• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.603-614
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• 2013

The popularity of mobile devices provides their users with a circumstance that services and information can be accessed wherever and whenever users need. Accordingly, various studies have been proposed personalized methods to improve accessibility of mobile users to information. However, since these personalized methods require users' private information, they gives rise to problems on security. An efficient way to resolve security problems is to estimate user information by using their online and offline behavior. In this paper, for this purpose, it is proposed a novel user information identification system that identifies users' personal and social information by using both his/her behavior on social network services and proximity patterns obtained from GPS data. In the proposed system, personal information of a user like age, gender, and so on is estimated by analyzing SNS texts and POI (Point of Interest) patterns, while social information between a pair of users like family and friend is predicted with proximity patterns between the users. Each identification module is efficiently designed to handle the characteristics of user data like much noise in SNS texts and missing signals in GPS data. In experiments to evaluate the proposed system, our system shows its superiority against ordinary identification methods. This result means that the proposed system can efficiently reflect the characteristics of user data.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.393-399
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• 2013

Recently, the quantity and type of data that is being processed in cloud environment are varied. A method for easy access in different network in a heterogeneous environment of big data stored in the device is required. This paper propose security management method for smoothly access to big data in other network environment conjunction with attribute information between big data and user. The proposed method has a high level of safety even if user-generated random bit signal is modulated. The proposed method is sufficient to deliver any number of bits the user to share information used to secure recognition. Also, the security awareness information bit sequence generated by a third party to avoid unnecessary exposure value by passing a hash chain of the user anonymity is to be guaranteed to receive.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.479-487
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• 2016

In a Web 2.0 context, users are exposed to numerous smart devices and services that allow real-time interaction between users (or consumers) and developers (or producers). For the provisioning of new user-created services based on user's context, the data management of service creation experiences becomes a non-trivial task. This article introduces a data model for service creation and then proposes a service creation management architecture which enables new service creation using the data model, the management of the service creation data, and the semantic service discovery across internal/external service repositories. The article also explains the use of the proposed architecture with two different scenarios: home and mobile environments. The proposed architecture for service creation data management offers consistent and seamless handling of the service creation data throughout its usage lifecycle.

• The KIPS Transactions:PartC
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• v.18C no.2
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• pp.79-88
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• 2011

It is necessary for us to enhance the security service on smart phone by using voice data on authentication procedure. In this study, a voice data based one-time password generation mechanism is designed and implemented for enhancing user authentication on smart phone. After receiving a PIN value from the server, a user inputs his/her own voice biometric data using mike device on smart phone. And then this captured a voice biometric data will be used to generate one-time token on server side after verification procedures. Based on those mutual authentication steps, a voice data based one-time password(V-OTP) will be generated by client module after receiving the one-time token from the server finally. Using proposed voice one-time password mechanism, it is possible for us to provide more secure user authentication service on smart phone.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.151-159
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• 2017

This study deals with characteristics and risk of a PM based on user survey result, road driving test and data analysis of PM accident. Text mining method is applied to extract PM accident data from Big Data, which are claim data of private insurance company. Road driving test and survey on safety, convenience, noise, overtake ability, steering ability, and climbing ability of PM are performed to evaluate user's safety and convenience considering domestic road condition. As the result of claim data analysis, annual average increase rate of PM accident is 47.4% and average compensation of personal mobility is higher than that of bicycle by maximum 1.5 times. 79.8% of PM accident is self-caused accident due to unskilled driving and age-specific diagnosis rate of driver over 60 is higher than that of under 60. Diagnosis rate of over 60 at lower limb, foot, rib and spine is especially higher than that of under 60. As the result of road driving test and user survey, satisfaction level on safety and convenience of PM is evaluated as close to that of bicycle and satisfaction level of PM is increased after boarding. Overtake ability, steering ability, and climbing ability of PM are evaluated as same or better than that of bicycle but warning equipment to pedestrian or bike such as horn is required because noise level of PM during driving is too low. Finally, user survey result shows that bicycle road is suitable for PM and safety standard, advance-education and insurance are required for PM. It is suggested that drivers' license for PM can be replaced by advance-education. Results of this study can be used to prepare safety measures and legal basis for PM operation.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.89-104
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• 2007

This research attempts to give a personalized recommendation framework in large-sized music contents environment. Despite of existing studios and commercial contents for recommendation systems, large online shopping malls are still looking for a recommendation system that can serve personalized recommendation and handle large data in real-time. This research utilizes data mining technologies and new pattern matching algorithm. A clustering technique is used to get dynamic user segmentations using user preference to contents categories. Then a sequential pattern mining technique is used to extract contents access patterns in the user segmentations. And the recommendation is given by our recommendation algorithm using user contents preference history and contents access patterns of the segment. In the framework, preprocessing and data transformation and transition are implemented on DBMS. The proposed system is implemented to show that the framework is feasible. In the experiment using real-world large data, personalized recommendation is given in almost real-time and shows acceptable correctness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.129-132
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• 2010

Users can obtain useful information from large of data because of development of internet. Since these data rise continuously like stream data, it is required to extract the appropriate information efficiently for the user's needs. In the traditional scheme, they are acquired by processing the user queries after the occurred data are stored at a database. However, it is inefficient to process the user queries over the large volume of continuous data by using the traditional scheme. In this paper, we propose the Event-Profile Model to define the data occurrence on the internet as the events and the user's requirements as the profiles. We also propose and implement the filtering scheme to process the events and the profiles efficiently. We evaluate the performance of the proposed scheme and our experiments show that the new scheme outperforms the other on various dataset.

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.31-39
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• 2005

This paper presented new biometrics data transfer model, and use MD5 (Message Digest5) and RSA (Ron Rivest, Adi Shamir, Len Adleman) algorithm to improve biometrics data's security. So, did so that can run user authentication more safely. That is, do so that may input fingerprint among biometrics through client, and transmit processed fingerprint to server. When fingerprint information is transmitted, it uses MD5 algorithm to solve problem that get seized unlawful living body information from outside and information does Digest. And did to pass through process that transmit again this by RSA method. Also, experimented general text data and living body data that is not encoded, transmission speed and security of living body data that encoding and transmit each comparison. By running user authentication through such improved method, is expected to be applied in several. fields by method to simplify certification procedure and is little more correct and stable.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.515-526
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• 2019

In the real world, the user's preference for a particular product is determined by many factors besides the quality of the product. The reflection of these external factors was very difficult because of various fundamental problems including lack of data. However, access to external factors has become easier as the infrastructure for public data is opened and the availability of evaluation platforms with diverse and vast amounts of data. In accordance with these changes, this paper proposes a recommendation system structure that can reflect the collectable factors that affect user's preference, and we try to observe the influence of actual influencing factors on preference by applying case. The structure of the proposed system can be divided into a process of selecting and extracting influencing factors, a process of supplementing insufficient data using sentence analysis, and finally a process of combining and merging user's evaluation data and influencing factors. We also propose a validation process that can determine the appropriateness of the setting of the structural variables such as the selection of the influence factors through comparison between the result group of the proposed system and the actual user preference group.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.1
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• pp.131-139
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• 2012

The cloud storage has the client lend and use the device as a form of service rather than owning it, and thus the client pays the charge for the service that he or she actually uses, making it beneficial over the self-managed data center. When the storage service is provided on public cloud, however, the clients does not have any control over the user data, which brings a problem of violating data confidentiality. In this paper, we propose a gateway that works between the public cloud and the client for the purpose of guaranteeing the confidentiality of user data stored in cloud. The gateway encrypts or decrypts, and then delivers the user data without the client's intervention. In addition, it provides the function of exchanging keys to allow the client to access through another gateway. The proposed idea has been tested on a commercial public cloud and verified to satisfy security and compatibility.