• Journal of Digital Convergence
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• v.17 no.1
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• pp.347-356
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• 2019

Recently, the liberalization of industrial control systems has been accompanied by a major change in the structural paradigm of information systems in the public and public sectors, and potential cyber security problems in the future major infrastructure control systems that cannot respond to the level of security of existing information systems. To cope with this, a cyber security evaluation tool that can evaluate security vulnerability in three dimensions against various infrastructure control system environment is needed. However, a cyber security evaluation in the domestic environments does not have the concept of the current security status and satisfy settings of the infrastructure. Also, the most of items in that environments have had short-term inspection themselves which makes a limitation by a technical area. In order to overcome this problems, many researches are needed to apply CSET (Cyber Security Evaluation Tool) which is the US cyber security evaluation tool to the control environment of various domestic infrastructure. In this paper, first, we analyze methods to apply to the major domain through the analysis of various case studies on existing security assessement tools. Finally, we discuss future directions.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.39-51
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• 2021

Recently, there has been much interest in practical use of standardized HD map that can effectively define roads, lanes, junctions, road signs, and road facilities in autonomous driving. Various kinds of de jure or de facto standards such as ISO 22726-1, ISO 14296, HERE HD Live map, NDS open lane model, OpenDRIVE, and NGII HD map are currently being used. However, there are lots of differences in data modeling among these standards, it makes difficult to use them together in autonomous driving. Therefore, we propose a data model conversion method to enable an efficient use of various kinds of HD map standards in autonomous driving in this study. Specifically, we propose a conversion method between the NGII HD map model, which is easily accessible in the country, and the OpenDRIVE model, which is commonly used in the autonomous driving industry. The proposed method consists of simple conversion of NGII HD map layers into OpenDRIVE objects, new OpenDRIVE objects creation corresponding to NGII HD map layers, and linear transformation of NGII HD map layers for OpenDRIVE objects creation. Finally, we converted some test data of NGII HD map into OpenDRIVE objects, and checked the conversion results through Carla simulator. We expect that the proposed method will greatly contribute to improving the use of NGII HD map in autonomous driving.

• Korean Journal of Optics and Photonics
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• v.33 no.6
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• pp.267-274
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• 2022

In this paper, we report the design and fabrication of binary diffractive optical elements (DOEs) for random-dot-pattern projection for Schlieren imaging. We selected the binary phase level and a pitch of 10 ㎛ for the DOE, based on cost effectiveness and ease of manufacture. We designed the binary DOE using an iterative Fourier-transform algorithm with binary phase optimization. During initial optimization, we applied a computer-generated pseudorandom dot pattern of uniform intensity as a target pattern, and found significant intensity nonuniformity across the field. Based on the evaluation of the initial optimization, we weighted the target random dot pattern with Gaussian profiles to improve the intensity uniformity, resulting in the improvement of uniformity from 52.7% to 90.8%. We verified the design performance by fabricating the designed binary DOE and a beam projector, to which the same was applied. The verification confirmed that the projector produced over 10,000 random dot patterns over 430 mm × 430 mm at a distance of 5 meters, as designed, but had a slightly less uniformity of 84.5%. The fabrication errors of the DOE, mainly edge blurring and spacing errors, were strong possibilities for the difference.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.63-73
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• 2008

RFID(Radio Frequency IDentification) system is an automated identification system that basically consists of tags and readers and Back-End-Databases. Tags and Readers communicate with each other by RF signal. As a reader can identify many tags in contactless manner using RF signal, RFID system is expected to do a new technology to replace a bar-code system in supply-chain management and payment system and access control and medical record and so on. However, RFID system creates new threats to the security of systems and privacy of individuals, Because tags and readers communicate with each other in insecure channel using RF signal. So many people are trying to study various manners to solve these problems against attacks, But they are difficult to apply to RFID system based on EPCglobal UHF Class-1 Generation-2 tags. Recently, Chien and Chen proposed a mutual Authentication protocol for RFID conforming to EPCglobal UHF Class-1 Generation-2 tags. we discover vulnerabilities of security and inefficiency about their protocol. Therefore, We analyze vulnerabilities of their protocol and propose an efficient mutual authentication protocol that improves security and efficiency.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.103-112
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• 2021

In recent years, public bicycle systems are widely spread over the world according to the development of ICT technology. Since the public bicycle systems in large cities need to secure both publicity and convenience for citizens, analysis of various their issues from introduction to operation is required. In addition, it is also necessary to prepare for various scenarios for coexistence with the PM business, which is recently in the spotlight as a last mile means and normally managed privately. This paper introduces modeling and simulation for efficient operations of public bicycle systems. In particular, the proposed method was developed in a form that can be easily used in other cities by modeling the general structure and behavior of the public bicycle system, and it was developed to facilitate modification and expansion of the future model with a component-based model configuration. This paper provides a case study of the propose method, which is the public bicycle simulation in Sejong City. The simulation results were derived by applying the data from the public bicycle system of Sejong City, and they were verified with the associated real data of Sejong City. Using the verified model, it is expected that it can be used as a tool to design and analyze various services on the public bicycle systems, which were especially suitable for Sejong City.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.1-7
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• 2022

Recently, as the use of applications such as big data programs and machine learning programs that are driven while generating large amounts of data in the program itself becomes common, the existing main memory alone lacks memory, making it difficult to execute the program quickly. In particular, the need to derive results more quickly has emerged in a situation where it is necessary to analyze whether the entire sequence is genetically altered due to the outbreak of the coronavirus. As a result of measuring performance by applying large-capacity data to a computing system equipped with a self-developed memory pool MOCA host adapter instead of processing large-capacity data from an existing SSD, performance improved by 16% compared to the existing SSD system. In addition, in various other benchmark tests, IO performance was 92.8%, 80.6%, and 32.8% faster than SSD in computing systems equipped with memory pool MOCA host adapters such as SortSampleBam, ApplyBQSR, and GatherBamFiles by task of workflow. When analyzing large amounts of data, such as electrical dielectric pipeline analysis, it is judged that the measurement delay occurring at runtime can be reduced in the computing system equipped with the memory pool MOCA host adapter developed in this research.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.87-94
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• 2022

Recently, with the development of information and communication infrastructure, the number of Internet access devices is rapidly increasing. Smartphones, laptops, computers, and even IoT devices are receiving information and communication services through Internet access. Since most of the device operating environment consists of web (WEB), it is vulnerable to web cyber attacks using web shells. When the web shell is uploaded to the web server, it is confirmed that the attack frequency is high because the control of the web server can be easily performed. As the damage caused by the web shell occurs a lot, each company is responding to attacks with various security devices such as intrusion prevention systems, firewalls, and web firewalls. In this case, it is difficult to detect, and in order to prevent and cope with web shell attacks due to these characteristics, it is difficult to respond only with the existing system and security software. Therefore, it is an automated defense system through the collection and analysis of web shells based on artificial intelligence machine learning that can cope with new cyber attacks such as detecting unknown web shells in advance by using artificial intelligence machine learning and deep learning techniques in existing security software. We would like to propose about. The machine learning-based web shell defense system model proposed in this paper quickly collects, analyzes, and detects malicious web shells, one of the cyberattacks on the web environment. I think it will be very helpful in designing and building a security system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.27-33
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• 2023

Countries around the world are calling for stronger law enforcement to combat the production and distribution of child sexual exploitation images, such as child grooming. Given the scale and importance of this social problem, it requires extensive cooperation between law enforcement, government, industry, and government organizations. In the wake of the Nth Room Case, there have been some amendments to the Enforcement Decree of the Telecommunications Business Act regarding additional telecommunications services provided by precautionary operators in Korea. While Naver and others in Korea use Electronics and Telecommunications Research Institute's own technology to filter illegal images, Microsoft uses its own PhotoDNA technology. Microsoft's PhotoDNA is so good at comparing and identifying illegal images that major global operators such as Twitter are using it to detect and filter images. In order to meet the Korean government's testing standards, Microsoft has conducted more than 16 performance tests on "PhotoDNA for Video 2.0A," which is being applied to the Bing service, in cooperation with the Korea Communications Commission and Telecommunications Technology Association. In this paper, we analyze the cases that did not pass the standards and derive improvement measures related to adding logos. In addition, we propose to use three video datasets for the performance test of filtering against illegal videos.

• Smart Media Journal
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• v.13 no.2
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• pp.68-84
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• 2024

This paper describes the development of a system and algorithms for high-quality welfare services by recognizing behavior development indicators (activity, sociability, danger) in children aged 0 to 2 years old using action recognition technology. Action recognition targeted 11 behaviors from lying down in 0-year-olds to jumping in 2-year-olds, using data directly obtained from actual videos provided for research purposes by three nurseries in the Gwangju and Jeonnam regions. A dataset of 1,867 actions from 425 clip videos was built for these 11 behaviors, achieving an average recognition accuracy of 97.4%. Additionally, for real-world application, the Edge Video Analyzer (EVA), a behavior analysis device, was developed and implemented with a region-specific random frame selection-based PoseC3D algorithm, capable of recognizing actions in real-time for up to 30 people in four-channel videos. The developed system was installed in three nurseries, tested by ten childcare teachers over a month, and evaluated through surveys, resulting in a perceived accuracy of 91 points and a service satisfaction score of 94 points.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.34 no.3
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• pp.79-85
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• 2024

We investigated the crystal structural property and chemical bonding nature of cellulose nanocrystal extracted directly from cotton cellulose using high-pressure homogenizer. The nanowire-like cellulose nanocrystals were randomly distributed in the form of a dense mesh. Based on calculating the interplanar distance of the Bragg-diffracted crystal plane observed through X-ray diffraction (XRD) analysis, it was found that the cellulose nanocrystals formed by high-pressure homogenizer had a monoclinc crystal structure, corresponding to the cellulose Iβ sub-polymorph. Solid-state nuclear magnetic resonance (NMR) analysis for the quantitatively evaluation of the amorphous region in cellulose nanocrystals revealed that the crystallinity index of cellulose nanocrystals was calculated to be 53.06 %. The O/C ratio of the surface of cellulose nanocrystal was estimated to be 0.82. Further analysis showed that chemical bonds of C-C bond or C-H bond, C-O bond, O-C-O bond or C=O bond, and O-C=O bond were the main chemical bonding states of the cellulose nanocrystal surface.