• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.93-104
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• 2021

In the process of the sustainable development of the world economy, the change and construction of urban living environment has always been the focus of people's attention. Therefore, the purpose of this study is to find out the potential safety hazards in residential areas, and put forward feasible improvement plans under the framework of CPTED theory.One is to collect the necessary literature. Secondly, according to the field investigation and questionnaire survey, sorting out the existing security risks. Finally, this paper puts forward the corresponding improvement and suggestion to this research. The conclusion is as follows: First, based on the six principles of CPTED theory, problems existing in Gamcheon Cultural Village, which is subject to research, were investigated. Second, six of the most serious safety issues (safety handle, landscaping, entrance control, signs, empty space, monitoring) were objectively analyzed, and designs were presented in terms of increasing safety stairs, installing automatic entrances, open access view, unifying signs, and building leisure areas.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.373-377
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• 2022

Wireless sensor networks are being used in various fields. Wireless sensor networks are applied in many areas, such as security, military detection, environmental management, industrial control, and home automation. There is a problem about the limit of energy that the sensor network basically has. In this paper, we propose the LEACH-CCBD (Low Energy Adaptive Clustering hierarchy - Centrailized with Cluster and Basestation Distance) algorithm that uses energy efficiently by improving network transmission based on LEACH-C among the representative routing protocols. The LEACH-CCBD algorithm is a method of assigning a cluster head to a cluster head by comparing the sum of the distance from the member node to the cluster distance and the distance from the cluster node to the base station with respect to the membership of the member nodes in the cluster when configuring the cluster. The proposed LEACH-CCBD used Matlab simulation to confirm the performance results for each protocol. As a result of the experiment, as the lifetime of the network increased, it was shown to be superior to the LEACH and LEACH-C algorithms.

• Journal of IKEEE
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• v.26 no.3
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• pp.380-388
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• 2022

The traditional malware detection technologies collect known malicious programs and analyze their characteristics. Then such a detection technology makes a blacklist based on the analyzed malicious characteristics and checks programs in the user's system based on the blacklist to determine whether each program is malware. However, such an approach can detect known malicious programs, but responding to unknown or variant malware is challenging. In addition, since such detection technologies generally monitor all programs in the system in real-time, there is a disadvantage that they can degrade the system performance. In order to solve such problems, various methods have been proposed to analyze major behaviors of malicious programs and to respond to them. The main characteristic of ransomware is to access and encrypt the user's file. So, a new approach is to produce the whitelist of programs installed in the user's system and allow the only programs listed on the whitelist to access the user's files. However, although it applies such an approach, attackers can still perform malicious behavior by performing a DLL(Dynamic-Link Library) injection attack on a regular program registered on the whitelist. This paper proposes a method to respond effectively to attacks using DLL injection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.17-22
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• 2022

In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.

• Journal of the Economic Geographical Society of Korea
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• v.24 no.2
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• pp.163-180
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• 2021

Nuclear power has been an attractive energy efficient and to the pressure with the climate change despite of its risks. There are safety, security, and environmental concerns with the nuclear radiation, but the techno-optimism forms the mainstream by experts and the state to be able to control and manage the risks yet occurred. The disastrous Chernobyl and Fukushima nuclear accidents brought about alternative action and thought including renewable energy expansion, efficient energy delivery and use, and enhancing stewardship to environmental carrying capacity. More significant alternative movement is sought by victims of nuclear radiation, technicians, and the general public who realized the pitfalls of expert and state centered policy formation. These laypersons become counter-expertise competent in recognizing local contamination and considering the risks and emotions seriously affecting peoples' everyday lives. They play important roles in the construction and legitimation of alternative knowledge about nuclear power widely realized across regions.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.48 no.4
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• pp.201-206
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• 2022

Objectives: Contemporary biometric technologies have been gaining traction in both public and private security sectors. Facial recognition is the most commonly used biometric technology for this purpose. We aimed to evaluate the ability of a publicly available facial recognition application program interface to calculate similarity scores of presurgical and postsurgical photographs of patients who had orthognathic surgery. Materials and Methods: Presurgical and postsurgical photographs of 75 patients who had orthognathic surgery between January 2018 and November 2020 in our department were used. Frontal photographs of patients in relaxed and smiling states were taken. The patients were classified into three groups: Group 2 had one-jaw surgery, Group 3 had two-jaw surgery to correct mandibular prognathism, and Group 4 had two-jaw surgery to correct facial asymmetry. For comparison, photographs of 10 participants were used as controls (Group 1). Two facial recognition application programs (Face X and Azure) were used to assess similarity scores. Results: The similarity scores in the two programs showed significant results. The similarity score of the control group, which did not undergo orthognathic surgery, was the highest. The results for Group 2, Group 3, and Group 4 were higher in the order of Group 2, Group 3, and Group 4. Conclusion: In this study, all orthodontic patients were recognized as the same person using the face recognition program before and after surgery. A significant difference in similarity results was obtained between the groups with both Face X and Azure and in both relaxed and smiling states.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.3
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• pp.27-36
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• 2022

Purpose : This study was aimed to analyze the effects of cosmetics containing Persicaria perfoliata water extract (PPWE) on the skin moisturizing and improvement of skin condition in clinical trials. Methods : Clinical trial was conducted for five weeks after IRB approval at Dong-Eui University. Out of a total of 64 people, 15 people each were assigned to four groups as follows; control group A, B, C and the experimental group A that using cosmetic containing PPWE. Skin condition was measured two times, before and after clinical trial, by a professional skin analyzer, SDM (skin diagnosis system). Moisture and oil value of participants was analyzed twice, each morning and evening, using a portable device on their cheeks. In addition, the survey was investigated subjective satisfaction on change in skin condition and the satisfaction on the use of cosmetics. Result : The experimental group exhibited subjectively significant changes before and after clinical trials on skin its dryness (p=.039), blush (p=.017), and redness (p<.001). In addition, subjective evaluation was also the highest satisfaction in aspects of number of application (p=.003), amount of application (p=.002), moisture maintenance, and skin scratching frequency. The satisfaction on the use of cosmetics was the highest in the intention to repurchase (p=.045), recommendation willingness to others (p=.020), and intention to use various products (p=.001). Skin moisture of the clinical trial participants using the SDM, moisture level and elasticity of the experimental group increased by 12.94 and 10.28. Moisture level, which was measured by a portable device, was the most potently increased in the experimental group. Conclusion : Consequently, PPWE containg cosmetics exhibited the effects of moisturization and attenuated skin dryness in clinical trials, which might be utilized as a fundamental data to develop numerous lines of cosmetics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.184-186
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• 2022

Recently, as interest in personal information protection has increased, various apps for personal information protection have emerged. These apps protect data in various formats, such as photos, videos, and documents containing personal information, using encryption and hide functions. These apps can have a positive effect on personal information protection, but in digital forensics, they act as anti-forensic because they can be difficult to analyze data during the investigation process. In this paper, finds out PIN, an access control function, through reverse engineering on Calculator - photo vault, one of the personal information protection apps, and files such as photos and documents to which encryption and hide were applied. In addition, the vulnerability to this app was analyzed by research decryption for database files where logs for encrypted and hide files are stored.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.7-17
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• 2017

In this paper, we propose the TPS (TPM-enhanced Privacy Protection System) which is an automated privacy protection system enhanced with a TPM (Trusted Platform Module). The TPS detects documents including personal information by periodic scanning the disk of clients at regular intervals and encrypts them. Hence, system manages the encrypted documents in the server. In particular, the security of TPS was greatly enhanced by limiting the access of documents including the personal information with regard to the client in an abnormal state through the TPM-based platform verification mechanism of the client system. In addition, we proposed and implemented a VTF (Virtual Trusted File) interface to provide users with the almost identical user interface as general document access even though documents containing personal information are encrypted and stored on the remote server. Consequently, the TPS automates the compliance of the personal information protection acts without additional users' interventions.