• Title/Summary/Keyword: Information Signal Process

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A Novel RGB Image Steganography Using Simulated Annealing and LCG via LSB

  • Bawaneh, Mohammed J.;Al-Shalabi, Emad Fawzi;Al-Hazaimeh, Obaida M.
    • International Journal of Computer Science & Network Security
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    • v.21 no.1
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    • pp.143-151
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    • 2021
  • The enormous prevalence of transferring official confidential digital documents via the Internet shows the urgent need to deliver confidential messages to the recipient without letting any unauthorized person to know contents of the secret messages or detect there existence . Several Steganography techniques such as the least significant Bit (LSB), Secure Cover Selection (SCS), Discrete Cosine Transform (DCT) and Palette Based (PB) were applied to prevent any intruder from analyzing and getting the secret transferred message. The utilized steganography methods should defiance the challenges of Steganalysis techniques in term of analysis and detection. This paper presents a novel and robust framework for color image steganography that combines Linear Congruential Generator (LCG), simulated annealing (SA), Cesar cryptography and LSB substitution method in one system in order to reduce the objection of Steganalysis and deliver data securely to their destination. SA with the support of LCG finds out the optimal minimum sniffing path inside a cover color image (RGB) then the confidential message will be encrypt and embedded within the RGB image path as a host medium by using Cesar and LSB procedures. Embedding and extraction processes of secret message require a common knowledge between sender and receiver; that knowledge are represented by SA initialization parameters, LCG seed, Cesar key agreement and secret message length. Steganalysis intruder will not understand or detect the secret message inside the host image without the correct knowledge about the manipulation process. The constructed system satisfies the main requirements of image steganography in term of robustness against confidential message extraction, high quality visual appearance, little mean square error (MSE) and high peak signal noise ratio (PSNR).

Pre-processing Method of Raw Data Based on Ontology for Machine Learning (머신러닝을 위한 온톨로지 기반의 Raw Data 전처리 기법)

  • Hwang, Chi-Gon;Yoon, Chang-Pyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.5
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    • pp.600-608
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    • 2020
  • Machine learning constructs an objective function from learning data, and predicts the result of the data generated by checking the objective function through test data. In machine learning, input data is subjected to a normalisation process through a preprocessing. In the case of numerical data, normalization is standardized by using the average and standard deviation of the input data. In the case of nominal data, which is non-numerical data, it is converted into a one-hot code form. However, this preprocessing alone cannot solve the problem. For this reason, we propose a method that uses ontology to normalize input data in this paper. The test data for this uses the received signal strength indicator (RSSI) value of the Wi-Fi device collected from the mobile device. These data are solved through ontology because they includes noise and heterogeneous problems.

Power-Based Side Channel Attack and Countermeasure on the Post-Quantum Cryptography NTRU (양자내성암호 NTRU에 대한 전력 부채널 공격 및 대응방안)

  • Jang, Jaewon;Ha, Jaecheol
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.6
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    • pp.1059-1068
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    • 2022
  • A Post-Quantum Cryptographic algorithm NTRU, which is designed by considering the computational power of quantum computers, satisfies the mathematically security level. However, it should consider the characteristics of side-channel attacks such as power analysis attacks in hardware implementation. In this paper, we verify that the private key can be recovered by analyzing the power signal generated during the decryption process of NTRU. To recover the private keys, the Simple Power Analysis (SPA), Correlation Power Analysis (CPA) and Differential Deep Learning Analysis (DDLA) were all applicable. There is a shuffling technique as a basic countermeasure to counter such a power side-channel attack. Neverthe less, we propose a more effective method. The proposed method can prevent CPA and DDLA attacks by preventing leakage of power information for multiplication operations by only performing addition after accumulating each coefficient, rather than performing accumulation after multiplication for each index.

Development of Wireless Measurement System for Bridge Using PDA and Fiber Optical Sensor (PDA와 광섬유 센서를 이용한 교량의 무선계측 시스템 개발)

  • Kwak, Kae-Hwan;Hwang, Hae-Sung;Jang, Hwa-Sup;Kim, Woo-Jong;Kim, Hoi-OK
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.13 no.1 s.53
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    • pp.88-96
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    • 2009
  • This study proposes a wireless measurement system that is a new safety management system by using an FBG sensor and a PDA. The sensor part has many advantages of implementing a wireless measurement system, and the study emploies an FBG-LVDT sensor, FBG-STRAIN sensor, FBG-TEMP sensor, and FBG-ACC sensor, using FBG sensors. Also, the study show a configuration of a signal process system for operating a wireless transmission system of FBG sensors applied to the signal process system, and engrafted the cutting edge information technology industry in order to display from a remote distance using a PDA. In order to verify the applicability of the developed FBG sensors and wireless measurement monitoring system to the field, their accuracy, and usability, the study has conducted a static and dynamic test to a bridge in the field. The study made an assessment of service for the vibration of the bridge by applying dynamic data measured by an FBG-LVDT sensor and FBG-ACC sensor to Meister's curve and prepared methods for assessing the vibration of the bridge by proposing a standard of vibration limitation given the service of vibration of the bridge. As a follow up for this study, it would be necessary to set up an overall model for the standard of service assessment established in this study.

A noble Sample-and-Hold Circuit using A Micro-Inductor To Improve The Contrast Resolution of X-ray CMOS Image Sensors (X-ray CMOS 영상 센서의 대조 해상도 향상을 위해 Micro-inductor를 적용한 새로운 Sample-and-Hold 회로)

  • Lee, Dae-Hee;Cho, Gyu-Seong;Kang, Dong-Uk;Kim, Myung-Soo;Cho, Min-Sik;Yoo, Hyun-Jun;Kim, Ye-Won
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.49 no.4
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    • pp.7-14
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    • 2012
  • A image quality is limited by a sample-and-hold circuit of the X-ray CMOS image sensor even though simple mos switch or bootstrapped clock circuit are used to get high quality sampled signal. Because distortion of sampled signal is produced by the charge injection from sample-and-hold circuit even using bootstrapped. This paper presents the 3D micro-inductor design methode in the CMOS process. Using this methode, it is possible to increase the ENOB (effective number of bit) through the use of micro-inductor which is calculated and designed in standard CMOS process in this paper. The ENOB is improved 0.7 bit from 17.64 bit to 18.34 bit without any circuit just by optimized inductor value resulting in verified simulation result. Because of this feature, micro-inductor methode suggested in this paper is able to adapt a mamography that is needed high resolution so that it help to decrease patients dose amount.

Optical security system using multi-phase separation and phase-wrapping method (다중 위상 분할과 위상 랩핑 방법을 이용한 광 암호화 시스템)

  • Shin Chang Mok;Kim Soo Joong;Seo Dong Hoan
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.42 no.6 s.336
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    • pp.31-38
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    • 2005
  • In this paper, we proposed an optical security system based on a gray-image exclusive-OR encryption using multi-phase separation and phase-wrapping method. For encryption, a gray image is sliced into binary images, which have the same pixel value, and these images are encrypted by modified XOR rules with binary random images. The XORed images and the binary images respectively combined and converted into full phase images, called an encrypted image and a key image. For decryption, when the encrypted image and key image are used as inputs on optical elements, Practically due to limited controllability of phase range in optical elements, the original gray image cannot be efficiently reconstructed by these optical elements. Therefore, by decreasing the phase ranges of the encrypted image and key image using a phase-wrapping method and separating these images into low-level phase images using multi-phase separation, the gray image can be reconstructed by optical elements which have limited control range. The decrytion process is simply implemented by interfering a multiplication result of encrypted image and key image with reference light. The validity of proposed scheme is verified and the effects, which are caused by phase limitation in decryption process, is analyzed by using computer simulations.

Spectral Analysis Method to Eliminate Spurious in FMICW HRR Millimeter-Wave Seeker (주파수 변조 단속 지속파를 이용하는 고해상도 밀리미터파 탐색기의 스퓨리어스 제거를 위한 스펙트럼 분석 기법)

  • Yang, Hee-Seong;Chun, Joo-Hwan;Song, Sung-Chan
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.23 no.1
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    • pp.85-95
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    • 2012
  • In this thesis, we develop a spectral analysis scheme to eliminate the spurious peaks generated in HRR Millimeterwave Seeker based on FMICW system. In contrast to FMCW system, FMICW system generates spurious peaks in the spectrum of its IF signal, caused by the periodic discontinuity of the signal. These peaks make the accuracy of the system depend on the previously estimated range if a band pass filter is utilized to eliminate them and noise floor go to high level if random interrupted sequence is utilized and in case of using staggering process, we must transmit several waveforms to obtain overlapped information. Using the spectral analysis one of the schemes such as IAA(Iterative Adaptive Approach) and SPICE(SemiParametric Iterative Covariance-based Estimation method) which were introduced recently, the spurious peaks can be eliminated effectively. In order to utilize IAA and SPICE, since we must distinguish between reliable data and unreliable data and only use reliable data, STFT(Short Time Fourier Transform) is applied to the distinguishment process.

Automatic Tumor Segmentation Method using Symmetry Analysis and Level Set Algorithm in MR Brain Image (대칭성 분석과 레벨셋을 이용한 자기공명 뇌영상의 자동 종양 영역 분할 방법)

  • Kim, Bo-Ram;Park, Keun-Hye;Kim, Wook-Hyun
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.4
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    • pp.267-273
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    • 2011
  • In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

Applications of Regularized Dequantizers for Compressed Images (압축된 영상에서 정규화 된 역양자화기의 응용)

  • Lee, Gun-Ho;Sung, Ju-Seung;Song, Moon-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.39 no.5
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    • pp.11-20
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    • 2002
  • Based on regularization principles, we propose a new dequantization scheme on DCT-based transform coding for reducing of blocking artifacts and minimizing the quantization error. The conventional image dequantization is simply to multiply the received quantized DCT coefficients by the quantization matrix. Therefore, for each DCT coefficients, we premise that the quantization noise is as large as half quantizer step size (in DCT domain). Our approach is based on basic constraint that quantization error is bounded to ${\pm}$(quantizer spacing/2) and at least there are not high frequency components corresponding to discontinuities across block boundaries of the images. Through regularization, our proposed dequantization scheme, sharply reduces blocking artifacts in decoded images. Our proposed algorithm guarantees that the dequantization process will map the quantized DCT coefficients will be evaluated against the standard JPEG, MPEG-1 and H.263 (with Annex J deblocking filter) decoding process. The experimental results will show visual improvements as well as numerical improvements in terms of the peak-signal-to-noise ratio (PSNR) and the blockiness measure (BM) to be defined.

Gaussian Noise Reduction Method using Adaptive Total Variation : Application to Cone-Beam Computed Tomography Dental Image (적응형 총변이 기법을 이용한 가우시안 잡음 제거 방법: CBCT 치과 영상에 적용)

  • Kim, Joong-Hyuk;Kim, Jung-Chae;Kim, Kee-Deog;Yoo, Sun-K.
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.49 no.1
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    • pp.29-38
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    • 2012
  • The noise generated in the process of obtaining the medical image acts as the element obstructing the image interpretation and diagnosis. To restore the true image from the image polluted from the noise, the total variation optimization algorithm was proposed by the R.O. F (L.Rudin, S Osher, E. Fatemi). This method removes the noise by fitting the balance of the regularity and fidelity. However, the blurring phenomenon of the border area generated in the process of performing the iterative operation cannot be avoided. In this paper, we propose the adaptive total variation method by mapping the control parameter to the proposed transfer function for minimizing boundary error. The proposed transfer function is determined by the noise variance and the local property of the image. The proposed method was applied to 464 tooth images. To evaluate proposed method performance, PSNR which is a indicator of signal and noise's signal power ratio was used. The experimental results show that the proposed method has better performance than other methods.