• Title/Summary/Keyword: Invasion of Privacy

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A Countermeasures on the Cyber Terror for the National Key Organizations (정부 주요기관에 대한 사이버 공격의 대처 방법)

  • Lee, Young-Gyo;Park, Joong-Soon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.4 no.2
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    • pp.39-47
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    • 2008
  • As internet is spreaded widely, the number of cyber terror using hacking and virus is increased. Also the international cyber terror to the national key organizations go on increasing. If the national key organizations is attacked by the attack, the national paper, document and records are exposed to the other nations. The national paper, document and records can give damage to the nation. Especially, the unknown attack can give much damage to the nation. Therefore, this paper suggested a countermeasures on the cyber terror for the national key organizations provided the inner of the organization is safe. The uneffective item and invasion privacy item are included among the countermeasures. However the countermeasures can protect only one cyber terror to the national key organizations.

A Study on the Improvement of Youth Housing Support Policy

  • KIM, Sun-Ju
    • The Journal of Industrial Distribution & Business
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    • v.11 no.11
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    • pp.29-38
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    • 2020
  • Purpose: The problem of housing poverty among young people is a very important problem for the nation. Therefore, the main purpose of this paper is to identify the problems of the government's housing support policy for young people. And it is in presenting specific solutions by fully reflecting the opinions of experts. Research design, data and methodology: This study consisted of analyzing the following three research topics: 1) the differences of youth residential support housing policy impact on young adults' housing stability, 2) the problems and solutions of youth housing support policy, and 3) the differences of experts' opinions on the impact of government policy on youth housing stability. The subject of this study is the government's seven housing policies for young people. The targets include Happy Public Rental Housing (Happiness Housing), Station Area Rental Housing for youth (Station Area 2030), Public Dormitory for College Students (Public Dormitory & Hope Dormitory), Jeonse Rental Housing for College Students (Subject Lease Rental Housing for College Students), Social Housing for Young People, and Share House. The data was organized through expert surveys from 1st to 30th June 2020. The experts surveyed include professors & researchers, public officer & public institutions staff, and private developers of young adults' housing. The methodology of analysis on the problem and the solution of government policy was Frequency analysis. And analysis methods on differences of experts' opinion were ANOVA, Levene' test, and Schefe test. Results: Problems in Government's youth residential support housing policy include high rents, lack of supply, difficulty in acquiring rental housing, inconvenience in using shared spaces, conflicts with cohabitants, and invasion of privacy. Solutions include expanding supply to urban areas, establishing long-term plans, securing privacy, diversifying business methods, establishing platforms for rental housing transactions, and expanding various public support (financial support, etc). Conclusions: There was a difference in perception among groups of experts on the impact of public rental housing (called 'happiness housing') in youth housing stability. It is very urgent to come up with the most reasonable policy to support youth housing. This requires in-depth discussions by experts to narrow their differences.

A Study on Expanding Participation in and Raising Awareness of the Green Parking Project for Improvement of Parking Conditions in Urban Residential Areas (도시주거지 주차환경개선을 위한 녹색주차사업 참여확대 및 인식제고 방안)

  • Kim, Myo-Jung
    • Journal of the Korean housing association
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    • v.26 no.1
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    • pp.61-70
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    • 2015
  • The purpose of this study was to provide information on how to expend participation in and raise awareness of the Green Parking Project. A survey was conducted for this study among two groups. One group consisted of 38 residents of the Green Parking Zone in Nam-gu, Ulsan, and the other group consised 129 residents with no experience with the Green Parking Project. For analysis, the frequency and means were calculated, and t-test, analysis of variance, and chi-square test were performed. The results showed, first, that general residents tended to think that parking on the street in front of one's house is a divine right, while residents living the Green Parking Zone thought that the street is a public space. Second, general residents regarded fences as means of security to protect their private property, while people living in the Green Parking Zone tended to think of their yards as semi-private spaces and allowed access to neighbors. Third, general residents had concerns about maintenance and administration fees, noise and dust, security of houses, and privacy. However, residents of the Green Parking Zone evaluated those conditions positively. Fourth, people who were well-informed about the Green Parking Project had low anxiety about security and invasion of privacy, results from the project. Therefore, effective public relations are very important for expanding participation and raising awareness.

A Deep Learning Based Device-free Indoor People Counting Using CSI (CSI를 활용한 딥러닝 기반의 실내 사람 수 추정 기법)

  • An, Hyun-seong;Kim, Seungku
    • 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.

Secure and Efficient Client-side Deduplication for Cloud Storage (안전하고 효율적인 클라이언트 사이드 중복 제거 기술)

  • Park, Kyungsu;Eom, Ji Eun;Park, Jeongsu;Lee, Dong Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.1
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    • pp.83-94
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    • 2015
  • Deduplication, which is a technique of eliminating redundant data by storing only a single copy of each data, provides clients and a cloud server with efficiency for managing stored data. Since the data is saved in untrusted public cloud server, however, both invasion of data privacy and data loss can be occurred. Over recent years, although many studies have been proposed secure deduplication schemes, there still remains both the security problems causing serious damages and inefficiency. In this paper, we propose secure and efficient client-side deduplication with Key-server based on Bellare et. al's scheme and challenge-response method. Furthermore, we point out potential risks of client-side deduplication and show that our scheme is secure against various attacks and provides high efficiency for uploading big size of data.

The Determinants for Discontinued Use of SNS: Perspectives of Rational Choice Theory and Social Comparison Theory (SNS중단의도의 결정요인: 합리적 선택이론 및 사회적 비교이론을 중심으로)

  • Yoo, Hyung-Wook;Son, Dal-Ho
    • The Journal of Information Systems
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    • v.26 no.4
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    • pp.39-62
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    • 2017
  • Purpose The purpose of this study is to investigate the factors which affect users' fatigue and reluctant intention of using a SNS. In particular, this study focused on the fatigue of SNS users, as the recent excessive use of SNS has led to negative effects such as invasion of privacy, addition and social overload. fatigue This research will explain how producing adverse effects by using SNS caused psychological and mental depression. Previous researches explained that mental fatigue associated with SNS is not simple one and it is complicated with various psychological factors. Considering this fact, this study introduced a behavioral economics concept and a social comparison theory in the research model. Design/methodology/approach For research purposes, this study developed research hypotheses in order to empirically examine the factors that affect SNS users' fatigue and reluctant intention. The empirical research was based on a poll done through 800 research candidates in the SNS fields and the final 451 responses were collected and used in statistical data analysis. The adaptability, trust, and validity to measurement model were verified and the structural relationship in the research model was analyzed through these 451 responses. Findings First of all, maintenance fatigue of SNS had a positive significant effect on coupling and fatigue of SNS and information privacy had a non-significant effect on fatigue. Second, coupling had a negative significant effect on rational inattention, however, perceived cost had a non-significant effect on rational inattention. Third, lateral/upward comparison had a positive significant on user's negative emotions. Meanwhile, user's negative emotions did not have a significant effect on rational inattention.

Applied Method to Trusted Digital Content Distribution Architecture (신뢰할 수 있는 디지털 콘텐츠 유통 아키텍처 방안)

  • Kim, Hye-Ri;Hong, Seng-Phil;Lee, Chul-Soo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.6A
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    • pp.151-162
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    • 2008
  • As the innovative internet technologies and multimedia are being rapidly developed, digital content is a remarkable new growth industry and supplied by various channel. For example, domestic sales volume in digital contents marked an annual increase of 14.7% since 2003. Against the merits of digital content distribution, Information reengineering aspects are getting more serious issues in these days such as infringement of copyright, flood of inappropriate content, invasion and infringement of privacy, etc. In this paper, we are making a suggestion of the TDCDA-Trusted Digital Content Distribution Architecture in order to solve above problems. TDCDA is provided to how well-define and design the trusted path in digital contents distribution in internet environments using a secure distribution mechanism, digital content integrity and copyright protection. Finally, we also proposed the TDCDA algorithm and applicable guidelines for feasible approach in real computing environment.

An Implementation of Federated Learning based on Blockchain (블록체인 기반의 연합학습 구현)

  • Park, June Beom;Park, Jong Sou
    • The Journal of Bigdata
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    • v.5 no.1
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    • pp.89-96
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    • 2020
  • Deep learning using an artificial neural network has been recently researched and developed in various fields such as image recognition, big data and data analysis. However, federated learning has emerged to solve issues of data privacy invasion and problems that increase the cost and time required to learn. Federated learning presented learning techniques that would bring the benefits of distributed processing system while solving the problems of existing deep learning, but there were still problems with server-client system and motivations for providing learning data. So, we replaced the role of the server with a blockchain system in federated learning, and conducted research to solve the privacy and security problems that are associated with federated learning. In addition, we have implemented a blockchain-based system that motivates users by paying compensation for data provided by users, and requires less maintenance costs while maintaining the same accuracy as existing learning. In this paper, we present the experimental results to show the validity of the blockchain-based system, and compare the results of the existing federated learning with the blockchain-based federated learning. In addition, as a future study, we ended the thesis by presenting solutions to security problems and applicable business fields.

Federated Deep Reinforcement Learning Based on Privacy Preserving for Industrial Internet of Things (산업용 사물 인터넷을 위한 프라이버시 보존 연합학습 기반 심층 강화학습 모델)

  • Chae-Rim Han;Sun-Jin Lee;Il-Gu Lee
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.6
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    • pp.1055-1065
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    • 2023
  • Recently, various studies using deep reinforcement learning (deep RL) technology have been conducted to solve complex problems using big data collected at industrial internet of things. Deep RL uses reinforcement learning"s trial-and-error algorithms and cumulative compensation functions to generate and learn its own data and quickly explore neural network structures and parameter decisions. However, studies so far have shown that the larger the size of the learning data is, the higher are the memory usage and search time, and the lower is the accuracy. In this study, model-agnostic learning for efficient federated deep RL was utilized to solve privacy invasion by increasing robustness as 55.9% and achieve 97.8% accuracy, an improvement of 5.5% compared with the comparative optimization-based meta learning models, and to reduce the delay time by 28.9% on average.

Anonymous Qualification Verifying Method on Web Environment (웹 환경에서 익명성을 제공하는 자격증명 방법)

  • Lee, Yun-Kyung;Hwang, Jung-Yeon;Chung, Byung-Ho;Kim, Jeong-Nyeo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.5
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    • pp.181-195
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    • 2011
  • There's a controversy about an invasion of privacy which includes a leakage of private information and linking of user's behavior on internet. Although many solutions for this problem are proposed, we think anonymous authentication, authorization, and payment mechanism is the best solution for this problem. In this paper, we propose an effective anonymity-based method that achieves not only authentication but also authorization. Our proposed method uses anonymous qualification certificate and group signature method as an underlying primitive, and combines anonymous authentication and qualification information. An eligible user is legitimately issued a group member key pair through key issuing process and issued some qualification certificates anonymously, and then, he can take the safe and convenience web service which supplies anonymous authentication and authorization. The qualification certificate can be expanded according to application environment and it can be used as payment token.