• Title/Summary/Keyword: Masking scheme

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An Entropy Masking Model for Image and Video Watermarking (영상 워터마킹을 위한 엔트로피 마스킹 모델)

  • Kim, Seong-Whan;Shan Suthaharan
    • The KIPS Transactions:PartB
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    • v.10B no.5
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    • pp.491-496
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    • 2003
  • We present a new watermark design tool for digital images and digital videos that are based on human visual system (HVS) characteristics. In this tool, basic mechanisms (inhibitory and excitatory behaviour of cells) of HVS are used to determine image dependent upper bound values on watermark insertion. This allows us to insert maximai allowable transparent watermark, which in turn is extremely hard to attack with common image processing, Motion Picture Experts Group (MPEG) compression. As the number of details (e.g. edges) increases in an image, the HVS decrease its sensitivity to the details. In the same manner, as the number of motion increases in a video signal, the HVS decrease its sensitivity to the motions. We model this decreased sensitivity to the details and motions as an (motion) entropy masking. Entropy masking model can be efficiently used to increase the robustness of image and video watermarks. We have shown that our entropy-masking model provides watermark scheme with increased transparency and henceforth increased robustness.

Deep Learning-based Target Masking Scheme for Understanding Meaning of Newly Coined Words (신조어의 의미 학습을 위한 딥러닝 기반 표적 마스킹 기법)

  • Nam, Gun-Min;Seo, Sumin;Kwahk, Kee-Young;Kim, Namgyu
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.391-394
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    • 2021
  • 최근 딥러닝(Deep Learning)을 활용하여 텍스트로 표현된 단어나 문장의 의미를 파악하기 위한 다양한 연구가 활발하게 수행되고 있다. 하지만, 딥러닝을 통해 특정 도메인에서 사용되는 언어를 이해하기 위해서는 해당 도메인의 충분한 데이터에 대해 오랜 시간 학습이 수행되어야 한다는 어려움이 있다. 이러한 어려움을 극복하고자, 최근에는 방대한 양의 데이터에 대한 학습 결과인 사전 학습 언어 모델(Pre-trained Language Model)을 다른 도메인의 학습에 적용하는 방법이 딥러닝 연구에서 많이 사용되고 있다. 이들 접근법은 사전 학습을 통해 단어의 일반적인 의미를 학습하고, 이후에 단어가 특정 도메인에서 갖는 의미를 파악하기 위해 추가적인 학습을 진행한다. 추가 학습에는 일반적으로 대표적인 사전 학습 언어 모델인 BERT의 MLM(Masked Language Model)이 다시 사용되며, 마스크(Mask) 되지 않은 단어들의 의미로부터 마스크 된 단어의 의미를 추론하는 형태로 학습이 이루어진다. 따라서 사전 학습을 통해 의미가 파악되어 있는 단어들이 마스크 되지 않고, 신조어와 같이 의미가 알려져 있지 않은 단어들이 마스크 되는 비율이 높을수록 단어 의미의 학습이 정확하게 이루어지게 된다. 하지만 기존의 MLM은 무작위로 마스크 대상 단어를 선정하므로, 사전 학습을 통해 의미가 파악된 단어와 사전 학습에 포함되지 않아 의미 파악이 이루어지지 않은 신조어가 별도의 구분 없이 마스크에 포함된다. 따라서 본 연구에서는 사전 학습에 포함되지 않았던 신조어에 대해서만 집중적으로 마스킹(Masking)을 수행하는 방안을 제시한다. 이를 통해 신조어의 의미 학습이 더욱 정확하게 이루어질 수 있고, 궁극적으로 이러한 학습 결과를 활용한 후속 분석의 품질도 향상시킬 수 있을 것으로 기대한다. 영화 정보 제공 사이트인 N사로부터 영화 댓글 12만 건을 수집하여 실험을 수행한 결과, 제안하는 신조어 표적 마스킹(NTM: Newly Coined Words Target Masking)이 기존의 무작위 마스킹에 비해 감성 분석의 정확도 측면에서 우수한 성능을 보임을 확인하였다.

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A Non-Cacheable Address Designating Scheme in MMU-less Embedded Microprocessor Systems

  • Lim, Yong-Seok;Suh, Woon-Sik;Kim, Suki
    • Proceedings of the IEEK Conference
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    • 2002.06e
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    • pp.235-238
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    • 2002
  • This paper proposes a novel scheme of designating non-cacheable addresses of memories in embedded systems of multi-master architectures without a Memory Management Unit (MMU). As a solution for data coherency problem between external memories and a cache memory, we proposes a cache masking scheme by allocating the most significant bit of address not used in 32-bit address system as indicator bit to designate non-cacheable address. As this scheme enables non-cacheable area designation every address, the simpler in the aspect of hardware and more flexible size of non-cacheable area can be obtained.

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Iterative Pre-Whitening Projection Statistics for Improving Multi-Target Detection Performance in Non-Homogeneous Clutter (불균일 클러터 환경에서 다중 표적탐지 성능 향상을 위한 반복 백색화 투영 통계 기법)

  • Park, Hyuck;Kang, Jin-Whan;Kim, Sang-Hyo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.4
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    • pp.120-128
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    • 2012
  • In this paper, we propose a modified iterative pre-whitening projection statistics (MIPPS) scheme for improving multi-target detection performance in non-homogeneous clutter environments. As a non-homogeneity detection (NHD) technique of space-time adaptive processing algorithm for airborne radar, the MIPPS scheme improves the average detection probability of weak target when multiple targets with different reflection signal intensities are located in close range. Numerical results show that the conventional NHD schemes suffers from the masking effect by strong targets and clutters and the proposed MIPPS scheme outperforms the conventional schemes with respect to the average detection probability of the weak target at low signal-to-clutter ratio.

Access-Authorizing and Privacy-Preserving Auditing with Group Dynamic for Shared Cloud Data

  • Shen, Wenting;Yu, Jia;Yang, Guangyang;Zhang, Yue;Fu, Zhangjie;Hao, Rong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.7
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    • pp.3319-3338
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    • 2016
  • Cloud storage is becoming more and more popular because of its elasticity and pay-as-you-go storage service manner. In some cloud storage scenarios, the data that are stored in the cloud may be shared by a group of users. To verify the integrity of cloud data in this kind of applications, many auditing schemes for shared cloud data have been proposed. However, all of these schemes do not consider the access authorization problem for users, which makes the revoked users still able to access the shared cloud data belonging to the group. In order to deal with this problem, we propose a novel public auditing scheme for shared cloud data in this paper. Different from previous work, in our scheme, the user in a group cannot any longer access the shared cloud data belonging to this group once this user is revoked. In addition, we propose a new random masking technique to make our scheme preserve both data privacy and identity privacy. Furthermore, our scheme supports to enroll a new user in a group and revoke an old user from a group. We analyze the security of the proposed scheme and justify its performance by concrete implementations.

Robust Image Watermarking via Perceptual Structural Regularity-based JND Model

  • Wang, Chunxing;Xu, Meiling;Wan, Wenbo;Wang, Jian;Meng, Lili;Li, Jing;Sun, Jiande
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.1080-1099
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    • 2019
  • A better tradeoff between robustness and invisibility will be realized by using the just noticeable (JND) model into the quantization-based watermarking scheme. The JND model is usually used to describe the perception characteristics of human visual systems (HVS). According to the research of cognitive science, HVS can adaptively extract the structure features of an image. However, the existing JND models in the watermarking scheme do not consider the structure features. Therefore, a novel JND model is proposed, which includes three aspects: contrast sensitivity function, luminance adaptation, and contrast masking (CM). In this model, the CM effect is modeled by analyzing the direction features and texture complexity, which meets the human visual perception characteristics and matches well with the spread transform dither modulation (STDM) watermarking framework by employing a new method to measure edge intensity. Compared with the other existing JND models, the proposed JND model based on structural regularity is more efficient and applicable in the STDM watermarking scheme. In terms of the experimental results, the proposed scheme performs better than the other watermarking scheme based on the existing JND models.

Analysis on Vulnerability of Masked SEED Algorithm (마스킹 기법이 적용된 SEED 알고리즘에 대한 취약점 분석)

  • Kim, TaeWon;Chang, Nam Su
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.4
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    • pp.739-747
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    • 2015
  • Masking technique that is most widely known as countermeasure against power analysis attack prevents leakage for sensitive information during the implementations of cryptography algorithm. it have been studied extensively until now applied on block cipher algorithms. Masking countermeasure have been applied to international standard SEED algorithm. Masked SEED algorithm proposed by Cho et al, not only protects against first order power analysis attacks but also efficient by reducing the execution of Arithmetic to Boolean converting function. In this paper, we analyze the vulnerability of Cho's algorithm against first order power analysis attacks. We targeted additional pre-computation to improve the efficiency in order to recover the random mask value being exploited in first order power analysis attacks. We describe weakness by considering both theoretical and practical aspects and are expecting to apply on every device equipped with cho's algorithm using the proposed attack method.

Enhanced Pre echo Control Algorithm for MPEG Audio Coders (MPEG 오디오 부호화기를 위한 향상된 프리 에코 컨트롤 알고리듬)

  • Lee Chang-Joon;Lee Jae-Seong;Park Young-Cheol
    • Journal of Broadcast Engineering
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    • v.11 no.2 s.31
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    • pp.191-199
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    • 2006
  • This paper presents an efficient pre echo control scheme for MPEG Audio coders based on the psychoacoustic model II (PAM-II). Pre echo control is the final step for the calculation of masking threshold in the PAM II. It is to minimize the spread of quantization error over the processing frame. In the conventional encoders, pre echo is reduced by restricting the estimated masking threshold not to exceed the one obtained in the previous frame. The conventional method performs pre echo control not only for short blocks but also for long blocks, which lowers the masking threshold in long blocks and, in turn, increases the quantization noise level of corresponding blocks. This paper proposes an efficient pre echo control process. The test result shows a mean enhancement of more than 0.4 especially for complex signals on the ITU R 5 point audio impairment scale.

Perceptual and Adaptive Quantization of Line Spectral Frequency Parameters (선 스펙트럼 주파수의 청각 적응 부호화)

  • 한우진;김은경;오영환
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.8
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    • pp.68-77
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    • 2000
  • Line special frequency (LSF) parameters have been widely used in low bit-rate speech coding due to their efficiency for representing the short-time speech spectrum. In this paper, a new distance measure based on the masking properties of human ear is proposed for quantizing LSF parameters whereas most conventional quantization methods are based on the weighted Euclidean distance measure. The proposed method derives the perceptual distance measure from the definition of noise-to-mask ratio (NMR) which has high correspondence with the actual distortion received in the human ear and uses it for quantizing LSF parameters. In addition, we propose an adaptive bit allocation scheme, which allocates minimal bits to LSF parameters maintaining the perceptual transparency of given speech frame for reducing the average bit-rates. For the performance evaluation, we has shown the ratio of perceptually transparent frames and the corresponding average bit-rates for the conventional and proposed methods. By jointly combining the proposed distance measure and adaptive bit allocation scheme, the proposed system requires only 770 bps for obtaining 95.5% perceptually transparent frames, while the conventional systems produce 89.9% at even 1800 bps.

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Object-based Digital Watermarking Using Wavelet Property (웨이브릿 특성을 이용한 객체기반 디지털 워터마킹)

  • 김유신;원치선;이재진
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.7A
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    • pp.1037-1043
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    • 2000
  • In this paper we present an object-based watermarking scheme, which cuts out several featured portions from an image and casts chaotic sequences as a watermark into the extracted object image in the discrete wavelet domain with respect to the models of the human visual system. In such a way we can insert watermark to several objects of an image separately. Advantages of the proposed scheme include that it can protect featured object out of an image selectively as well as entire image and casts watermark sequences according to human visual masking utilizing the time-frequency localization property of the wavelet transform.

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