• 제목/요약/키워드: Hidden Data

검색결과 962건 처리시간 0.029초

A Method of Data Hiding in a File System by Modifying Directory Information

  • Cho, Gyu-Sang
    • 한국컴퓨터정보학회논문지
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    • 제23권8호
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    • pp.85-93
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    • 2018
  • In this research, it is proposed that a method to hide data by modifying directory index entry information. It consists of two methods: a directory list hiding and a file contents hiding. The directory list hiding method is to avoid the list of files from appearing in the file explorer window or the command prompt window. By modifying the file names of several index entries to make them duplicated, if the duplicated files are deleted, then the only the original file is deleted, but the modified files are retained in the MFT entry intact. So, the fact that these files are hidden is not exposed. The file contents hiding is to allocate data to be hidden on an empty index record page that is not used. If many files are made in the directory, several 4KB index records are allocated. NTFS leaves the empty index records unchanged after deleting the files. By modifying the run-list of the index record with the cluster number of the file-to-hide, the contents of the file-to-hide are hidden in the index record. By applying the proposed method to the case of hiding two files, the file lists are not exposed in the file explorer and the command prompt window, and the contents of the file-to-hide are hidden in the empty index record. It is proved that the proposed method has effectiveness and validity.

Hidden truncation circular normal distribution

  • Kim, Sung-Su;Sengupta, Ashis
    • Journal of the Korean Data and Information Science Society
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    • 제23권4호
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    • pp.797-805
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    • 2012
  • Many circular distributions are known to be not only asymmetric but also bimodal. Hidden truncation method of generating asymmetric distribution is applied to a bivariate circular distribution to generate an asymmetric circular distribution. While many other existing asymmetric circular distributions can only model an asymmetric data, this new circular model has great flexibility in terms of asymmetry and bi-modality. Some properties of the new model, such as the trigonometric moment generating function, and asymptotic inference about the truncation parameter are presented. Simulation and real data examples are provided at the end to demonstrate the utility of the novel distribution.

CRM을 위한 은닉 마코프 모델과 유사도 검색을 사용한 시계열 데이터 예측 (Time-Series Data Prediction using Hidden Markov Model and Similarity Search for CRM)

  • 조영희;전진호;이계성
    • 한국컴퓨터정보학회논문지
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    • 제14권5호
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    • pp.19-28
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    • 2009
  • 시계열의 예측에 대한 문제는 오랫동안 많은 연구자들의 연구의 대상이었으며 예측을 위한 많은 방법이 제안되었다. 본 논문에서는 은닉 마코프 모델(Hidden Markov Model)과 우도(likelihood)를 사용한 유사도 검색을 통하여 향후 시계열 데이터의 운행 방향을 예측하는 방법을 제안한다. 이전에 기록된 시계열 데이터에서 질의 시퀸스(sequence)와 유사한 부분을 검색하고 유사 부분의 서브 시퀸스를 사용하여 시계열을 예측하는 방법이다. 먼저 주어진 질의 시퀸스에 대한 은닉 마코프 모델을 작성한다. 그리고 시계열 데이터에서 순차적으로 일정 길이의 서브 시퀸스를 추출하고 추출된 서브 시퀸스와 작성된 은닉 마코프 모델과의 우도를 계산한다. 시계열 데이터로부터 추출된 서브 시퀸스 중에서 우도가 가장 높은 시퀸스를 유사 시퀸스로 결정하고 결정된 부분 이후의 값을 추출하여 질의 시퀸스 이후의 예측 값을 추정한다. 실험 결과 예측 값과 실제 값이 상당한 유사성을 나타내었다. 제안된 방법의 유효성은 코스피(KOSPI) 종합주가지수를 대상으로 실험하여 검증한다.

은닉 마르코프 모델을 이용한 속도 변화가 있는 회전 기계의 상태 진단 기법 (Condition Monitoring of Rotating Machine with a Change in Speed Using Hidden Markov Model)

  • 장미;이종민;황요하;조유종;송재복
    • 한국소음진동공학회논문집
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    • 제22권5호
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    • pp.413-421
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    • 2012
  • In industry, various rotating machinery such as pumps, gas turbines, compressors, electric motors, generators are being used as an important facility. Due to the industrial development, they make high performance(high-speed, high-pressure). As a result, we need more intelligent and reliable machine condition diagnosis techniques. Diagnosis technique using hidden Markov-model is proposed for an accurate and predictable condition diagnosis of various rotating machines and also has overcame the speed limitation of time/frequency method by using compensation of the rotational speed of rotor. In addition, existing artificial intelligence method needs defect state data for fault detection. hidden Markov model can overcome this limitation by using normal state data alone to detect fault of rotational machinery. Vibration analysis of step-up gearbox for wind turbine was applied to the study to ensure the robustness of diagnostic performance about compensation of the rotational speed. To assure the performance of normal state alone method, hidden Markov model was applied to experimental torque measuring gearbox in this study.

군용 무전기를 이용한 근거리 무선 데이터 전송에서의 분산 매체 접근 제어 방식의 성능 분석 (A Performance Analysis of DFWMAC Protocols in Short-Distance Wireless Data Transmission Using Military Radio)

  • 이성규;최영윤
    • 한국군사과학기술학회지
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    • 제2권2호
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    • pp.117-130
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    • 1999
  • In this paper, the performance of data communication function of military radio equipment P-999K is analyzed based on the standard CSMA/CA protocol which is DFWMAC standard protocol done by IEEE802.11 work group. Basic three standard protocols, i.e. Basic CSMA/CA, Stop & Wait ARQ and 4-Way Handshake CSMA/CA protocols are analyzed and compared with each other under the hidden terminal environment. The computer simulation is also done by using SIMSCRIPT II.5 which is popular software tool for an independent processing. The results show that p-persistent(with p=0.3) CSMA scheme is superior to non-persistent CSMA scheme with non-hidden terminal condition, but the performances of both schemes are almost same with hidden terminal situation. And the results of computer simulations are also showed that Basic CSMA/CA protocol is superior to the other protocols when the ratio of hidden terminals is below 10 % of total user population, however, with the above 20% hidden terminals environment and the higher offered traffic conditions the 4-Way Handshake CSMA/CA protocol shows the most superior performance.

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Evaluation of existing bridges using neural networks

  • Molina, Augusto V.;Chou, Karen C.
    • Structural Engineering and Mechanics
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    • 제13권2호
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    • pp.187-209
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    • 2002
  • The infrastructure system in the United States has been aging faster than the resource available to restore them. Therefore decision for allocating the resources is based in part on the condition of the structural system. This paper proposes to use neural network to predict the overall rating of the structural system because of the successful applications of neural network to other fields which require a "symptom-diagnostic" type relationship. The goal of this paper is to illustrate the potential of using neural network in civil engineering applications and, particularly, in bridge evaluations. Data collected by the Tennessee Department of Transportation were used as "test bed" for the study. Multi-layer feed forward networks were developed using the Levenberg-Marquardt training algorithm. All the neural networks consisted of at least one hidden layer of neurons. Hyperbolic tangent transfer functions were used in the first hidden layer and log-sigmoid transfer functions were used in the subsequent hidden and output layers. The best performing neural network consisted of three hidden layers. This network contained three neurons in the first hidden layer, two neurons in the second hidden layer and one neuron in the third hidden layer. The neural network performed well based on a target error of 10%. The results of this study indicate that the potential for using neural networks for the evaluation of infrastructure systems is very good.

PAPG: Private Aggregation Scheme based on Privacy-preserving Gene in Wireless Sensor Networks

  • Zeng, Weini;Chen, Peng;Chen, Hairong;He, Shiming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권9호
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    • pp.4442-4466
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    • 2016
  • This paper proposes a privacy-preserving aggregation scheme based on the designed P-Gene (PAPG) for sensor networks. The P-Gene is constructed using the designed erasable data-hiding technique. In this P-Gene, each sensory data item may be hidden by the collecting sensor node, thereby protecting the privacy of this data item. Thereafter, the hidden data can be directly reported to the cluster head that aggregates the data. The aggregation result can then be recovered from the hidden data in the cluster head. The designed P-Genes can protect the privacy of each data item without additional data exchange or encryption. Given the flexible generation of the P-Genes, the proposed PAPG scheme adapts to dynamically changing reporting nodes. Apart from its favorable resistance to data loss, the extensive analyses and simulations demonstrate how the PAPG scheme efficiently preserves privacy while consuming less communication and computational overheads.

복합문서 파일에 은닉된 데이터 탐지 기법에 대한 연구 (An effective detection method for hiding data in compound-document files)

  • 김은광;전상준;한재혁;이민욱;이상진
    • 정보보호학회논문지
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    • 제25권6호
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    • pp.1485-1494
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    • 2015
  • 기존 데이터 은닉은 대용량 멀티미디어 파일에 데이터를 삽입하는 방식으로 이루어졌다. 하지만 최근 Microsoft Office 2003 이하 버전 제품의 문서파일은 구조가 파일시스템과 유사하여 데이터 은닉이 비교적 용이해 커버데이터(Cover data)로 사용되고 있다. 데이터가 은닉된 문서파일을 MS Office 프로그램으로 실행할 경우 은닉 사실을 모르는 사용자는 은닉 데이터를 눈으로 쉽게 확인할 수 없다. 이에 본 논문에서는 Microsoft Office 2003 이하 버전과 한컴오피스 문서파일에서 사용되는 복합문서 파일 이진형식(Compound File Binary Format) 파일 포맷 구조를 분석하여 데이터 삽입이 가능한 공간을 살펴보고 이를 탐지하기 위한 방안을 제시하고자 한다.

Multirate를 지원하는 애드 혹 무선 망에서의 Hidden Terminal 문제 분석 (Hidden Terminal Problem Analysis in Multirate Ad Hoc Networks)

  • 이민형;유준;김종권
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2003년도 가을 학술발표논문집 Vol.30 No.2 (3)
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    • pp.478-480
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    • 2003
  • IEEE 802.11 무선 MAC 표준은 물리 계층에서 Multirate를 제공하며. 이를 이용하기 위한 다양한 Rate adaptation 알고리즘들이 제안되었다. 일반적으로 애드 혹 무선 망은 802.11의 MAC을 기반으로 하므로 Multirate를 고려할 필요가 있다. Multirate을 지원하는 상황에서 높은 Data Rate로 통신을 할 경우, 그에 따른 높은 SNR (Signal to Noise Ratio) Threshold가 요구되므로. 기존의 RTS/CTS로는 해결할 수 없는 심각한 Hidden Terminal 문제가 발생할 수 있다. 이 논문에서는 Multirate를 지원하는 애드 혹 무선 망에서의 Hidden Terminal 문제를 분석하고 분석의 수치결과를 제시한다. 또한. Hidden Terminal 문제를 해결하기 위한 새로운 방안을 제안한다.

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Hidden LMS 적응 필터링 알고리즘을 이용한 경쟁학습 화자검증 (Speaker Verification Using Hidden LMS Adaptive Filtering Algorithm and Competitive Learning Neural Network)

  • 조성원;김재민
    • 대한전기학회논문지:시스템및제어부문D
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    • 제51권2호
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    • pp.69-77
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    • 2002
  • Speaker verification can be classified in two categories, text-dependent speaker verification and text-independent speaker verification. In this paper, we discuss text-dependent speaker verification. Text-dependent speaker verification system determines whether the sound characteristics of the speaker are equal to those of the specific person or not. In this paper we obtain the speaker data using a sound card in various noisy conditions, apply a new Hidden LMS (Least Mean Square) adaptive algorithm to it, and extract LPC (Linear Predictive Coding)-cepstrum coefficients as feature vectors. Finally, we use a competitive learning neural network for speaker verification. The proposed hidden LMS adaptive filter using a neural network reduces noise and enhances features in various noisy conditions. We construct a separate neural network for each speaker, which makes it unnecessary to train the whole network for a new added speaker and makes the system expansion easy. We experimentally prove that the proposed method improves the speaker verification performance.