Factorization Problem (IFP). The security analysis of the scheme has been done and it is proved that, the proposed scheme can withstand an adaptive chosen ciphertext attack. This scheme can be very useful in organizations where there is a need to send confidential documents to a specific recipient. This scheme can also be applicable to real life scenarios, such as, e-commerce applications, e-banking and e-voting.

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 2003년도 하계학술대회논문집
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• pp.37-42
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• 2003

Threshold signature and blind signature are playing important roles in cryptography as well as practical applications such as e-cash and e-voting systems. In this paper, we present a new threshold blind digital signature based on pairings without a trusted third party. Our scheme operates on Gap Diffie-Hellman group, where Computational Diffie-Hellman problems are hard but Decision Diffie-Hellman problems are easy. For example, we use pairings that could be built from Weil pairing or Tate pairing. To the best of our knowledge, we claim that our scheme is the first threshold blind signature using pairings with provable security in the random oracle model.

• 한국컴퓨터교육학회 학술대회
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• 한국컴퓨터교육학회 2018년도 하계학술대회
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• pp.67-70
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• 2018

블록체인 기술은 4차 산업혁명 시대를 이끌어 나갈 핵심기술로 거론되고 있으며 높은 보안성을 장점으로 가상화폐, 사물인터넷, 등 다양한 분야에서 활용되고 있다. 본 연구는 캠퍼스 내에서 진행되는 투표를 위한 전자투표시스템을 제작하고, 보안성을 강화하기 위해 블록체인기술을 활용하였다. 기존의 분산원장네트워크를 활용하는 방식과 달리, 소규모 투표에 적합하도록 개인 간의 가상화폐 거래과정을 활용한 투표시스템을 구축하였다. 이를 통해 기존의 블록체인기술기반 전자투표시스템의 단점인 초기 서버구축비용의 소요를 줄일 수 있을 것으로 기대한다.

• Journal of Information Processing Systems
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• 제13권5호
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• pp.1203-1212
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• 2017

Intrusion detection systems (IDSs) are crucial in this overwhelming increase of attacks on the computing infrastructure. It intelligently detects malicious and predicts future attack patterns based on the classification analysis using machine learning and data mining techniques. This paper is devoted to thoroughly evaluate classifier ensembles for IDSs in IEEE 802.11 wireless network. Two ensemble techniques, i.e. voting and stacking are employed to combine the three base classifiers, i.e. decision tree (DT), random forest (RF), and support vector machine (SVM). We use area under ROC curve (AUC) value as a performance metric. Finally, we conduct two statistical significance tests to evaluate the performance differences among classifiers.