• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3966-3991
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• 2018

Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.231-239
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• 2006

For such large-scale software as for operating a switching system, the use of real-time databases is essential for data exchanges among various functions and their data processing. Under the environment of developing the DBMS software for a switching system, the application program including database manipulations is first developed on a host computer and then the developed program is loaded into a switching system for its tests. To make it possible for DBMS manipulation software to be developed on a host computer rather than a switching system itself, we developed a host-based DBMS simulation system(HDBMS). In this paper we presented the roles and functions of HDBMS, its system structure, and the technical details for implementing HDBMS.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.37-42
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• 2015

In this paper, we propose malware database in mobile memory for realtime malware URL detection and we support realtime malware URL detection engine, that is control the web service for more secure mobile service. Recently, mobile malware is on the rise and to be new threat on mobile environment. In particular the mobile characteristics, the damage of malware is more important, because it leads to monetary damages for the user. There are many researches in cybercriminals prevention and malware detection, but it is still insufficient. Additionally we propose the method for prevention Smishing within SMS, MMS. In the near future, mobile venders must build the secure mobile environment with fundamental measures based on our research.

• Journal of Convergence Society for SMB
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• v.5 no.4
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• pp.37-42
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• 2015

Due to the advance of ICT, a variety of attacks have been developing and active. Recently, APT attacks using malicious codes have frequently occurred. Advanced Persistent Threat means that a hacker makes different security threats to attack a certain network of a company or an organization. Exploiting malicious codes or weaknesses, the hacker occupies an insider's PC of the company or the organization and accesses a server or a database through the PC to collect secrets or to destroy them. The paper suggested a countermeasure to cope with APT attacks through an APT attack process. It sought a countermeasure to delay the time to attack taken by the hacker and suggested the countermeasure able to detect and remove APT attacks.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.149-156
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• 2008

In this paper, we develope the Exhibition Grounds Management System utilizing the ubiquitous computing which integrates the RFID ubiquitous main technology, existing use technology Bar-code, the Mobile communication technology for IT main technology field. The developed system consists of the program for exhibition information. the visitor registration program, manager program and mobile program for the visitor's current location inquiry and the exhibition management. This system is realized and designed based on database, web program, mobile program, wireless telecommunication technology. The automation technology utilizing the developed RFID system and the Exhibition Grounds Management System integrated with the wireless packet telecommunication using the mobile telecommunication technology could have a ripple effect on whole information industrial application fields.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.358-362
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• 2011

The National Emergency Management Agency of South Korea has established a Disaster Victims Psychology Support Center. The Disaster Victims Psychology Support Center can enable victims who got psychological damage from disasters to return to their daily lives through healing activity, field visits and advice of experts. The previous Psychology Support Center System managed the information of disaster victims through an independent database. However, this paper proposes a system that is developed to identify medical institutions and mental health centers within a distance of radius, based on the potential Hot-Spot areas of disaster victims using the GIS Systems. The proposed system can efficiently support selection of appropriate institutions for disaster victims using their location and age, classification of damage, and damaged parts of the body. Also, this spatial analysis can assist to decide on a policy based on the location of disaster victims and the extent of damage. Therefore, this paper can provide the required information to support decision making based on the concentrated areas for disaster victims.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3191-3196
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• 2011

Smart home system are being installed in the most new construction of building for the convenience of living life. As smart home systems are becoming more common and their diffusion rates are faster, hacker's attack for the smart home system will be increased. In this paper, Risk level of smart home's to do respond to intrusion that occurred from the wired network and wireless network intrusion cases and attacks can occur in a virtual situation created scenarios to build a database. This is based on the smart home users vulnerable to security to know finding illegal intrusion traffic in real-time and attack prevent was designed the intrusion detection algorithm.

• Proceedings of the KIEE Conference
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• summer
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• pp.88-90
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• 2004

Data are a critical utility asset. Collecting correct data on site leads to accurate information. Data, when gathered with foresight & properly formatted, are useful to both existing database and easily transferable to newer, more comprehensive historical outage data. However, when investigating data items options, the task, can be an arduous one, often requiring the efforts of entire committees. This paper firstly discusses the KEPCO's past 10 years of historical outage data which include meterological data, and also by several elements of the National Weather Service, failure rate, outage duration, and probability classification, etc. Then, these collected data are automatically stored in an Outage Data Management System (ODMS), which allows for easy access and display. ODMS has a straight-forward and easy-to-use interface. It lets you to navigate through modules very easily and allows insertion, deletion or editing of data. In particular, this will further provide the KEPCO that not only helps with probabilistic security assessment but also provides a platform for future development of Probability Estimation Program (PEP).

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.23-28
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• 2021

In this paper, we studied a system that can efficiently build security management for single-person households using Arduino, ESP32-CAM and PIR sensors, and proposed an Android app with an internet connection. The ESP32-CAM is an Arduino compatible board that supports both Wi-Fi, Bluetooth, and cameras using an ESP32-based processor. The PCB on-board antenna may be used independently, and the sensitivity may be expanded by separately connecting the external antenna. This system has implemented an Arduino-based Unauthorized intrusion system that can significantly help prevent crimes in single-person households using the combination of PIR sensors, Arduino devices, and smartphones. unauthorized intrusion system, showing the connection between Arduino Uno and ESP32-CAM and with smartphone applications. Recently, if daily quarantine is underway around us and it is necessary to verify the identity of visitors, it is expected that it will help maintain a safety net if this system is applied for the purpose of facial recognition and restricting some access. This technology is widely used to verify that the characters in the two images entered into the system are the same or to determine who the characters in the images are most similar to among those previously stored in the internal database. There is an advantage that it may be implemented in a low-power, low-cost environment through image recognition, comparison, feature point extraction, and comparison.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1494-1507
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• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.