• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.564-573
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• 1999

Recently, as the development and use of distributed multimedia services are growing explosively in every aspects of our lives, administrators of multimedia services are very concerned with providing users with reliable and efficient services. However, the management of distributed multimedia services is a very complex and troublesome work such that a flexible but powerful management system is necessary. This paper proposes a management system for managing CORBA-based distributed multimedia services. We have developed an architecture for the management system and defined a set of management services needed to monitor and control distributed multimedia services. The architecture consists of several objects, which perform configuration management, fault management, security management and event management. A generic distributed multimedia service (DMS) MIB has been defined for the management of various multimedia services and applications. In addition, as a proof of concept, we have developed a Web-based management system for a CORBA-based distributed multimedia system called MAESTRO. The prototype management system uses OrbixWeb to interface with the management server which is implemented as a set of CORBA objects. Though our management system has been developed for distributed multimedia services, it can easily manage other CORBA-based services and applications.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.139-146
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• 2015

WSN has been utilized in various directions from basic infrastructure of environment composition to business models including corporate inventory, production and distribution management. However, as energy organizations' private information, which should be protected safely, has been integrated with ICT such as WSN to be informatization, it is placed at potential risk of leaking out with ease. Accordingly, it is time to need secure sensor node deployment strategies for stable enterprise business. Establishment of fragmentary security enhancement strategies without considering energy organizations' security status has a great effect on energy organizations' business sustainability in the event of a security accident. However, most of the existing security level evaluation models for diagnosing energy organizations' security use technology-centered measurement methods, and there are very insufficient studies on managerial and environmental factors. Therefore, this study would like to diagnose energy organizations' security and to look into how to accordingly establish strategies for planning secure sensor node deployment strategies.

• Health Policy and Management
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• v.33 no.1
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• pp.29-39
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• 2023

Background: Breaking the chain of disease transmission from overseas is necessary to control new infectious diseases such as coronavirus disease 2019 effectively. In this study, we developed a mobile app called Self-Symptom Checker (SSC) to monitor the health of inbound travelers. Methods: SSC was developed for general users and administrators. The functions of SSC include non-repudiation using QR (quick response) codes, monitoring fever and respiratory symptoms, and requiring persons showing symptoms to undergo polymerase chain reaction tests at nearby screening stations following a review of reported symptoms by the Korea Disease Control and Prevention Agency, as well as making phone calls, via artificial intelligence or public health personnel, to individuals who have not entered symptoms to provide the necessary information. Results: From February 12 to March 27, 2020, 165,000 people who were subjected to the special entry procedure installed SSC. The expected number of public health officers and related resources needed per day would be 800 if only the phone was used to perform symptom monitoring during the above period. Conclusion: By applying SSC, more effective symptom monitoring was possible. The daily average number of health officers decreased to 100, or 13% of the initial estimate. SSC reduces the work burden on public healthcare personnel. SSC is an electronic solution conceived in response to health questionnaires completed by inbound travelers specified in the World Health Organization International Health Regulations as a requirement in the event of a pandemic.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6060-6070
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• 2012

Real-Time Enterprise (RTE)'s key requirement is that it should respond and adapt fast to the change of the firms' internal and external situations including the change of market and customers' needs. Recently, the big data processing technology to support the speedy change of the firms is spotlighted. Under the circumstances that wire and wireless communication networks are evolving with an accelerated rate, it is especially critical to provide a strong security monitoring function and stable services through a real-time processing of massive communication data traffic. By applying the big data processing technology based on a cloud computing architecture, this paper solves the managerial problems of telecommunication service providers and discusses how to operate the network management system effectively.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.233-238
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• 2020

In the cloud environment, IoT devices using sensors and wearable devices are being applied in various environments, and technologies that accurately determine the information generated by IoT devices are being actively studied. However, due to limitations in the IoT environment such as power and security, information generated by IoT devices is very weak, so financial damage and human casualties are increasing. To accurately collect and analyze IoT information, this paper proposes a topographic information-based key management technique that considers IoT information errors. The proposed technique allows IoT layout errors and groups topographic information into groups of dogs in order to secure connectivity of IoT devices in the event of arbitrary deployment of IoT devices in the cloud environment. In particular, each grouped terrain information is assigned random selected keys from the entire key pool, and the key of the terrain information contained in the IoT information and the probability-high key values are secured with the connectivity of the IoT device. In particular, the proposed technique can reduce information errors about IoT devices because the key of IoT terrain information is extracted by seed using probabilistic deep learning.

• International Journal of Contents
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• v.16 no.1
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• pp.75-86
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• 2020

As the elderly population is becoming an aging society, the elderly are experiencing many problems. Social security costs for the elderly are increasing and the un-linked social phenomenon is emerging. Thus, the social infrastructure and welfare system established in the past economic growth period are in danger of not functioning properly. People socially isolated or with chronic diseases among the elderly are exposed to various accidents. Thus, an active healthcare management service is imperative. Additionally, in the event of a dangerous situation, the system must have ways to notify guardians (family or medical personnel) regarding appropriate action. Thus, in this paper, we propose the smartphone-based healthcare and emergency response service platform. The proposed service platform aggregates movement of relevant data in real-time using a smartphone. Based on aggregated data, it will always recognize the user's movements and current state using the human motion recognition mechanism. Thus, the proposed service platform provides real-time status monitoring, activity reports, a health calendar, location-based hospital information, emergency situation detection, and cloud messaging server-based efficient notification to several subscribers such as family, guardians, and medical personnel. Through this service, users or guardians can augment the level of care for the elderly through the reports. Also, if an emergency situation is detected, the system immediately informs guardians so as to minimize the risk through immediate response.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.231-237
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• 2017

Threat intelligences collected from cyber incident sharing system and security events collected from Security Information & Event Management system are analyzed and coped with expanding malicious code rapidly with the advent of big data. Analytical classification of the threat intelligence in cyber incidents requires various features of cyber observable. Therefore it is necessary to improve classification accuracy of the similarity by using multi-profile which is classified as the same features of cyber observables. We propose a multi-profile ensemble model performed similarity analysis on cyber incident of threat intelligence based on both attack types and cyber observables that can enhance the accuracy of the classification. We see a potential improvement of the cyber incident analysis system, which enhance the accuracy of the classification. Implementation of our suggested technique in a computer network offers the ability to classify and detect similar cyber incident of those not detected by other mechanisms.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.896-905
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• 2021

In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.103-138
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• 2009

In this article we examine a unique data set of intraday fair disclosure(FD) releases to shed light on market efficiency within the trading day. Specifically, this paper analyze the response of stock prices on fair disclosure disseminated in real-time through KIND(Korea Investor's Network for Disclosure) on Korea stock exchange during the period from January 2003 to September 2004. We find that the prices of stock experiences a statistically and economically significant increase beginning seconds after the fair disclosure is initially announced and lasting approximately two minutes. The stock price responds more strongly to fair disclosure on smaller firm but the response to fair disclosure on the largest firm stock is more gradual, lasting five minutes. We also examine the profitability of a short-term trading strategy based on dissemination of fair disclosure. After controlling for trading costs we find that trader who execute a trade following initial disclosure generate negative profits, but trader buying stock before initial disclosure realize statistically significant positive profit after two minute of disclosure. Summarizing overall results, our evidence supports that security prices on Korea stock exchange reflects all available information within two minutes and the Korea stock market is semi-strongly efficient enough that a trader cannot generate profits based on widely disseminated news unless he acts almost immediately.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.562-574
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• 2012

Simulation validation techniques which have been employed in most studies are statistical analysis, which validate a model with mean or variance of throughput and resource utilization as an evaluation object. However, these methods have not been able to ensure the reliability of individual elements of the model well. To overcome the problem, the weighted F-measure method was proposed, but this technique also had some limitations. First, it is difficult to apply the technique to complex system environment with numerous values of interarrival time because it assigns a class to an individual value of interarrival time. In addition, due to unbounded weights, the value of weighted F-measure has no lower bound, so it is difficult to determine its threshold. Therefore, this paper propose weighted F-measure technique with cluster analysis to solve these problems. The classes for the technique are defined by each cluster, which reduces considerable number of classes and enables to apply the technique to various systems. Moreover, we improved the validation technique in the way of assigning minimum bounded weights without any lack of objectivity.