• Journal of Environmental Impact Assessment
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• v.15 no.4
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• pp.271-277
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• 2006

In this study, we investigated the applicable plan of GIS on the environmental impact assessment of 60 Hz Powerline. So we assessed distance data based on calculations by use of 2D and 3D Geographical information systems(GIS) and distance data based on measurements on 1: 5000 maps accord with on site distance measurements to use input data for calculating magnetic field. One hundred eight of the on site measured addresses were selected from residences. The data were achieved by measuring the distance between residence and power line on maps with scales of 1: 5000. The digital map was obtained from National Geographic Information Institute with scales of 1: 5000, and we made 2D and 3D map. Correlation analyses were performed for statistical analyses. For the 3D GIS versus on site comparison of different exposure categories, 70 of 108 measurements were assigned to the correct category. Similarly for 2D GIS versus on site comparison, 71 of 108 were correctly categorized. When comparing map measurement with on site measurement, 62 of 108 were correctly categorized. When the correlation analysis was performed, best correlation was found between 3D GIS and on site measurements with r = 0.84947 (p<0.0001). The correlation between map and on site measurement yielded an r of 0.76517 (p<0.0001). Since the GIS measurements and map measurement were made from the center point in the building and the on site measurements had to be made from the closest wall on the building, this might introduce and additional error in urban areas. The difference between 2D and 3D calculations were resulted from the height of buildings.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.856-858
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• 2013

The data which is sensed on USN(Ubiquitous Sensor Network) environment is concerned with personal privacy and the secret information of business, but it has more vulnerable characteristics, in contrast to common networks. In other words, USN has the vulnerabilities which is easily exposed to the attacks such as the eavesdropping of sensor information, the distribution of abnormal packets, the reuse of message, an forgery attack, and denial of service attacks. Therefore, the key is necessarily required for secure communication between sensor nodes. This paper proposes a KDPC(Key Distribution Protocol based on Cluster) using ECDH algorithm by considering the characteristics of sensor network. As a result, the KDPC can provide the safe USN environment by detecting the forgery data and preventing the exposure of sensing data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1409-1415
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• 2013

With the development of Internet communication and the use of a variety of online services has been greatly expanded. Therefore, the importance of authentication techniques for users of online services has increased. The most commonly used methods for user authentication is a technique that utilizes a prearranged password. However, the existing password scheme for authentication must use the same password every time. Therefore, the password being leaked by attackers, it can be used maliciously. In this paper, we proposed the Variable Password Generation Method in Internet Authentication System that generates a new password using information such as the access date, time, and IP address when user logs in. The method proposed in this paper prevents disclosure of personal information due to password exposure and improves the reliability and competitiveness in the field of security systems.

• Journal of Dairy Science and Biotechnology
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• v.40 no.1
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• pp.35-47
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• 2022

The taste preference for cheese is primarily dependent on an individual's habitual experience, such as personal memories since childhood. Cheese is not a traditional food in Korea, and therefore, the liking of cheese is acquired mainly through the exposure to European natural cheese by frequent travels rather than habitual experience. Although Korean dairy farms started the production of European style natural cheese because of surplus milk undulation, yet its demand has been consistently increasing in the last decade. Most of the mountain cheese variety in Europe are produced during the summer season on mountain pastures, especially in countries surrounded by the Alps. Nevertheless, not only consumers but also mountain cheese producers cannot comprehensively explain the differences in the nutritional properties of the milk from cows that grazed on mountain pasture and cows that were raised indoors. As the demand for cheese consumption is steadily increasing in Korea, it is necessary to study the effects of providing marketing information regarding the health conditions and rearing system of dairy cows in relation to the nutritional composition of cheese. In addition to the marketing focus on health-promoting unsaturated fatty acid composition of milk and cheese, the relationship between providing the marketing information on the raising environments of cows and the overall liking of mountain cheese were also investigated.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.465-474
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• 2023

As the effective use and strong protection of an organization's information resources are recognized as a condition for the growth of an organization, they are increasing technological and policy investments in IS(information security). However, information exposure can occur from external invasions such as hacking and incidents related to misuse and abuse by insiders. This study proposes a mechanism that considers the organizational environment and individual characteristics from the viewpoint of promoting employees' IS participation activities. In other words, the study presents the complex effects of organizational environmental factors (ethical leadership, IS collaborative communication) and personal factors (person-organization fit) on organization trust and IS voice behavior. We surveyed office workers who asked for IS-related business activities and tested hypotheses using 422 samples. As a result, ethical leadership influenced organization trust through collaborative communication, and organization trust strengthened IS voice behavior by having an interaction effect with person-organization fit. This study suggests direction for establishing an organizational environment for promoting IS-related activities by office workers, so it provides practical implications for organizations with goals related to internal information exposure control.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.195-200
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• 2021

Seafarers play an important role in shipping and logistics. However, seafarers are relatively vulnerable to mental illness because they have to board ships for a considerable period of time and work in isolation. In particular, in the pandemic situation caused by COVID-19, the crew change is delayed due to the closure of many ports around the world, increasing the mental burden on seafarers. The mental health management of the crew is important because these mental problems can lead to major accidents of lives and ships. This paper identified the necessity of mental health management of seafarers through a survey and identified problems with the currently operated mental health management program and curriculum. Especially, this study proposed VR-based programs to help crews receive mentally counseling treatment in a timely manner and to reduce the mental burden on them by preventing sensitive personal information exposure. Through this, it is expected to contribute to the stable development of the logistics industry by establishing a safe seafarers working environment.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.21-30
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• 2021

With the development of IoT technology, various cloud computing-based services such as smart cars, smart healthcare, smart homes, and smart farms are expanding. With the advent of a new environment, various problems continue to occur, such as the possibility of exposure of important information such as personal information or company secrets, financial damage cases due to hacking, and human casualties due to malicious attack techniques. In this paper, we propose a message communication protocol for smart home-based secure communication and user data protection. As a detailed process, secure device registration, message authentication protocol, and renewal protocol were newly designed in the smart home environment. By referring to the security requirements related to the smart home service, the stability of the representative attack technique was verified, and as a result of performing a comparative analysis of the performance, the efficiency of about 50% in the communication aspect and 25% in the signature verification aspect was confirmed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.201-210
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• 2023

Deep learning-based face verificattion model show high performance and are used in many fields, but there is a possibility the user's face image may be leaked in the process of inputting the face image to the model. Althoughde-identification technology exists as a method for minimizing the exposure of face features, there is a problemin that verification performance decreases when the existing technology is applied. In this paper, after combining the face features of other person, a de-identified face image is created through StyleGAN. In addition, we propose a method of optimizingthe combining ratio of features according to the face verification model using HopSkipJumpAttack. We visualize the images generated by the proposed method to check the de-identification performance, and evaluate the ability to maintain the performance of the face verification model through experiments. That is, face verification can be performed using the de-identified image generated through the proposed method, and leakage of face personal information can be prevented.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.76-90
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• 2024

Although artificial intelligence (AI) can be utilized in various domains such as smart city, healthcare, it is limited due to concerns about the exposure of personal and sensitive information. In response, the concept of distributed machine learning has emerged, wherein learning occurs locally before training a global model, mitigating the concentration of data on a central server. However, overall learning phase in a collaborative way among multiple participants poses threats to data privacy. In this paper, we systematically analyzes recent trends in privacy protection within the realm of distributed machine learning, considering factors such as the presence of a central server, distribution environment of the training datasets, and performance variations among participants. In particular, we focus on key distributed machine learning techniques, including horizontal federated learning, vertical federated learning, and swarm learning. We examine privacy protection mechanisms within these techniques and explores potential directions for future research.