• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.528-537
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• 2021

Face recognition has gained significant notice because of its application in many businesses: security, healthcare, and marketing. In this paper, we will present the recognition method using the combination of correlation filters (CF) and Support Vector Machine (SVM). Firstly, we evaluate the performance and compared four different correlation filters: minimum average correlation energy (MACE), maximum average correlation height (MACH), unconstrained minimum average correlation energy (UMACE), and optimal-tradeoff (OT). Secondly, we propose the machine learning approach by using the OT correlation filter for features extraction and SVM for classification. The numerical results on National Cheng Kung University (NCKU) and Pointing'04 face database show that the proposed method OT-SVM gets higher accuracy in face recognition compared to other machine learning methods. Our approach doesn't require graphics card to train the image. As a result, it could run well on a low hardware system like an embedded system.

• Journal of the Chungcheong Mathematical Society
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• v.20 no.4
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• pp.355-366
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• 2007

In this paper, we propose a new blind group identification protocol and a hidden group signature protocol as its application. These protocols involve many provers and one verifier such that (1) the statement of all the provers are proved simultaneously, (2) and also all the provers using computationally limited devices (e.g. smart cards) have no need of computing the bilinear pairings, (3) but only the verifier uses the bilinear pairings. A. Saxena et al. proposed a two-round blind (group) identification protocol in 2005 using the bilinear pairings. But it reveals weakness in the active-intruder attack, and all the provers as well as the verifier must have devices computing bilinear pairings. Comparing their results, our protocol is secure from the active-intruder attack and has more fit for smart cards. In particular, it is secure under only the assumption of the hardness of the Discrete-Logarithm Problem in bilinear groups.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2171-2178
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• 2008

Recently, Network companies have introduced security solutions to protect the network from intrusions, attacks and viruses but the network has still weakness and vulnerability. It is time to bring more stable and reliable authentication system that would meet the Internet user's need. In this study, Current broadband networks don't have hierarchic and stable authentication solutions. And so, an integrated and hierarchic system is needed to provide a various kinds of application services. I'd like to present a new authentication system which is based on unified web authentication design. It will unit various authentication systems that have been deployed in various network environment and reinforce network security to provice a various kinds of application services in a stable and safe environment. that is a simple and more secure method for fighting a rise in card-not-present fraud.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.617-625
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.147-149
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• 2004

Although most of the people have studied English for a long time, their English conversation capability is low. When we provide them portable conversational-type English learners by the application of computer and information process technology, such portable learners can be used to enhance their English conversation capability by their conventional conversation exercises. The core technology to develop such learner is the development of a voice recognition and synthesis module under an embedded environment. This paper deals with voice recognition and synthesis, prototype of the learner module using a DSP(Digital Signal Processing) chip for voice processing, voice playback function, flash memory file system, PC download function using USB ports, English conversation text function by the use of SMC(Smart Media Card) flash memory, LCD display function, MP3 music listening function, etc. Application areas of the prototype equipped with such various functions are vast, i.e. portable language learners, amusement devices, kids toy, control by voice, security by the use of voice, etc.

• Journal of Multimedia Information System
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• v.5 no.2
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• pp.99-104
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.849-860
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• 2003

As mobile device is becoming more popular, E-Commerce changes into M-Commerce. Especially, IMT-2000 (International Mobile Telecommunication 2000) service is prepared for M-Commerce and this has USIM (Universal Subscriber Identity Module) as a core of certification of individuality and transactions. As a result, the area of mobile service going to expand by USIM. But, mobile services using USIM leave much to be desired, and developed application don't variety. In this paper, for the efficient design of USIM, the structure of USIM and protocol is analyzed, and secure payment solution in USIM is proposed. Specially, offline payment system is proposed for the verification of proposed protocols including security, saving, and calculation of balance. finally, the simulation of proposed payment system on USIM is performed using Java Card.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.221-227
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• 2014

When implementing cryptographic algorithms in mobile devices like smart cards, the security against side-channel attacks should be considered. Side-channel attacks try to find critical information from the side-channel infromation obtained from the underlying cryptographic devices' execution. Especially, the power analysis attack uses the power consumption profile of the devices as the side-channel information. This paper proposes a new gate-level countermeasure against the power analysis attack and the glitch attack and suggests how to apply the measure to securely implement AES.

• Convergence Security Journal
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• v.16 no.7
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• pp.167-172
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• 2016

The purpose of this study is to provide implications for preventing insider information leakages in public agencies for national security. First, the study examined the definitions and current usage of information security systems of public agencies were examined. Second, web-service base information leaks and malware-base information leaks were discussed and three major credit card companies' personal information leakage cases were analyzed. Based on the analysis, four solutions were provided. First, information leakages can be protected by using web filtering solutions based on the user, which make possible to limit frequencies of malware exposures. Second, vaccine programs and vaccine management system should be implemented to prevent information leakages by malware. Third, limit the use of portable devices within local networks to prevent information leakages and vaccines programs for malware should be regularly used. Forth, to prevent information leakages by smartphone malwares, data encryption application should be used to encrypt important information.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.253-260
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• 2017

Authenticated key agreement in multi-server environments is one of very important security issues because only authorized user needs to access their data and services. To support this issue, numerous schemes have been proposed over recent years. Recently, Shin showed the security weaknesses in the previous scheme and proposed an improved scheme called SIAKAS to solve them. Unfortunately, this paper shows that SIAKAS is still weak against application server impersonation attack and could be traceable to attackers. To solve the problems in SIAKAS, we propose an untraceable authenticated key agreement scheme, denoted by UAKAS. UAKAS efficiently solves security and privacy issues in SIAKAS and the related schemes and could reduce the operation overhead at least 12% compared to them.