• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.935-941
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• 2020

People estimation is important to provide IoT services. Most people counting technologies use camera or sensor data. However, the conventional technologies have the disadvantages of invasion of privacy and the need to install extra infrastructure. This paper proposes a method for estimating the number of people using a Wi-Fi AP. We use channel state information of Wi-Fi and analyze that using deep learning technology. It can be achieved by pre-installed Wi-Fi infrastructure that reduce cost for people estimation and privacy infringement. The proposed algorithm uses a k-binding data for pre-processing process and a 1D-CNN learning model. Two APs were installed to analyze the estimation results of six people. The result of the accurate number estimation was 64.8%, but the result of classifying the number of people into classes showed a high result of 84.5%. This algorithm is expected to be applicable to estimate the density of people in a small space.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.187-190
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• 2022

본 논문은 메타버스 등 인공지능 연계 증강/가상현실 부동 중계 플랫폼에서 부동산 영상 기반 매물 소개 시스템 구축에서 사생활 및 개인정보가 영상에 담기게 될 수 있는 위험이 존재하기에 부동산 영상 내의 개인정보 및 민감 정보를 인공지능 기술을 기반으로 검출하여 삭제해주고 복원해주는 인공지능 기술 연구개발을 목표로 하였다. 한국형 부동산 내 민감 object 를 정의하고, 최신 인공지능 딥러닝 기술 기반 민감 object detection 알고리즘을 연구 개발하며, 영상에서 삭제된 부분은 인공지능 기술을 기반으로 물체가 없는 실제 공간영상으로 복원해주는 영상복원 기술도 연구 개발하였다. 한국형 부동산 환경 (영상 촬영 조도, 디스플레이 스타일, 주변 가구 배치 등)에 맞는 인공지능 모델 구축을 위하여, 자체적으로 한국 영상 database 구축 및 Transfer learning for target domain adaptation 을 진행하였다. 제안된 알고리즘은 일반적인 환경에서 98%의 정확도와 challenge 환경에서 (occlusion 빛 반사, 저조도 등) 81%의 정확도를 보였다. 본 기술은 Proptech 분야에서 주목받고 있는 메타버스 기반 온라인 중계 서비스 기술을 활성화하기 위하여 기획되었으며, 특히 메타버스 부동산 중계 플랫폼의 활성화를 위하여 사생활 보호 측면에서 필요한 중요 기술을 인공지능 기술을 활용하여 연구 개발하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.627-628
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• 2022

There is no internationally accepted codified definition of digital trade because of the wide variety and scope of related industries and transactions(product + service + data) in general. Recently, innovative changes are taking place in digital trade due to the development of technologies such as IT due to the 4th industrial revolution, and advanced countries such as the US, EU, and Japan are including digital trade issues such as data movement liberalization in the negotiation agenda of the digital trade agreement. The issue with the liberalization of cross-border data movement is that freedom of data movement is necessary to vitalize digital trade, but it also increases the risk of information security and privacy violations. Looking at the directions of advanced countries, the US favors minimization of regulations, Europe favors regional single marketization, but passively opens up to the outside world, and China promotes independent markets through regulations. Therefore, measures to strengthen restrictions on cross-border data movement are an issue that has recently been implemented by each country or an international aggrement is scheduled to be reached soon, and Korea also needs a close response.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.647-654
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• 2023

Deep Learning is a useful method for classifying and recognizing complex data such as images and text, and the accuracy of the deep learning method is the basis for making artificial intelligence-based services on the Internet useful. However, the vast amount of user da vita used for training in deep learning has led to privacy violation problems, and it is worried that companies that have collected personal and sensitive data of users, such as photographs and voices, own the data indefinitely. Users cannot delete their data and cannot limit the purpose of use. For example, data owners such as medical institutions that want to apply deep learning technology to patients' medical records cannot share patient data because of privacy and confidentiality issues, making it difficult to benefit from deep learning technology. In this paper, we have designed a privacy preservation technique-applied deep learning technique that allows multiple workers to use a neural network model jointly, without sharing input datasets, in multi-party system. We proposed a method that can selectively share small subsets using an optimization algorithm based on modified stochastic gradient descent, confirming that it could facilitate training with increased learning accuracy while protecting private information.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.33-56
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• 2017

As Internet usage is becoming more common worldwide and smartphone become necessity in daily life, technologies and applications related to mobile Internet are developing rapidly. The results of the Internet usage patterns of consumers around the world imply that there are many potential new business opportunities for mobile Internet technologies and applications. The location-based service (LBS) is a service based on the location information of the mobile device. LBS has recently gotten much attention among many mobile applications and various LBSs are rapidly developing in numerous categories. However, even with the development of LBS related technologies and services, there is still a lack of empirical research on the intention to use LBS. The application of previous researches is limited because they focused on the effect of one particular factor and had not shown the direct relationship on the intention to use LBS. Therefore, this study presents a research model of factors that affect the intention to use and actual use of LBS whose market is expected to grow rapidly, and tested it by conducting a questionnaire survey of 330 users. The results of data analysis showed that service customization, service quality, and personal innovativeness have a positive effect on the intention to use LBS and the intention to use LBS has a positive effect on the actual use of LBS. These results implies that LBS providers can enhance the user's intention to use LBS by offering service customization through the provision of various LBSs based on users' needs, improving information service qualities such as accuracy, timeliness, sensitivity, and reliability, and encouraging personal innovativeness. However, privacy concerns in the context of LBS are not significantly affected by service customization and personal innovativeness and privacy concerns do not significantly affect the intention to use LBS. In fact, the information related to users' location collected by LBS is less sensitive when compared with the information that is used to perform financial transactions. Therefore, such outcomes on privacy concern are revealed. In addition, the advantages of using LBS are more important than the sensitivity of privacy protection to the users who use LBS than to the users who use information systems such as electronic commerce that involves financial transactions. Therefore, LBS are recommended to be treated differently from other information systems. This study is significant in the theoretical point of contribution that it proposed factors affecting the intention to use LBS in a multi-faceted perspective, proved the proposed research model empirically, brought new insights on LBS, and broadens understanding of the intention to use and actual use of LBS. Also, the empirical results of the customization of LBS affecting the user's intention to use the LBS suggest that the provision of customized LBS services based on the usage data analysis through utilizing technologies such as artificial intelligence can enhance the user's intention to use. In a practical point of view, the results of this study are expected to help LBS providers to develop a competitive strategy for responding to LBS users effectively and lead to the LBS market grows. We expect that there will be differences in using LBSs depending on some factors such as types of LBS, whether it is free of charge or not, privacy policies related to LBS, the levels of reliability related application and technology, the frequency of use, etc. Therefore, if we can make comparative studies with those factors, it will contribute to the development of the research areas of LBS. We hope this study can inspire many researchers and initiate many great researches in LBS fields.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.15-34
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• 2009

Today the u-government services are becoming more personalized and intelligent. For the successful implementation of personalization, individual user's privacy concerns must be respected and taken care of. Based on the empirical survey results, this research summarizes the reluctance to the government's use of private information using six categories. We measure user's psychological distance toward e-government using the four levels, adopting the suggestions by the Proxemics. Since a positive correlation is Identified between people's psychological Intimacy toward e-government and their tolerance to the use of private Information, the amount and/or types of private information should be sequentially used in personalization systems. Initially allowing the least intolerable private information such as occupation information, the personalization system should additionally use the next tolerable Information such as health information or service request/interest information, as user's psychological distance toward government services becomes shorter.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2013.04a
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• pp.154-155
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• 2013

2007년 1월 1일부터 2012년 5월 31일까지의 주택화재에 대한 소방방재청의 통계자료를 보면 공동주택에서 발생하는 화재는 매년 약 10,000여건 이상이 발생하는 것으로 나타났다. 이는 전체 화재발생의 약 30%정도를 차지하고 있으므로 조기에 인명을 대피시키기 위한 경보설비의 필요성은 더욱 높아지고 있는 상황이다. 화재감지기는 보통 거실/방 등의 천정에 위치하는데, 해당 화재감지기가 제대로 작동하는지를 점검하기 위해서는 점검기구를 이용하여 열 또는 연기를 각 감지기에 직접 가하는 방법으로 개별적인 점검을 하고 있다. 그러나 공동주택과 같이 사생활침해가 우려되는 건물의 침실 등에 설치된 화재감지기를 점검하는 경우 점검자가 해당 세대에 직접 들어가 점검을 수행해야 하기 때문에 현실적으로 100% 점검이 불가능한 상황이다. 따라서 본 논문은 이와 같은 문제점을 해결하기 위한 방안을 제시한 것으로서, 화재감지기가 정상작동 여부를 수신기에서 원격으로 점검할 수 있도록 하기위한 것이다.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.960-965
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• 2006

Privacy and security are latent problems in pervasive healthcare system. For the sake of protecting health monitoring information, it is necessary to classify and categorize the various contexts in terms of obfuscation. In this paper, we propose the physiological context categorization and specification methodology by exploiting data fusion network for automatic context alignment. In addition, we introduce the methodologies for making various level of physiological context on the context aware application model, which is wear-UCAM. This physiological context has several layers of context according to the level of abstraction such as user-friendly level or parametric level. This mechanism facilitates a user to restrict access to his/her monitoring results based on the level of details in context.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.865-868
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• 2006

최근 물류, 교통, 환경 등 우리가 살아가는 생활 중 다양하게 많이 사용되어지는 RFID 시스템은 우리에게 많은 편의를 제공하고 있다. 이러한 시스템은 무선네트워크를 이용하기 때문에 이것이 가지고 있는 보안적 취약점이 크게 문제가 되고 있다. 개인정보를 도용하여 악의적인 목적으로 사용하고 사생활까지 침해하여 사회에서 큰 불신을 갖게 되는 이러한 취약점을 안전하게 이용할 수 있도록 여러 가지 보안방식들을 사용한다. 본 연구에서는 이러한 보안방식 중 OTP(One Time Password)라는 보안방식을 RFID 시스템에 응용하여 이러한 시스템에서 지금까지 사용되고 있는 여러 보안방식들 보다도 더욱 안전하게 개인 프라이버시를 보호하고자 한다.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.388-394
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• 2007

정보기술(IT) 산업의 발달은 인터넷 활용을 급속도로 증가시켰으며, 인터넷 사용자의 수가 기하급수적으로 늘어감에 따라 인터넷을 상업적으로 활용하려는 욕구 또한 커져 가고 있다. 아울러 인터넷 관련 정보 기술의 발전속도가 매우 빠르게 발전되고 있다. 그러나 그 이면에는 개인정보의 무단유출, 사생활 노출 등의 역기능도 급격히 증가하고 있다. 이로 인해 오늘날 정보 유출로 인한 개인적 피해는 사회 문제로 대두되고 있으며, 개인의 프라이버시 침해에 대한 우려는 인터넷과 전자상거래 발달에 가장 큰 장애중의 하나로 대두되게 되었다. 온라인에서 비즈니스를 행하는 기업들은 이러한 사용자들의 프라이버시 침해에 대한 우려를 줄이고자 하는 다양한 노력들을 행하고 있다. 우선 프라이버시 보호에 관한 정책이나 규약을 홈페이지에 명시함으로써 사용자들을 안심시키려 하고 있으며, 동시에 금전적 인센티브나 편의를 제공함으로써 사용자들의 참여를 증가시키고 자신들의 비즈니스를 활성화시키고자 한다. 이에 본 연구에서는 기업의 어떠한 전략들이 사용자의 프라이버시 침해 우려를 낮추고 사용자들의 참여를 활성화시키는지를 동기부여의 기대이론에 근거하여 분석하고자 한다. 아울러 기업뿐만 아니라 사회적으로도 도움이 될 수 있는 프라이버시에 관한 전략들을 제안하고자 한다.