The Experts below are selected from a list of 9966 Experts worldwide ranked by ideXlab platform
Chinchen Chang - One of the best experts on this subject based on the ideXlab platform.
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high Embedding Capacity data hiding algorithm for h 264 avc video sequences without intraframe distortion drift
Security and Communication Networks, 2018Co-Authors: Chinchen Chang, Dinh-chien Nguyen, Thai-son Nguyen, Huan-sheng Hsueh, Fang-rong HsuAbstract:Data hiding is a technique that allows secret data to be delivered securely by Embedding the data into cover digital media. In this paper, we propose a new data hiding algorithm for H.264/advanced video coding (AVC) of video sequences with high Embedding Capacity. In the proposed scheme, to embed secret data into the quantized discrete cosine transform (QDCT) coefficients of frames without any intraframe distortion drift, some embeddable coefficient pairs are selected in each block, and they are divided into two different groups, i.e., the Embedding group and the averting group. The Embedding group is used to carry the secret data, and the averting group is used to prevent distortion drift in the adjacent blocks. The experimental results show that the proposed scheme can avoid intraframe distortion drift and guarantee low distortion of video sequences. In addition, the proposed scheme provides enhanced Embedding Capacity compared to previous schemes. Moreover, the embedded secret data can be extracted completely without the requirement of the original secret data.
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High Embedding Capacity Data Hiding Algorithm for H.264/AVC Video Sequences without Intraframe Distortion Drift
Security and Communication Networks, 2018Co-Authors: Dinh-chien Nguyen, Chinchen Chang, Thai-son Nguyen, Huan-sheng Hsueh, Fang-rong HsuAbstract:Data hiding is a technique that allows secret data to be delivered securely by Embedding the data into cover digital media. In this paper, we propose a new data hiding algorithm for H.264/advanced video coding (AVC) of video sequences with high Embedding Capacity. In the proposed scheme, to embed secret data into the quantized discrete cosine transform (QDCT) coefficients of frames without any intraframe distortion drift, some embeddable coefficient pairs are selected in each block, and they are divided into two different groups, i.e., the Embedding group and the averting group. The Embedding group is used to carry the secret data, and the averting group is used to prevent distortion drift in the adjacent blocks. The experimental results show that the proposed scheme can avoid intraframe distortion drift and guarantee low distortion of video sequences. In addition, the proposed scheme provides enhanced Embedding Capacity compared to previous schemes. Moreover, the embedded secret data can be extracted completely without the requirement of the original secret data.
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ICVIP - Extended Exploiting-Modification-Direction Data Hiding with High Capacity
Proceedings of the International Conference on Video and Image Processing, 2017Co-Authors: Yanjun Liu, Chinchen Chang, Peng-cheng HuangAbstract:Data hiding is referred as a famous and effective technique for delivering secret message securely, in which the secret message is concealed in a cover medium during transmission. At present, reference matrix is extensively applied to data hiding, but the Embedding Capacity of existing reference matrix based data hiding schemes is limited. In this paper, we propose an extended exploiting-modification-direction (EMD) data hiding scheme to enhance the Embedding Capacity. An extended EMD reference matrix is established to guide the hiding procedure such that the Embedding Capacity can achieve as large as 2.5 bpp. Experimental results reveal that the proposed scheme maintains better Embedding Capacity than some state-of-the-art schemes while keeping great image quality.
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IWDW - A High Embedding Capacity Data Hiding Scheme Based upon Permutation Vectors
Digital Forensics and Watermarking, 2017Co-Authors: Chinchen Chang, Jenchun Chang, Yunhong ChouAbstract:Reference-matrix-based data hiding is a way to embed secret data within cover images according to a secret reference matrix. Existing schemes such as exploiting-modification-direction-based method, Sudoku-based method, and magic-cube-based method provide several means to construct reference matrices and embed secret data by modifying the LSBs of cover images according to generated reference matrices. In order to obtain better Embedding Capacity and stego-image quality, we propose a novel data hiding scheme based on permutation vectors. In this proposed scheme, a 1-dimensional reference matrix is constructed by concatenating a secret permutation vector repeatedly. Experimental results show that the proposed scheme achieves higher Embedding Capacity and better stego-image quality. To further improve the visual quality when the Embedding Capacity is less than 1.5 bpp, we also propose an improved version where a 2-dimensional reference matrix is constructed based on a secret permutation vector. The experimental result also demonstrates nice visual quality of our improved scheme.
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a high Embedding Capacity data hiding scheme based upon permutation vectors
International Workshop on Digital Watermarking, 2016Co-Authors: Chinchen Chang, Jenchun Chang, Yunhong ChouAbstract:Reference-matrix-based data hiding is a way to embed secret data within cover images according to a secret reference matrix. Existing schemes such as exploiting-modification-direction-based method, Sudoku-based method, and magic-cube-based method provide several means to construct reference matrices and embed secret data by modifying the LSBs of cover images according to generated reference matrices. In order to obtain better Embedding Capacity and stego-image quality, we propose a novel data hiding scheme based on permutation vectors. In this proposed scheme, a 1-dimensional reference matrix is constructed by concatenating a secret permutation vector repeatedly. Experimental results show that the proposed scheme achieves higher Embedding Capacity and better stego-image quality. To further improve the visual quality when the Embedding Capacity is less than 1.5 bpp, we also propose an improved version where a 2-dimensional reference matrix is constructed based on a secret permutation vector. The experimental result also demonstrates nice visual quality of our improved scheme.
Song Guo - One of the best experts on this subject based on the ideXlab platform.
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Rank-Based Image Watermarking Method With High Embedding Capacity and Robustness
IEEE Access, 2016Co-Authors: Tianrui Zong, Song Guo, Y Xiang, Yue RongAbstract:This paper presents a novel rank-based method for image watermarking. In the watermark Embedding process, the host image is divided into blocks, followed by the 2-D discrete cosine transform (DCT). For each image block, a secret key is employed to randomly select a set of DCT coefficients suitable for watermark Embedding. Watermark bits are inserted into an image block by modifying the set of DCT coefficients using a rank-based Embedding rule. In the watermark detection process, the corresponding detection matrices are formed from the received image using the secret key. Afterward, the watermark bits are extracted by checking the ranks of the detection matrices. Since the proposed watermarking method only uses two DCT coefficients to hide one watermark bit, it can achieve very high Embedding Capacity. Moreover, our method is free of host signal interference. This desired feature and the usage of an error buffer in watermark Embedding result in high robustness against attacks. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method.
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Spread spectrum-based high Embedding Capacity watermarking method for audio signals
IEEE Transactions on Audio Speech and Language Processing, 2015Co-Authors: Y Xiang, Yue Rong, Iynkaran Natgunanathan, Song GuoAbstract:Audio watermarking is a promising technology for copyright protection of audio data. Built upon the concept of spread spectrum (SS), many SS-based audio watermarking methods have been developed, where a pseudonoise (PN) sequence is usually used to introduce security. A major drawback of the existing SS-based audio watermarking methods is their low Embedding Capacity. In this paper, we propose a new SS-based audio watermarking method which possesses much higher Embedding Capacity while ensuring satisfactory imperceptibility and robustness. The high Embedding Capacity is achieved through a set of mechanisms: Embedding multiple watermark bits in one audio segment, reducing host signal interference on watermark extraction, and adaptively adjusting PN sequence amplitude in watermark Embedding based on the property of audio segments. The effectiveness of the proposed audio watermarking method is demonstrated by simulation examples.
Y Xiang - One of the best experts on this subject based on the ideXlab platform.
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A high Embedding Capacity image watermarking method with rank-based embedder and decoder
2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA), 2016Co-Authors: Tianrui Zong, Y Xiang, Peng Chen, Saeid Nahavandi, Gleb BeliakovAbstract:High Embedding Capacity is desired in digital image watermarking. In this paper, we propose a novel rank-based image watermarking method to achieve high Embedding Capacity. We first divide the host image into blocks. Then the 2-D discrete cosine transform (DCT) and zigzag scanning is used to construct the coefficient sets with a secret key. After that, the DCT coefficient sets are modified using a rank-based Embedding strategy to insert the watermark bits. A buffer is also introduced during the Embedding phase to enhance the robustness. At the decoding step, the watermark bits are extracted by checking the ranks of the detection matrices. The proposed method is host signal interference (HSI) free, invariant to amplitude scaling and constant luminance change, and robust against other common signal processing attacks. Experimental results demonstrate the effectiveness of the proposed method.
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Robustness and Embedding Capacity enhancement in time-spread echo-based audio watermarking
2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA), 2016Co-Authors: Iynkaran Natgunanathan, Y Xiang, Lei Pan, Peng Chen, Dezhong PengAbstract:In echo-based audio watermarking methods, poor robustness and low Embedding Capacity are the main problems. In this paper, we propose a novel time-spread echo method for audio watermarking, aiming to improve the robustness and the Embedding Capacity. To improve the robustness, we design an efficient pseudonoise (PN) sequence and a corresponding decoding function. Compared to the conventional PN sequence used in time-spread echo hiding based method, more large peaks are produced during the autocorrelation of the proposed PN sequence. Our decoding function is designed to utilize these peaks to improve the robustness. To enhance the Embedding Capacity, multiple watermark bits are embedded into one audio segment. This is achieved by varying the delays of added echo signals. Moreover, the security of the proposed method is further improved by scrambling the watermarks at the Embedding stage. Compared with the conventional time-spread echo-based method, the proposed method is more robust to conventional attacks and has higher Embedding Capacity. The effectiveness of our method is illustrated by simulation results.
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Rank-Based Image Watermarking Method With High Embedding Capacity and Robustness
IEEE Access, 2016Co-Authors: Tianrui Zong, Song Guo, Y Xiang, Yue RongAbstract:This paper presents a novel rank-based method for image watermarking. In the watermark Embedding process, the host image is divided into blocks, followed by the 2-D discrete cosine transform (DCT). For each image block, a secret key is employed to randomly select a set of DCT coefficients suitable for watermark Embedding. Watermark bits are inserted into an image block by modifying the set of DCT coefficients using a rank-based Embedding rule. In the watermark detection process, the corresponding detection matrices are formed from the received image using the secret key. Afterward, the watermark bits are extracted by checking the ranks of the detection matrices. Since the proposed watermarking method only uses two DCT coefficients to hide one watermark bit, it can achieve very high Embedding Capacity. Moreover, our method is free of host signal interference. This desired feature and the usage of an error buffer in watermark Embedding result in high robustness against attacks. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method.
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Spread spectrum-based high Embedding Capacity watermarking method for audio signals
IEEE Transactions on Audio Speech and Language Processing, 2015Co-Authors: Y Xiang, Yue Rong, Iynkaran Natgunanathan, Song GuoAbstract:Audio watermarking is a promising technology for copyright protection of audio data. Built upon the concept of spread spectrum (SS), many SS-based audio watermarking methods have been developed, where a pseudonoise (PN) sequence is usually used to introduce security. A major drawback of the existing SS-based audio watermarking methods is their low Embedding Capacity. In this paper, we propose a new SS-based audio watermarking method which possesses much higher Embedding Capacity while ensuring satisfactory imperceptibility and robustness. The high Embedding Capacity is achieved through a set of mechanisms: Embedding multiple watermark bits in one audio segment, reducing host signal interference on watermark extraction, and adaptively adjusting PN sequence amplitude in watermark Embedding based on the property of audio segments. The effectiveness of the proposed audio watermarking method is demonstrated by simulation examples.
Yue Rong - One of the best experts on this subject based on the ideXlab platform.
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Rank-Based Image Watermarking Method With High Embedding Capacity and Robustness
IEEE Access, 2016Co-Authors: Tianrui Zong, Song Guo, Y Xiang, Yue RongAbstract:This paper presents a novel rank-based method for image watermarking. In the watermark Embedding process, the host image is divided into blocks, followed by the 2-D discrete cosine transform (DCT). For each image block, a secret key is employed to randomly select a set of DCT coefficients suitable for watermark Embedding. Watermark bits are inserted into an image block by modifying the set of DCT coefficients using a rank-based Embedding rule. In the watermark detection process, the corresponding detection matrices are formed from the received image using the secret key. Afterward, the watermark bits are extracted by checking the ranks of the detection matrices. Since the proposed watermarking method only uses two DCT coefficients to hide one watermark bit, it can achieve very high Embedding Capacity. Moreover, our method is free of host signal interference. This desired feature and the usage of an error buffer in watermark Embedding result in high robustness against attacks. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method.
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Spread spectrum-based high Embedding Capacity watermarking method for audio signals
IEEE Transactions on Audio Speech and Language Processing, 2015Co-Authors: Y Xiang, Yue Rong, Iynkaran Natgunanathan, Song GuoAbstract:Audio watermarking is a promising technology for copyright protection of audio data. Built upon the concept of spread spectrum (SS), many SS-based audio watermarking methods have been developed, where a pseudonoise (PN) sequence is usually used to introduce security. A major drawback of the existing SS-based audio watermarking methods is their low Embedding Capacity. In this paper, we propose a new SS-based audio watermarking method which possesses much higher Embedding Capacity while ensuring satisfactory imperceptibility and robustness. The high Embedding Capacity is achieved through a set of mechanisms: Embedding multiple watermark bits in one audio segment, reducing host signal interference on watermark extraction, and adaptively adjusting PN sequence amplitude in watermark Embedding based on the property of audio segments. The effectiveness of the proposed audio watermarking method is demonstrated by simulation examples.
Lang Tong - One of the best experts on this subject based on the ideXlab platform.
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the Embedding Capacity of information flows under renewal traffic
IEEE Transactions on Information Theory, 2013Co-Authors: Stefano Marano, Vincenzo Matta, Lang TongAbstract:Given two independent point processes and a certain rule for matching points between them, what is the fraction of matched points over infinitely long streams? In many application contexts, e.g., secure networking, a meaningful matching rule is that of a maximum causal delay, and the problem is related to Embedding a flow of packets in cover traffic such that no timing analysis can detect it. We study the best undetectable Embedding policy and the corresponding maximum flow rate-that we call the Embedding Capacity-under the assumption that the cover traffic can be modeled as an arbitrary renewal process. We find that computing the Embedding Capacity requires the inversion of a very structured linear system that, for a broad range of renewal models encountered in practice, admits a fully analytical expression in terms of the renewal function of the processes. This result enables us to explore the properties of the Embedding Capacity, obtaining closed-form solutions for selected distribution families and a suite of sufficient conditions on the Capacity ordering. We test our solution on real network traces, which shows a remarkable match for tight delay constraints. A gap between the predicted and the actual Embedding capacities appears for looser constraints, and further investigation reveals that it is caused by inaccuracy of the renewal traffic model rather than of the solution itself.
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The Embedding Capacity of Information Flows Under Renewal Traffic
IEEE Transactions on Information Theory, 2013Co-Authors: Stefano Marano, Vincenzo Matta, Lang TongAbstract:Given two independent point processes and a certain rule for matching points between them, what is the fraction of matched points over infinitely long streams? In many application contexts, e.g., secure networking, a meaningful matching rule is that of a maximum causal delay, and the problem is related to Embedding a flow of packets in cover traffic such that no traffic analysis can detect it. We study the best undetectable Embedding policy and the corresponding maximum flow rate ---that we call the Embedding Capacity--- under the assumption that the cover traffic can be modeled as arbitrary renewal processes. We find that computing the Embedding Capacity requires the inversion of very structured linear systems that, for a broad range of renewal models encountered in practice, admits a fully analytical expression in terms of the renewal function of the processes. Our main theoretical contribution is a simple closed form of such relationship. This result enables us to explore properties of the Embedding Capacity, obtaining closed-form solutions for selected distribution families and a suite of sufficient conditions on the Capacity ordering. We evaluate our solution on real network traces, which shows a noticeable match for tight delay constraints. A gap between the predicted and the actual Embedding capacities appears for looser constraints, and further investigation reveals that it is caused by inaccuracy of the renewal traffic model rather than of the solution itself.
