• Title/Summary/Keyword: 차분 데이터

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Privacy-Preserving Method to Collect Health Data from Smartband

  • Moon, Su-Mee;Kim, Jong-Wook
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.4
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    • pp.113-121
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    • 2020
  • With the rapid development of information and communication technology (ICT), various sensors are being embedded in wearable devices. Consequently, these devices can continuously collect data including health data from individuals. The collected health data can be used not only for healthcare services but also for analyzing an individual's lifestyle by combining with other external data. This helps in making an individual's life more convenient and healthier. However, collecting health data may lead to privacy issues since the data is personal, and can reveal sensitive insights about the individual. Thus, in this paper, we present a method to collect an individual's health data from a smart band in a privacy-preserving manner. We leverage the local differential privacy to achieve our goal. Additionally, we propose a way to find feature points from health data. This allows for an effective trade-off between the degree of privacy and accuracy. We carry out experiments to demonstrate the effectiveness of our proposed approach and the results show that, with the proposed method, the error rate can be reduced upto 77%.

New approach method of finite difference formulas for control algorithm (제어 알고리즘 구현을 위한 새로운 미분값 유도 방법)

  • Kim, Tae-Yeop
    • Journal of IKEEE
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    • v.23 no.3
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    • pp.817-825
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    • 2019
  • Difference equation is useful for control algorithm in the microprocessor. To approximate a derivative values from sampled data, it is used the methods of forward, backward and central differences. The key of computing discrete derivative values is the finite difference coefficient. The focus of this paper is a new approach method of finite difference formula. And we apply the proposed method to the recursive least squares(RLS) algorithm.

Reversible Data Embedding Algorithm Using the Locality of Image and the Adjacent Pixel Difference Sequence (영상의 지역성과 인접 픽셀 차분 시퀀스를 이용하는 가역 데이터 임베딩 기법)

  • Jung, Soo-Mok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.6
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    • pp.573-577
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    • 2016
  • In this paper, reversible data embedding scheme was proposed using the locality of image and the adjacent pixel difference sequence. Generally, locality exists in natural image. The proposed scheme increases the amount of embedding data and enables data embedding at various levels by applying a technique of predicting adjacent pixel values using image locality to an existing technique APD(Adjacent Pixel Difference). The experimental results show that the proposed scheme is very useful for reversible data embedding.

Improved Differential Attack of Seven-Round SEED (7-라운드 SEED에 대한 향상된 차분 공격)

  • Sung, Jae-Chul
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.20 no.4
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    • pp.25-30
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    • 2010
  • Block Cipher SEED which was developed by KISA are not only Korea national standard algorithm of TTA but also one of standard 128-bit block ciphers of ISO/IEC. Since SEED had been developed, many analyses were tried but there was no distinguishing cryptanalysis except the 7-round differential attack in 2002. The attack used the 6-round differential characteristic with probability $2^{-124}$ and analyzed the 7-round SEED with $2^{127}$ chosen plaintexts. In this paper, we propose a new 6-round differential characteristic with probability $2^{-110}$ and analyze the 7-round SEED with $2^{113}$ chosen plaintexts.

Vegetation Height and Age Estimation using Shuttle Radar Topography Mission and National Elevation Datasets (SRTM과 NED를 이용한 식생수고 및 수령 추정)

  • Kim, Jin-Woo;Heo, Joon;Sohn, Hong-Gyoo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1D
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    • pp.203-209
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    • 2006
  • SAR (Synthetic Aperture Radar) technology, which is not influenced by cloud cover because of using electromagnetic wave of long wavelength, has an advantage in mapping the earth. NASA, recognizing these strong points of SAR, launched SRTM (Shuttle Radar Topography Mission), and acquired the topographic information of the earth. SRTM and NED (National Elevation Data) of USGS were used for the research and vegetation height map was produced through differentiating the two data. Correlation between SRTM-NED and planting year was analyzed to see the relationship. Strong correlation was detected and it shows the feasibility of estimating timber age and eventually creating timber age map from SRTM-NED. Additional analyses were conducted to check if the linearity is influenced by regional characteristics and forest uniformity. As results, the correlation between SRTM-NED and timber age is influenced by roughness of the terrain. Overall, this paper shows that timber age estimation using SRTM and NED can be sufficiently practical.

A Study of Split Learning Model to Protect Privacy (프라이버시 침해에 대응하는 분할 학습 모델 연구)

  • Ryu, Jihyeon;Won, Dongho;Lee, Youngsook
    • Convergence Security Journal
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    • v.21 no.3
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    • pp.49-56
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    • 2021
  • Recently, artificial intelligence is regarded as an essential technology in our society. In particular, the invasion of privacy in artificial intelligence has become a serious problem in modern society. Split learning, proposed at MIT in 2019 for privacy protection, is a type of federated learning technique that does not share any raw data. In this study, we studied a safe and accurate segmentation learning model using known differential privacy to safely manage data. In addition, we trained SVHN and GTSRB on a split learning model to which 15 different types of differential privacy are applied, and checked whether the learning is stable. By conducting a learning data extraction attack, a differential privacy budget that prevents attacks is quantitatively derived through MSE.

Design of Multiple Model Fuzzy Prediction Systems Based on HCKA (HCKA 기반 다중 모델 퍼지 예측 시스템의 구현)

  • Bang, Young-Keun;Shim, Jae-Son;Park, Ha-Yong;Lee, Chul-Heui
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.1642_1643
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    • 2009
  • 일반적으로, 퍼지 예측 시스템의 성능은 데이터의 특성과 퍼지 집합을 생성하기 위한 클러스터일 기법에 매우 의존적이다. 하지만, 예측을 위한 시계열 데이터들은 자연현상에 기인하는 강한 비선형적 특성을 가지고 있으므로 적합한 시스템을 구현하는 것에 많은 제약이 따른다. 따라서 본 논문에서는 시계열의 비선형적 특성을 적절히 취급하기 위하여, 그들로부터 생성 가능한 차분 데이터 중, 유효한 차분데이터를 이용하여 다중 모델 퍼지 예측 시스템을 구현함으로써, 보다 우수한 예측이 가능하도록 하였으며, 퍼지 시스템의 모델링에는 교차 상관분석기법에 따른 계층적 구조의 클러스터링 기법 (Hierarchical Cross-correlation and K-means Clustering Algorithms: HCKA)을 적용하여, 시스템을 위한 규칙기반의 적합성을 높일 수 있도록 하였다.

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Design of Fuzzy System with Hierarchical Classifying Structures and its Application to Time Series Prediction (계층적 분류구조의 퍼지시스템 설계 및 시계열 예측 응용)

  • Bang, Young-Keun;Lee, Chul-Heui
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.5
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    • pp.595-602
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    • 2009
  • Fuzzy rules, which represent the behavior of their system, are sensitive to fuzzy clustering techniques. If the classification abilities of such clustering techniques are improved, their systems can work for the purpose more accurately because the capabilities of the fuzzy rules and parameters are enhanced by the clustering techniques. Thus, this paper proposes a new hierarchically structured clustering algorithm that can enhance the classification abilities. The proposed clustering technique consists of two clusters based on correlationship and statistical characteristics between data, which can perform classification more accurately. In addition, this paper uses difference data sets to reflect the patterns and regularities of the original data clearly, and constructs multiple fuzzy systems to consider various characteristics of the differences suitably. To verify effectiveness of the proposed techniques, this paper applies the constructed fuzzy systems to the field of time series prediction, and performs prediction for nonlinear time series examples.

Kernel-Based Video Frame Interpolation Techniques Using Feature Map Differencing (특성맵 차분을 활용한 커널 기반 비디오 프레임 보간 기법)

  • Dong-Hyeok Seo;Min-Seong Ko;Seung-Hak Lee;Jong-Hyuk Park
    • KIPS Transactions on Software and Data Engineering
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    • v.13 no.1
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    • pp.17-27
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    • 2024
  • Video frame interpolation is an important technique used in the field of video and media, as it increases the continuity of motion and enables smooth playback of videos. In the study of video frame interpolation using deep learning, Kernel Based Method captures local changes well, but has limitations in handling global changes. In this paper, we propose a new U-Net structure that applies feature map differentiation and two directions to focus on capturing major changes to generate intermediate frames more accurately while reducing the number of parameters. Experimental results show that the proposed structure outperforms the existing model by up to 0.3 in PSNR with about 61% fewer parameters on common datasets such as Vimeo, Middle-burry, and a new YouTube dataset. Code is available at https://github.com/Go-MinSeong/SF-AdaCoF.

Improved Differential-Linear Cryptanalysis Using DLCT (DLCT를 활용한 향상된 차분선형 분석)

  • Kim, Hyunwoo;Kim, Seonggyeom;Hong, Deukjo;Sung, Jaechul;Hong, Seokhie
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.6
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    • pp.1379-1392
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    • 2018
  • The complexity of the differential-linear cryptanalysis is strongly influenced by the probability of the differential-linear characteristic computed under the assumption of round independence, linear approximation independence, and uniformity for the trail that does not satisfy differential trail. Therefore, computing the exact probability of the differential-linear characteristic is a very important issue related to the validity of the attack. In this paper, we propose a new concept called DLCT(Differential-Linear Connectivity Table) for the differential-linear cryptanalysis. Additionally, we propose an improved probability computation technique of differential-linear characteristic by applying DLCT. By doing so, we were able to weaken linear approximation independence assumption. We reanalyzed the previous results by applying DLCT to DES and SERPENT. The probability of 7-round differential-linear characteristic of DES is $1/2+2^{-5.81}$, the probability of 9-round differential-linear characteristic of SERPENT is computed again to $1/2+2^{-57.9}$, and data complexity required for the attack is reduced by $2^{0.2}$ and $2^{2.2}$ times, respectively.