• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.447-452
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• 2013

Vessel traffic system uses multiple sea surveillance radars as a primary sensor to obtain maritime traffic information like as ship's position, speed, course. The systematic errors such as the range bias and the azimuth bias of the two-dimensional radar system can significantly degrade the accuracy of the radar image and target tracking information. Therefore, the systematic errors of the radar system should be corrected precisely in order to provide the accurate target information in the vessel traffic system. In this paper, it is proposed that the method compensates the range bias and the azimuth bias using AtoN information installed at VTS coverage. The radar measurement residual error model is derived from the standard error model of two-dimensional radar measurements and the position information of AtoN, and then the linear Kalman filter is designed for estimation of the systematic errors of the radar system. The proposed method is validated via Monte-Carlo runs. Also, the convergence characteristics of the designed filter and the accuracy of the systematic error estimates according to the number of AtoN information are analyzed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.1-11
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• 2002

This study set up a purpose in the efficient utilization of security target objects. This purpose is the following: Firstly, this study analyzed problem about deleted areas for security described on aerial photography image. Secondly, this study made clustering and labeling to recognize censored areas of image. Finally, this study tried to maximize various utilizability of digital image data through postprocessing algorithm. Based on these courses, the results of this study appeared that brightness value of image increased depending on topography and quantities of topographic features. It was estimated that these was able to utilized by useful estimative data in judging information of topography and topographic features included in the total image. Besides, in the image recognition and postprocessing, the better result value was not elicited than in a mountainous region. Because it was included that a lots of topography and topographic features was similarly recognized with the process for deletion of the existing security target objects in urban and suburb region. This result appeared that the topography and quantities of topographic features absolutely affected the recognition and processing of image.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.545-558
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• 2020

The gaze-based input provides feedback to confirm that the typing is correct when the user types the text. Many studies have already demonstrated that feedback can increase the usability of gaze-based inputs. However, because the information of the typed text is revealed through feedback, it can be a target for shoulder-surfing attacks. Appropriate feedback needs to be used to improve security without compromising the usability of the gaze-based input using the original feedback. In this paper, we propose a new gaze-based input method, FFI(Fake Flickering Interface), to resist shoulder-surfing attacks. Through experiments and questionnaires, we evaluated the usability and security of the FFI compared to the gaze-based input using the original feedback.

• KEPCO Journal on Electric Power and Energy
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• v.3 no.2
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• pp.73-78
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• 2017

Recently, a number of foreign electric power companies including domestic Korea Electric Power Corporation (KEPCO) have actively engaged in the construction of a power grid with the concept of a smart grid. The Smart grid is a technology that increases the efficiency of the power by converging the information network with the power grid. It can maximize the energy efficiency through the two-way communication between the utility and the consumer. However, as the power grid converges with the information and communication network, security threats are increasing more than existing power grids. Due to the nature of the power grid, the damage caused by security threats is not only personal privacy but also economic loss of society. So smart grid becomes the target of hackers. In this paper, we discuss security vulnerabilities of Advanced Metering Infrastructure (AMI), which is a core technology of smart grid construction, and the corresponding security technologies to prevent security damage of smart grid.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.1001-1011
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• 2014

Smart Grid Devices could have security vulnerabilities that have legacy communication networks because of the fact that Smart Grid employs bi-directional communications and adopted a variety of communication interface. Consequently, it is required to build concrete response processes and to minimize the damage of the cyber attacks including security evaluation and certification methods. DCU is designed to collect meter data from numerous smart meter and send to utility's server so DCU installed between smart meter and utility's server. For this reason, If DCU compromised by attacker then attacker could use DCU to launching point for and attack on other devices. However, DCU's security evaluation and certification techniques do not suffice to be deployed in smart grid infrastructure. This work development DCU protection profile based on CC, it is expected that provide some assistance to DCU manufacturer for development of DCU security target and to DCU operator for help safety management of DCU.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.30-38
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• 2015

IT security service provides customers with the capability of protecting the networked information asset and infrastructures, and the scope of security service is expanding from a technology-intensive task to a comprehensive protection system for IT environment. To improve the quality of this service, a research model which help assess the quality is required. Several research models have been proposed and used in various service areas, but few cases are found for IT security service. In this work, a research model for the IT security quality has been proposed, based on research models such as SERVQUAL and E-S-QUAL. With the proposed model, factors which affect the service quality and the best quality measure have been identified. And the feasibility of using quantitative measures for quality has been examined. For analysis, structural equation modeling and various statistical methods such as principal component analysis were used. The result shows that satisfaction is the most significant measure affected by the proposed quality factors. Two quality factors, fulfillment and empathy, are the main determinants of the service quality. This leads to a strategy of quality improvement based on factors of emotion and perception, not of technology. The quantitative measures are considered as promising alternative measures, when combined with other measures. In order to design reliable quantitative measures, more work should be done on target processing time and users' expectation. It is hoped that work of this research will provide efficient tools and methods to improve the quality of IT security service and help future research works for other IT service areas.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.807-819
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• 2019

Greybox fuzzing is known as an effective method to discover unknown security flaws reside in software and has been actively researched today. However, most of greybox fuzzing tools require an executable file. Because of this, a library, which cannot be executed by itself requires an additional executable file for greybox fuzzing. Generating such an executable file is challengeable because it requires both understanding of the library and fuzzing. In this research, we suggest the approach to generate an executable file automatically for a library and implement this approach as a tool based on the LLVM framework. This tool shows that executable files and seed files can be generated automatically by static/dynamic analysis of a unit test in the target project. A generated executable file is compatible with various greybox fuzzers like AFL because it has a common interface for greybox fuzzers. We show the performance of this tool as code coverage and discovered unknown security bugs using generated executable files and seed files from open source projects through this tool.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.541-547
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• 2019

Recent developments in hacking technology are continuing to increase the number of new security vulnerabilities. Approximately 80,000 new vulnerabilities have been registered in the Common Vulnerability Enumeration (CVE) database, which is a representative vulnerability database, from 2010 to 2015, and the trend is gradually increasing in recent years. While security vulnerabilities are growing at a rapid pace, responses to security vulnerabilities are slow to respond because they rely on manual analysis. To solve this problem, there is a need for a technology that can automatically detect and patch security vulnerabilities and respond to security vulnerabilities in advance. In this paper, we propose the technology to extract the features of the vulnerability-discovery target binary through complexity analysis, and select a vulnerability-discovery strategy suitable for the feature and automatically explore the vulnerability. The proposed technology was compared to the AFL, ANGR, and Driller tools, with about 6% improvement in code coverage, about 2.4 times increase in crash count, and about 11% improvement in crash incidence.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.4
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• pp.53-60
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• 2007

In a known plaintext scenario, fast correlation attack is very powerful attack on stream ciphers. Most of fast correlation attacks consider the cryptographic problem as the suitable decoding problem. In this paper, we introduce advanced multi-pass fast correlation attack which is based on the fast correlation attack, which uses parity check equation and Fast Walsh Transform, proposed by Chose et al. and the Multi-pass fast correlation attack proposed by Zhang et al. We guess some bits of initial states of the target LFSR with the same method as previously proposed methods, but we can get one more bits at each passes and we will recover the initial states more efficiently.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.225-238
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. In this paper, we propose a framework for user behavior analysis for bot detection in online games. Specifically, we focus on party play that reflects the social activities of gamers: In a Massively Multi-user Online Role Playing Game (MMORPG), party play log includes a distinguished information that can classify game users under normal-user and abnormal-user. That is because the bot users' main activities target on the acquisition of cyber assets. Through a statistical analysis of user behaviors in game activity logs, we establish the threshold levels of the activities that allow us to identify game bots. Also, we build a knowledge base of detection rules based on this statistical analysis. We apply these rule reasoner to the sixth most popular online game in the world. As a result, we can detect game bot users with a high accuracy rate of 95.92%.