• Title/Summary/Keyword: The Private Security

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Improving the Effectiveness of Crime Prevention of Child Safety Keeper System -Focusing on the Influence of Job Satisfaction- (아동안전지킴이 제도의 실효성 향상 방안 -직무만족에 미치는 영향을 중심으로-)

  • Kim, Jung-Gyu;Kim, Moon-Ho
    • The Journal of the Korea Contents Association
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    • v.15 no.9
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    • pp.118-125
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    • 2015
  • According to the children's crime risk is increased, national police agency has implemented child safety keeper system since 2009. Despite the importance of child safety keeper studies, there was no seeking of empirical research and development plan for the operation. The purpose of the study is to find ways to improve the effectiveness of the child safety keeper system. To achieve the research objectives, all the child safety keepers were surveyed by quota sampling in the 16 provincial police agency. Questionnaire analyzed by frequency analysis, t-test, Avova, multiple regression analysis. The result of analysis is the need to strengthen links with child safety keeping house, participatory setting for the patrol route, the improvement of education management and supervision, adequacy of allowance, strengthening contact with children for job success awareness.

Routing for Enhancing Source-Location Privacy in Wireless Sensor Networks of Multiple Assets

  • Tscha, Yeong-Hwan
    • Journal of Communications and Networks
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    • v.11 no.6
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    • pp.589-598
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    • 2009
  • In wireless sensor networks, a node that reports information gathered from adjacent assets should relay packets appropriately so that its location context is kept private, and thereby helping ensure the security of the assets that are being monitored. Unfortunately, existing routing methods that counter the local eavesdropping-based tracing deal with a single asset, and most of them suffer from the packet-delivery latency as they prefer to take a separate path of many hops for each packet being sent. In this paper, we propose a routing method, greedy perimeter stateless routing-based source-location privacy with crew size w (GSLP-w), that enhances location privacy of the packet-originating node (i.e., active source) in the presence of multiple assets. GSLP-w is a hybrid method, in which the next-hop node is chosen in one of four modes, namely greedy, random, perimeter, and retreat modes. Random forwarding brings the path diversity, while greedy forwarding refrains from taking an excessively long path and leads to convergence to the destination. Perimeter routing makes detours that avoid the nodes near assets so that they cannot be located by an adversary tracing up the route path. We study the performance of GSLP-w with respect to crew size w (the number of packets being sent per path) and the number of sources. GSLP-w is compared with phantom routing-single path (PR-SP), which is a notable routing method for source-location privacy and our simulation results show that improvements from the point of the ratio of safety period and delivery latency become significant as the number of source nodes increases.

A Secure Personal Health Record System for Handling of Emergency Situations (응급 상황 처리를 위한 안전한 개인건강기록 시스템)

  • Yi, Myung-Kyu;Hwang, Hee-Joung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.5
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    • pp.117-123
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    • 2016
  • In recent years, Personal Health Record (PHR) has emerged as a patient-centric model of health information exchange. The Personal Health Record (PHR) owners enjoy the full right of accessing their records anywhere and anytime making storage and retrieval more efficient. Due to the sensitivity and confidential nature of the PHR, however, the PHR is maintained in a secure and private environment with the individual determining rights of access. In this paper, we propose a system which enables access to the user's PHR in the event of emergency. In emergency situation where the user is unconscious, the emergency staff can use the PHR information to request a emergency access to the PHR server based on the predefined rights of access for PHR. Under the proposed system, the PHR owner can specify a fine grain access control policy during emergency situations.

Implementation Method of Insurance Object GIS DB for the Storm and Flood Hazard Risks Premium Rate Mapping (풍수해보험 관리지도를 위한 보험 목적물 GIS DB 구축)

  • Lee, Jun-Seok;Lee, In-Su
    • Journal of Cadastre & Land InformatiX
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    • v.45 no.2
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    • pp.87-100
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    • 2015
  • Currently, Korea government has strongly recommended the storm and flood insurance system to reduce the damage caused by natural disasters. The storm and flood insurance operated by private insurance company is the type of policy insurance. and is supervised by Minister of Public Safety and Security. It is the advanced disaster management system which is able to protect the public interests through unexpected natural disaster by assisting some part of the insurance premium from a central or local government. The main purpose of the present investigation is to build the insurance object GIS DB which should be necessary to calculate the premium rate in the map for storm and flood insurance, and also, to perform GIS analysis. The service model in this study is aimed to general single house, apartment and green house. The service management plan targeting the whole country has been investigated in terms of building DB and service operation.

Analysis of Regional Fertility Gap Factors Using Explainable Artificial Intelligence (설명 가능한 인공지능을 이용한 지역별 출산율 차이 요인 분석)

  • Dongwoo Lee;Mi Kyung Kim;Jungyoon Yoon;Dongwon Ryu;Jae Wook Song
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.47 no.1
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    • pp.41-50
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    • 2024
  • Korea is facing a significant problem with historically low fertility rates, which is becoming a major social issue affecting the economy, labor force, and national security. This study analyzes the factors contributing to the regional gap in fertility rates and derives policy implications. The government and local authorities are implementing a range of policies to address the issue of low fertility. To establish an effective strategy, it is essential to identify the primary factors that contribute to regional disparities. This study identifies these factors and explores policy implications through machine learning and explainable artificial intelligence. The study also examines the influence of media and public opinion on childbirth in Korea by incorporating news and online community sentiment, as well as sentiment fear indices, as independent variables. To establish the relationship between regional fertility rates and factors, the study employs four machine learning models: multiple linear regression, XGBoost, Random Forest, and Support Vector Regression. Support Vector Regression, XGBoost, and Random Forest significantly outperform linear regression, highlighting the importance of machine learning models in explaining non-linear relationships with numerous variables. A factor analysis using SHAP is then conducted. The unemployment rate, Regional Gross Domestic Product per Capita, Women's Participation in Economic Activities, Number of Crimes Committed, Average Age of First Marriage, and Private Education Expenses significantly impact regional fertility rates. However, the degree of impact of the factors affecting fertility may vary by region, suggesting the need for policies tailored to the characteristics of each region, not just an overall ranking of factors.

Anomaly Intrusion Detection based on Association Rule Mining in a Database System (데이터베이스 시스템에서 연관 규칙 탐사 기법을 이용한 비정상 행위 탐지)

  • Park, Jeong-Ho;Oh, Sang-Hyun;Lee, Won-Suk
    • The KIPS Transactions:PartC
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    • v.9C no.6
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    • pp.831-840
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    • 2002
  • Due to the advance of computer and communication technology, intrusions or crimes using a computer have been increased rapidly while tremendous information has been provided to users conveniently Specially, for the security of a database which stores important information such as the private information of a customer or the secret information of a company, several basic suity methods of a database management system itself or conventional misuse detection methods have been used. However, a problem caused by abusing the authority of an internal user such as the drain of secret information is more serious than the breakdown of a system by an external intruder. Therefore, in order to maintain the sorority of a database effectively, an anomaly defection technique is necessary. This paper proposes a method that generates the normal behavior profile of a user from the database log of the user based on an association mining method. For this purpose, the Information of a database log is structured by a semantically organized pattern tree. Consequently, an online transaction of a user is compared with the profile of the user, so that any anomaly can be effectively detected.

Changes in a facial recognition algorithm following different types of orthognathic surgery: a comparative study

  • Kim, Won-Yong;Han, Se Jin
    • 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.

A Method of Authenticating WLAN APs for Smartphones (스마트폰을 위한 무선 AP 인증 방법)

  • Shin, DongOh;Kang, Jeonil;Nyang, DaeHun;Lee, Sokjoon;Lee, KyungHee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39B no.1
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    • pp.17-28
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    • 2014
  • The increase of smartphone users have made mobile carriers offload increasingly congested traffic of 3/4G by providing Wi-Fi hot-spots in the public places such as coffee shops and subway stations. In the traditional authentication in WLAN, the users should convince the service providers that they are valid customers before they use WLAN services. Since the authentication protocol is designed for service providers. Even with the mutual authentication based on the IEEE 802.1X, which is supported by IEEE 802.11 standard, it is difficult to be convinced of that the service providers really have installed the WLAN APs, which users are confronted with. An attacker can install rogue APs that masquerade as legitimate APs by copying the SSID, MAC address, etc. in order to obtain users' private information. In this paper, we introduce a method of authenticating legitimate APs for smartphone users. And we show our proposal can be well utilized for the current Wi-Fi hot-spots as a security plug-in and prove it through our experiments.

Noisy Weighted Data Aggregation for Smart Meter Privacy System (스마트 미터 프라이버시 시스템을 위한 잡음 가중치 데이터 집계)

  • Kim, Yong-Gil;Moon, Kyung-Il
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.3
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    • pp.49-59
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    • 2018
  • Smart grid system has been deployed fast despite of legal, business and technology problems in many countries. One important problem in deploying the smart grid system is to protect private smart meter readings from the unbelievable parties while the major smart meter functions are untouched. Privacy-preserving involves some challenges such as hardware limitations, secure cryptographic schemes and secure signal processing. In this paper, we focused particularly on the smart meter reading aggregation,which is the major research field in the smart meter privacy-preserving. We suggest a noisy weighted aggregation scheme to guarantee differential privacy. The noisy weighted values are generated in such a way that their product is one and are used for making the veiled measurements. In case that a Diffie-Hellman generator is applied to obtain the noisy weighted values, the noisy values are transformed in such a way that their sum is zero. The advantage of Diffie and Hellman group is usually to use 512 bits. Thus, compared to Paillier cryptosystem series which relies on very large key sizes, a significant performance can be obtained.

Robustness of Face Recognition to Variations of Illumination on Mobile Devices Based on SVM

  • Nam, Gi-Pyo;Kang, Byung-Jun;Park, Kang-Ryoung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.1
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    • pp.25-44
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    • 2010
  • With the increasing popularity of mobile devices, it has become necessary to protect private information and content in these devices. Face recognition has been favored over conventional passwords or security keys, because it can be easily implemented using a built-in camera, while providing user convenience. However, because mobile devices can be used both indoors and outdoors, there can be many illumination changes, which can reduce the accuracy of face recognition. Therefore, we propose a new face recognition method on a mobile device robust to illumination variations. This research makes the following four original contributions. First, we compared the performance of face recognition with illumination variations on mobile devices for several illumination normalization procedures suitable for mobile devices with low processing power. These include the Retinex filter, histogram equalization and histogram stretching. Second, we compared the performance for global and local methods of face recognition such as PCA (Principal Component Analysis), LNMF (Local Non-negative Matrix Factorization) and LBP (Local Binary Pattern) using an integer-based kernel suitable for mobile devices having low processing power. Third, the characteristics of each method according to the illumination va iations are analyzed. Fourth, we use two matching scores for several methods of illumination normalization, Retinex and histogram stretching, which show the best and $2^{nd}$ best performances, respectively. These are used as the inputs of an SVM (Support Vector Machine) classifier, which can increase the accuracy of face recognition. Experimental results with two databases (data collected by a mobile device and the AR database) showed that the accuracy of face recognition achieved by the proposed method was superior to that of other methods.