• Journal of Digital Convergence
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• v.15 no.7
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• pp.201-211
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• 2017

Wireless network using dynamic IP and mobile IP technology provides the user with convenience of access and movement. However, this causes the attacker who disguises normal user(pretending to be a regular user) to have more opportunity in regard to access and acquisition of information. This paper help the network administrator and the service provider quickly to recognize the attacker's intention to access network and service. Therefore network administrator and service provider can specify and respond the location of the attacker appropriately. To achieve above, we define an entity (W_L_M) that manages user information of WiFi and LTE network, and propose messages and procedures for attacker's location identification and alarm. The performance evaluation of this paper is based on qualitative analysis. By using the proposed method, some cost (message creation, processing and transmission) occurred but it was analyzed to be less than the total network operation cost. The proposal of this paper is a management method that utilizes existing network information and structure. This method can be used as a reference material to enhance security.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.501-511
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• 2013

Recently, the visualization method of social network service have been only focusing on presentation of visualizing network data, which the methods do not consider an efficient processing speed and computational complexity for increasing at the ratio of arithmetical of a big data regarding social networks. This paper proposes a cloud based on visualization method to visualize a user focused hierarchy relationship between user's nodes on social network. The proposed method can intuitionally understand the user's social relationship since the method uses fuzzy to represent a hierarchical relationship of user nodes of social network. It also can easily identify a key role relationship of users on social network. In addition, the method uses hadoop and hive based on cloud for distributed parallel processing of visualization algorithm, which it can expedite the big data of social network.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.544-546
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• 2011

Due to the explosive growth of online social network users, large numbers of users discover these social network sites are a place where they can be able to spend their spare time, share feelings, ideas freely, and to search for new friends or partners. These web sites give an opportunity for its users to socialize with new people and to keep in touch or reconnect with current or old friends and families across disperse continents via these web sites, which traditionally replace the traditional methods. These social network web sites need careful investigations and findings on the usability for effective interactivity and more usability. However, little research might have previously invested on the usability of these on social network web sites. Therefore, we propose a new framework to study the usability of these social network sites. We namely call our framework "Interactivity". This framework will enable us to assess the usability of the social network sites. It will provide an overview of the user's behavior while interacting in these social network web sites. Measurement of the interactivity will be measured using Camtasia software. This software will entirely capture the interactivity of users including the screen and the movements, which the screen and the motion of the user action will undergo to analysis at the end of our research.

• Journal of The Korean Association of Information Education
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• v.8 no.4
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• pp.547-554
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• 2004

Education is the largest application area of adaptive hypermedia systems. The user modeling is considered a very important part of the field of adpative hypermedia systems. In this paper we present the developed user model which provides different educational contents using a neural network. The user model has been verified on hypermedia for learning about basic web concepts, multimedia and HTML. This paper reports the results of simulation. Our simulation shows that the user model exactly can provide contextual different links for different students.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.55-63
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• 2021

The design functionality put forward by mapping the interactiveness of information. The presentation of such information with the user interface model indicates that the guidelines, concepts, and workflows form the deliverables and milestones for achieving a visualized design, therefore forming the right trend is significant to ensure compliance in terms of changing consideration and applying evaluation in the early stages. It is evidenced that prototype design is guided by improvement specifications, includes modes, and variables that increase improvements. The study presents five user interface testing methods. The testing methods are heuristic evaluation, perspective-based user interface testing, cognitive walkthrough, pluralistic walkthrough, and formal usability inspection. It appears that the five testing methods can be combined and matched to produce reasonable results. At last, the study presents different mobile application designs for student projects besides the evaluation of mobile application designs to consider the user needs and usability.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.614-618
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• 2008

As the multimedia data increase a lot with the rapid development of the Internet, an efficient retrieval technique focusing on individual users is required based on the analyses of such data. However, user modeling services provided by recent web sites have the limitation of text-based page configurations and recommendation retrieval. In this paper, we construct the user preference model with a Bayesian network to apply the user modeling to video retrieval, and suggest a method which utilizes probability reasoning. To do this, context information is defined in a real office environment and the video scripts acquired from established cameras and annotated the context information manually are used. Personal information of the user, obtained from user input, is adopted for the evidence value of the constructed Bayesian Network, and user preference is inferred. The probability value, which is produced from the result of Bayesian Network reasoning, is used for retrieval, making the system return the retrieval result suitable for each user's preference. The usability test indicates that the satisfaction level of the selected results based on the proposed model is higher than general retrieval method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.154-163
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• 2017

Collaborative filtering, one of the most widely used techniques to build recommender systems, is based on the idea that users with similar preferences can help one another find useful items. Credit card user behavior analytics show that most customers hold three or less credit cards without duplicates. This behavior is one of the most influential factors to data sparsity. The 'cold-start' problem caused by data sparsity prevents recommender system from providing recommendation properly in the personalized credit card recommendation scenario. We propose a personalized credit card recommender system to address the cold-start problem, using multiple user profiles. The proposed system consists of a training process and an application process using five user profiles. In the training process, the five user profiles are transformed to five user networks based on the cosine similarity, and an integrated user network is derived by weighted sum of each user network. The application process selects k-nearest neighbors (users) from the integrated user network derived in the training process, and recommends three of the most frequently used credit card by the k-nearest neighbors. In order to demonstrate the performance of the proposed system, we conducted experiments with real credit card user data and calculated the F1 Values. The F1 value of the proposed system was compared with that of the existing recommendation techniques. The results show that the proposed system provides better recommendation than the existing techniques. This paper not only contributes to solving the cold start problem that may occur in the personalized credit card recommendation scenario, but also is expected for financial companies to improve customer satisfactions and increase corporate profits by providing recommendation properly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1832-1853
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• 2018

The personal health record (PHR) system is a promising application that provides precise information and customized services for health care. To flexibly protect sensitive data, attribute-based encryption has been widely applied for PHR access control. However, escrow, exposure and abuse of private keys still hinder its practical application in the PHR system. In this paper, we propose a coordinated ciphertext policy attribute-based access control with user accountability (CCP-ABAC-UA) for the PHR system. Its coordinated mechanism not only effectively prevents the escrow and exposure of private keys but also accurately detects whether key abuse is taking place and identifies the traitor. We claim that CCP-ABAC-UA is a user-side lightweight scheme. Especially for PHR receivers, no bilinear pairing computation is needed to access health records, so the practical mobile PHR system can be realized. By introducing a novel provably secure construction, we prove that it is secure against selectively chosen plaintext attacks. The analysis indicates that CCP-ABAC-UA achieves better performance in terms of security and user-side computational efficiency for a PHR system.

• The Journal of Information Systems
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• v.22 no.3
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• pp.1-24
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• 2013

SNS(Social Network Services) is being recognized as an important part in our society, individual lives and corporate business aspects, and the influence of SNS is growing explosively as expansion and supply of infrastructures that support mobile environments increase. Previous studies related to SNS were focused on user acceptance of new technology, based on Technology Acceptance Model(TAM). However, they had a limitation to focus on technology acceptance, without the consideration of personal and behavioral factors in SNS use. However, above all, successful SNS requires the understanding of users who are active on the network. Therefore, from the user's perspective, this study attempted a multi-dimensional approach by reflecting characteristics that come from SNS usage. This study considered user innovation, virtual skill, self-efficacy, social pressure and network effect as independent variables, and perceived ease-of-use, perceived usefulness and perceived value as mediating variables, and intention-to-use as dependent variable. The result showed that user innovation, self-efficacy, social pressure and network effect had a significant effect on the mediating variables. The practical contribution of this study is to suggest useful decision alternatives concerned to marketing strategy for acquiring and retaining lone-term customers related to SNS business.