• Title/Summary/Keyword: Sensitive data

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A Privacy-Preserving Health Data Aggregation Scheme

  • Liu, Yining;Liu, Gao;Cheng, Chi;Xia, Zhe;Shen, Jian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.8
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    • pp.3852-3864
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    • 2016
  • Patients' health data is very sensitive and the access to individual's health data should be strictly restricted. However, many data consumers may need to use the aggregated health data. For example, the insurance companies needs to use this data to setup the premium level for health insurances. Therefore, privacy-preserving data aggregation solutions for health data have both theoretical importance and application potentials. In this paper, we propose a privacy-preserving health data aggregation scheme using differential privacy. In our scheme, patients' health data are aggregated by the local healthcare center before it is used by data comsumers, and this prevents individual's data from being leaked. Moreover, compared with the existing schemes in the literature, our work enjoys two additional benefits: 1) it not only resists many well known attacks in the open wireless networks, but also achieves the resilience against the human-factor-aware differential aggregation attack; 2) no trusted third party is employed in our proposed scheme, hence it achieves the robustness property and it does not suffer the single point failure problem.

Errors of MODIS product of Gross Primary Production by using Data Assimilation Office Meteorological Data (MODIS 총일차생산성 산출물의 오차요인 분석: 입력기상자료의 영향)

  • Kang Sinkyu;Kim Youngil;Kim Youngjin
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.7 no.2
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    • pp.171-183
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    • 2005
  • In order to monitor the global terrestrial carbon cycle, NASA (National Aeronautics and Space Administration) provides 8-day GPP images by use of satellite remote-sensing reflectance data from MODIS (Moderate Resolution Imaging Spectroradiometer) at l-km nadir spatial resolution since December, 1999. MODIS GPP algorithm adopts DAO (Data Assimilation Office) meteorological data to calculate daily GPP. By evaluating reliability of DAO data with respect to surface weather station data, we examined the effect of errors from DAO data on MODIS GPP estimation in the Korean Peninsula from 2001 to 2003. Our analyses showed that DAO data underestimated daily average temperature, daily minimum temperature, and daily vapor pressure deficity (VPD), but overestimated daily shortwave radiation during the study period. Each meteorological variable resulted in different spatial patterns of error distribution across the Korean Peninsula. In MODIS GPP estimation, DAO data resulted in overestimation of GPP by $25\%$ for all biome types but up to $40\%$ for forest biomes, the major biome type in the Korean Peninsula. MODIS GPP was more sensitive to errors in solar radiation and VPD than in temperatures. Our results indicate that more reliable gridded meteorological data than DAO data are necessary for satisfactory estimation of MODIS GPP in the Korean Peninsula.

Disc Tilt Error Measurement using Reconstructed Image Pattern for Holographic Data Storage (홀로그래픽 정보저장기기의 재생 이미지 패턴을 이용한 디스크 틸트 오차 측정)

  • Lim, Sung-Yong;Han, Cho-Lok;Kim, Do-Hyung;Yang, Hyun-Seok;Park, No-Cheol;Park, Young-Pil
    • Transactions of the Society of Information Storage Systems
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    • v.8 no.2
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    • pp.67-71
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    • 2012
  • Page-oriented holographic data storage (HDS) is very sensitive to the tilt error. Therefore, tilt error should be measured and compensated. Especially, mechanical tilt measurement method cannot cope with tilt error measurement because photopolymer medium has shrinkage problem. Therefore, the method to solve this problem is using the reconstructed image which can represent both tilt and shrinkage effect. In this paper, we suggest disc tilt measurement algorithm using image pattern of retrieval data.

The Design and Implementation of Secure-ReXpis System with Internet Environment (인터넷 환경 하에서의 Secure-ReXpis 시스템 설계 및 구현)

  • 안경림;박상필;백혜경;임병찬;박준홍;고대식
    • The Journal of Society for e-Business Studies
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    • v.6 no.3
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    • pp.101-113
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    • 2001
  • Security is very important in EC(Electronic Commerce) environment because exchanged information(that is transaction details, private data, charges data(card-no, accounts), etc) is various and is very sensitive. So, In this paper, we propose Secure-ReXpis(Reliable St excellent Xh3 Processing Infrastructure) System that transfer message and support Message Level Security(Encryption/Decryption and Digital Signature). And we implement Message Confidentiality Service, User Authentication & Message Integrity Service and Non-Repudiation Service among the various Security Services. This system support XML message format and EDI message, WEB Data and Private Format Data, etc.

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Analysis for Accuracy of High Resolution Satellite Data Using Simulation data (시뮬레이션 자료를 이용한 고해상도 인공위성자료의 정확도 분석)

  • Seo Doo-Chun;Lee Dong-Han;Park Su-Young;Song Jeong-Heon;Lim Hyo-Suk
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2006.04a
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    • pp.255-258
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    • 2006
  • With the increasing availability of high-resolution satellite imagery, the demand for ortho-rectified products will also be growing. High-resolution of the imagery (up to 1m) the desired accuracy of the ortho-rectification is more sensitive to a number of factors. including satellite position, velocity, internal sensor error (specifically, misalignment. lens distortion, etc.). sensor modeling, relief displacement and matching error, etc. The main objective of this study is to analysis the accuracy of high resolution satellite data using simulation data.

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Evaluation of DoP-CPD Classification Technique and Multi Looking Effects for RADARSAT-2 Images

  • Lee, Kyung-Yup;Oh, Yi-Sok;Kim, Youn-Soo
    • Korean Journal of Remote Sensing
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    • v.28 no.3
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    • pp.329-336
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    • 2012
  • This paper give further assessment on the original DoP-CPD classification scheme. This paper provides some additional comparative study on the DoP-CPD with H/A/alpha classifier in terms of multi look effects and classification performances. The statistics and multi looking effects of the DoP and CPD were analyzed with measured polarimetric SAR data. DoP-CPD is less sensitive to the number of averaging pixels than the entropy-alpha technique. A DoP-CPD diagram with appropriate boundaries between six different classes was then developed based on the data analysis. A polarimetric SAR image DoP-CPD classification technique is verified with C-band polarimetric RADARSAT-2 images.

Wavelet-based damage detection method for a beam-type structure carrying moving mass

  • Gokdag, Hakan
    • Structural Engineering and Mechanics
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    • v.38 no.1
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    • pp.81-97
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    • 2011
  • In this research, the wavelet transform is used to analyze time response of a cracked beam carrying moving mass for damage detection. In this respect, a new damage detection method based on the combined use of continuous and discrete wavelet transforms is proposed. It is shown that this method is more capable in making damage signature evident than the traditional two approaches based on direct investigation of the wavelet coefficients of structural response. By the proposed method, it is concluded that strain data outperforms displacement data at the same point in revealing damage signature. In addition, influence of moving mass-induced terms such as gravitational, Coriolis, centrifuge forces, and pure inertia force along the deflection direction to damage detection is investigated on a sample case. From this analysis it is concluded that centrifuge force has the most influence on making both displacement and strain data damage-sensitive. The Coriolis effect is the second to improve the damage-sensitivity of data. However, its impact is considerably less than the former. The rest, on the other hand, are observed to be insufficient alone.

Combining Ridge Regression and Latent Variable Regression

  • Kim, Jong-Duk
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.1
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    • pp.51-61
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    • 2007
  • Ridge regression (RR), principal component regression (PCR) and partial least squares regression (PLS) are among popular regression methods for collinear data. While RR adds a small quantity called ridge constant to the diagonal of X'X to stabilize the matrix inversion and regression coefficients, PCR and PLS use latent variables derived from original variables to circumvent the collinearity problem. One problem of PCR and PLS is that they are very sensitive to overfitting. A new regression method is presented by combining RR and PCR and PLS, respectively, in a unified manner. It is intended to provide better predictive ability and improved stability for regression models. A real-world data from NIR spectroscopy is used to investigate the performance of the newly developed regression method.

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Object Detection Algorithm in a Level Crossing Area Using Image Processing (화상처리를 이용한 철도 건널목의 물체 감지 알고리즘)

  • Yoo, Kwang-Kiun;Han, Seung-Jin;Lee, Key-Seo
    • Proceedings of the KIEE Conference
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    • 1995.11a
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    • pp.225-227
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    • 1995
  • An object detection algorithm using a modified IDM(Image Differential Method) is proposed for detecting an object in a level crossing area. The conventional object detection method using LASER light has the deadzone that it cannot detect small objects, while the object detection method using image data in a level crossing area can detect such small objects. But the image data in a level crossing area can be changeable easily because the data is outdoor and sensitive to such surrounding environments as the change of the sun beam, the shadow of cars, and so on. So we resolve these problems by adding the normalization and the process for shadow of the image data in a level crossing area to the basic IDM(Image Differential Method).

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Study on a Measurement of Disclosure Risk of Microdata by Similarity

  • Cho, Hyeon-Kwan;Kwon, Dae-Hong;Lee, Suk-Hoon
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.743-755
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    • 2012
  • Researchers using various of statistical data want to obtain microdata for a detailed analysis. Institutes need to provide microdata after masking processes for sensitive data. Many researchers have used the proportion of unique identity for the measurement of disclosure risk. We proposed a new measurement of disclosure risk that considers the case that all identities are the same or similar. As an application example, we compare the newly proposed measurement and the existing measurement using 10667 data in 'Korea Household Income and Expenditure Survey data for 2010'.