• Journal of Information Processing Systems
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• v.13 no.1
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• pp.68-82
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• 2017

Nowadays, geographic information system (GIS) is developed and implemented in many areas. A huge volume of vector map data has been accessed unlawfully by hackers, pirates, or unauthorized users. For this reason, we need the methods that help to protect GIS data for storage, multimedia applications, and transmission. In our paper, a selective encryption method is presented based on vertex randomization and hybrid transform in the GIS vector map. In the proposed algorithm, polylines and polygons are focused as the targets for encryption. Objects are classified in each layer, and all coordinates of the significant objects are encrypted by the key sets generated by using chaotic map before changing them in DWT, DFT domain. Experimental results verify the high efficiency visualization by low complexity, high security performance by random processes.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.99-105
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• 2021

The cloud computing evolution has brought us increasing necessity to manage virtual resources. For this reason, Kubernetes has developed to realize autonomous resource management in a large scale. It provides cloud computing infrastructure to handle cluster creations and deletions in a secure virtual computing environment. In the paper, we provide a monitoring scheme in which users can observe securely encrypted protocols while each Kubernetes component exchanges their packets. Eventually, users can utilize the proposed scheme for debugging as well as monitoring.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.177-188
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• 2024

As technology evolves, Internet usage continues to grow, resulting in a geometric increase in network traffic and communication volumes. The network path selection process, which is one of the core elements of the Internet, is becoming more complex and advanced as a result, and it is important to effectively manage and analyze it, and there is a need for a representation and visualization method that can be intuitively understood. To this end, this study designs a framework that analyzes network data using BGP, a network path selection method, and applies it to the cyber common operating picture for situational awareness. After that, we analyze the visualization elements required to visualize the information and conduct an experiment to implement a simple visualization. Based on the data collected and preprocessed in the experiment, the visualization screens implemented help commanders or security personnel to effectively understand the network situation and take command and control.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.303-314
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• 2018

In the past few years, government agencies and corporations have succumbed to stealthy, tailored cyberattacks designed to exploit vulnerabilities, disrupt operations and steal valuable information. Security Information and Event Management (SIEM) is useful tool for cyberattacks. SIEM solutions are available in the market but they are too expensive and difficult to use. Then we implemented basic SIEM functions to research and development for future security solutions. We focus on collection, aggregation and analysis of real-time logs from host. This tool allows parsing and search of log data for forensics. Beyond just log management it uses intrusion detection and prioritize of security events inform and support alerting to user. We select Elastic Stack to process and visualization of these security informations. Elastic Stack is a very useful tool for finding information from large data, identifying correlations and creating rich visualizations for monitoring. We suggested using vulnerability check results on our SIEM. We have attacked to the host and got real time user activity for monitoring, alerting and security auditing based this security information management.

• 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.

• Advanced Industrial SCIence
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• v.2 no.1
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• pp.15-20
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• 2023

The purpose of this study is to analyze the changes and importance of welfare policies in Chungcheong Province using big data analysis technology in the era of the Fourth Industrial Revolution, and to propose stable welfare policies for all generations, including the socially underprivileged. Chungcheong-do policy-related big data is coded in Python, and stable government policies are proposed based on the results of visualization analysis. As a result of the study, the keywords of Chungcheong-do government policy were confirmed in the order of region, society, government and support, education, and women, and welfare policy should be strengthened with a focus on improving local health policy and social welfare. For future research direction, it will be necessary to compare overseas cases and make policy proposals on the stable impact of national welfare policies.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.1 s.24
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• pp.72-79
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• 2006

This study was focused on analyzing mathematical model for optimal allocation of surveillance equipment which is operated on the natural geographical condition, such as DMZ fence area. Optimal allocation algorithm was studied for the equipment to develop the whole surveillance and watch model for the two area as testing. Also 3D visualization program was developed to display and analyze the detecting effect. The results show that our suggested model will be available for enhancing security condition on the watching area.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1495-1502
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• 2015

Dashboard camera is important system to store the variable data that not only video but also non-visual information that state of vehicle such as accelerometer, speed, direction. Non-visual information include variable data that can't visualization, so it used important evidence to figure out the situation in accident. It could be missed to non-visual information what can be prove the case in the just digital video forensic procedure. In this paper, We proposal the digital forensic analysis procedure for dashboard camera to all data in dashboard camera extract and analysis data for investigating traffic accident case. And I analyze to some products in with this digital forensic analysis procedure.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.131-134
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• 2020

스마트시티로 가는 첫걸음이자 핵심이라 할 수 있는 IoT 기술이 우리의 삶을 변화시키고 있다. 원격에서 집 내부의 상태를 확인하며 조정할 수 있고, 집 내부의 상황도 영상을 통해 확인할 수 있게 되었다. 이처럼 IoT 기술은 우리 삶의 편리함을 제공하고 중요한 요소가 되었지만, IoT 환경 관리의 주체가 사용자 개인이거나 IoT 환경상태를 모니터링하며 관리할 수 있는 수단이 없어 관리가 되지 않고 있고 공격을 받아도 사용자가 알 수 없다는 특성 때문에 IoT 보안에 있어 심각한 문제를 일으킬 수 있다. 이러한 문제에도 불구하고 IoT 보안에 대한 인식과 IoT 환경에 특화된 관리 시스템은 갖춰지지 않고 있다. 본 논문에서는 오픈 소스 데이터 분석 및 시각화 솔루션인 Elastic Stack을 활용하여 손쉽게 IoT 환경을 관리하고 상태를 시각화하여 제공하는 IoT 환경 관리 시스템을 제안한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.382-389
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• 2018

Recently cyber attacks can cause serious damage on various information systems. Log data analysis would be able to resolve this problem. Security log analysis system allows to cope with security risk properly by collecting, storing, and analyzing log data information. In this paper, a security log analysis system is designed and implemented in order to analyze security log data using the Logstash in the Elasticsearch, a distributed search engine which enables to collect and process various types of log data. The Kibana, an open source data visualization plugin for Elasticsearch, is used to generate log statistics and search report, and visualize the results. The performance of Elasticsearch-based security log analysis system is compared to the existing log analysis system which uses the Flume log collector, Flume HDFS sink and HBase. The experimental results show that the proposed system tremendously reduces both database query processing time and log data analysis time compared to the existing Hadoop-based log analysis system.