• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.673-685
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• 2017

STI(Social Trust Index) indicates levels of trustworthiness, honesty and reliability among people in a society. Since the STI varies in countries, security control on cyber space should be applied differently according to the STI so that companies can protect their assets efficiently and effectively. We compare STIs between Korea and United States using the Diamond Model and investigate how the STIs affect corporate security controls in those two countries. We finally present a formula using AHP (Analytic Hierarchy Process) to measure levels of corporate security controls in different countries.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.237-242
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• 2013

SNS is emerging as an academic and social interest, as Facebook and Twitter are developed explosively. But, SNS has a problem of exposing user's privacy because it is originated by exchanging user's personal information and opinion. This paper proposes SNS user privacy protecting model using data separation and false data information instead of blocking which is using to protect user's personal privacy. The proposed model do not let the third party extract precise information after collecting user's context information by adding false information to separated context information. Also, it gets user's agreement beforehand if SNS service provider uses user's information not to be used illegally by the third party.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.49-58
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• 2020

Lately, a large amount of textual data have been poured out of the Internet and the technology to refine them is needed. Most of these data are long text and often have no title. Therefore, in this paper, we propose a technique to combine the sequence-to-sequence model of RNN and the REINFORCE algorithm to generate the title of the long text automatically. In addition, the TextRank algorithm was applied to extract a summarized text to minimize information loss in order to protect the shortcomings of the sequence-to-sequence model in which an information is lost when long texts are used. Through the experiment, the techniques proposed in this study are shown to be superior to the existing ones.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.1114-1117
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• 2004

Application of information technology for the construction area has been processed actively with the development of information technology. In this study, a framework of the Construction Specification IETM(Interactive Electronic Technical Manual) was suggested through the analysis of the Department of Defense(DoD)'s standards and the trend of techniques related to the IETM. As the Framework, the DFD(Data Flow Diagram) of the construction specification IETM's organizing and using procedure was suggested. And a Model of construction specification IETM was organized on the basis of DFD. Finally, a scenario was constructed by the pilot system which is based on the model. The application of the construction specification IETM would make efficient and effect task implementations possible. By that, in addition to the reduction of the cost and time, the quality enhancement from information missing protect effectiveness could be expected.

• ETRI Journal
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• v.24 no.2
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• pp.69-81
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• 2002

This paper reviews the existing research activities on signaling and control procedures for IP over optical networks. We focus on the IP-centric signaling and control architecture based on the generalized multi-protocol label switching (GMPLS) protocol and analyze various scenarios and technical issues for deploying the IP over an optical network. We analyze the signaling and operations and administration and maintenance requirements for integrating an IP network and an optical network in order to cope with the high bandwidth and poor resource granularity of the optical network, including the optical cross-connect system. On the basis of network architecture and a reference configuration model, we investigate the GMPLS-based control architecture and interconnection model appropriate for controlling IP bandwidth and optical lambda resources. The signaling and control procedure based on GMPLS on optical user-network interface and network-network interface are comparatively investigated to provide the optical lightpath. We also study protection and restoration procedures to protect link failure when it applies to generalized MPLS signaling.

• Journal of Convergence Society for SMB
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• v.6 no.2
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• pp.11-17
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• 2016

Recently, As the IT skills development, the different kinds of data (or information) generated by the company are becoming more frequent leaked to outside organizations and individuals. However, it is insufficient situation to reduce the dysfunctional corporate information at the enterprise level. In this paper, we propose a role-based enterprise information processing model to minimize the dysfunctions of corporate information. The proposed model is to allow you to set protect corporate information through the relevant departments for the management and supervision of enterprise information, and rapid and systematic recovery and operating strategy was to improve the efficiency of enterprise information services. The proposed model is caught blocking access to information access to information to establish a rapid and systematic recovery and operational continuity strategy after the administrator user permissions and roles that access to information is centrally managed by the user when the abnormality. In experimental results, virus damage was lower 48.8% than the previous model. In addition, information on the number of dysfunction distribution occurring within the company gained 17.9% lower results than the previous model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.6
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• pp.1256-1264
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• 2009

When unapproved users access to healthcare system and use medical information for other malicious purposes, it could severely threaten important information related to patients' life, because in ubiquitous environment healthcare service makes patient's various examination results, medical records or most information of a patient into data. Therefore, to solve these problems, we design RBAC(Role Based Access Control) for U-healthcare that can access control with location, time and context-awareness information like status information of user and protect patient's privacy. With implementation of the proposed model, we verify effectiveness of the access control model for healthcare in ubiquitous environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.657-660
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• 2021

A video information processing system (CCTV) requires comprehensive administrative, physical, and technical security management to collect, transmit and store sensitive information. However, there are no regulations related to video information processing, certification methods for the technology used, and application standards suitable for security technology. In this paper, we propose a cryptography, certification, protection, system (CCPS) model that can protect the system by including encryption technology for application to the video information processing system and authentication measures for the technology used in the system configuration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.742-756
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• 2022

A flood of information has occurred with the rise of the internet and digital devices in the fourth industrial revolution era. Every millisecond, massive amounts of structured and unstructured data are generated; smartphones, wearable devices, sensors, and self-driving cars are just a few examples of devices that currently generate massive amounts of data in our daily. Machine learning has been considered an approach to support and recognize patterns in data in many areas to provide a convenient way to other sectors, including the healthcare sector, government sector, banks, military sector, and more. However, the conventional machine learning model requires the data owner to upload their information to train the model in one central location to perform the model training. This classical model has caused data owners to worry about the risks of transferring private information because traditional machine learning is required to push their data to the cloud to process the model training. Furthermore, the training of machine learning and deep learning models requires massive computing resources. Thus, many researchers have jumped to a new model known as "Federated Learning". Federated learning is emerging to train Artificial Intelligence models over distributed clients, and it provides secure privacy information to the data owner. Hence, this paper implements Federated Averaging with a Deep Neural Network to classify the handwriting image and protect the sensitive data. Moreover, we compare the centralized machine learning model with federated averaging. The result shows the centralized machine learning model outperforms federated learning in terms of accuracy, but this classical model produces another risk, like privacy concern, due to the data being stored in the data center. The MNIST dataset was used in this experiment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.817-826
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• 2022

AI technology is being successfully introduced in many fields, and models deployed as a service are deployed with black box environment that does not expose the model's information to protect intellectual property rights and data. In a black box environment, attackers try to steal data or parameters used during training by using model output. This paper proposes a method of inferring the type of model to directly find out the composition of layer of the target model, based on the fact that there is no attack to infer the information about the type of model from the deep learning model. With ResNet, VGGNet, AlexNet, and simple convolutional neural network models trained with MNIST datasets, we show that the types of models can be inferred using the output values in the gray box and black box environments of the each model. In addition, we inferred the type of model with approximately 83% accuracy in the black box environment if we train the big and small relationship feature that proposed in this paper together, the results show that the model type can be infrerred even in situations where only partial information is given to attackers, not raw probability vectors.