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277 results on '"Wang, Rangding"'

1. Universal Defensive Underpainting Patch: Making Your Text Invisible to Optical Character Recognition

Author

Deng, JiaCheng, Dong, Li, Chen, Jiahao, Yan, Diqun, Wang, Rangding, Ye, Dengpan, Zhao, Lingchen, and Tian, Jinyu

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Optical Character Recognition (OCR) enables automatic text extraction from scanned or digitized text images, but it also makes it easy to pirate valuable or sensitive text from these images. Previous methods to prevent OCR piracy by distorting characters in text images are impractical in real-world scenarios, as pirates can capture arbitrary portions of the text images, rendering the defenses ineffective. In this work, we propose a novel and effective defense mechanism termed the Universal Defensive Underpainting Patch (UDUP) that modifies the underpainting of text images instead of the characters. UDUP is created through an iterative optimization process to craft a small, fixed-size defensive patch that can generate non-overlapping underpainting for text images of any size. Experimental results show that UDUP effectively defends against unauthorized OCR under the setting of any screenshot range or complex image background. It is agnostic to the content, size, colors, and languages of characters, and is robust to typical image operations such as scaling and compressing. In addition, the transferability of UDUP is demonstrated by evading several off-the-shelf OCRs. The code is available at https://github.com/QRICKDD/UDUP.

Published
2023
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3. Detecting and Recovering Adversarial Examples from Extracting Non-robust and Highly Predictive Adversarial Perturbations

Author

Dong, Mingyu, Chen, Jiahao, Yan, Diqun, Gao, Jingxing, Dong, Li, and Wang, Rangding

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Deep neural networks (DNNs) have been shown to be vulnerable against adversarial examples (AEs) which are maliciously designed to fool target models. The normal examples (NEs) added with imperceptible adversarial perturbation, can be a security threat to DNNs. Although the existing AEs detection methods have achieved a high accuracy, they failed to exploit the information of the AEs detected. Thus, based on high-dimension perturbation extraction, we propose a model-free AEs detection method, the whole process of which is free from querying the victim model. Research shows that DNNs are sensitive to the high-dimension features. The adversarial perturbation hiding in the adversarial example belongs to the high-dimension feature which is highly predictive and non-robust. DNNs learn more details from high-dimension data than others. In our method, the perturbation extractor can extract the adversarial perturbation from AEs as high-dimension feature, then the trained AEs discriminator determines whether the input is an AE. Experimental results show that the proposed method can not only detect the adversarial examples with high accuracy, but also detect the specific category of the AEs. Meanwhile, the extracted perturbation can be used to recover the AEs to NEs., Comment: 10 pages

Published
2022

4. Adversarial Privacy Protection on Speech Enhancement

Author

Dong, Mingyu, Yan, Diqun, and Wang, Rangding

Subjects
Computer Science - Sound, Computer Science - Cryptography and Security, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Speech is easily leaked imperceptibly, such as being recorded by mobile phones in different situations. Private content in speech may be maliciously extracted through speech enhancement technology. Speech enhancement technology has developed rapidly along with deep neural networks (DNNs), but adversarial examples can cause DNNs to fail. In this work, we propose an adversarial method to degrade speech enhancement systems. Experimental results show that generated adversarial examples can erase most content information in original examples or replace it with target speech content through speech enhancement. The word error rate (WER) between an enhanced original example and enhanced adversarial example recognition result can reach 89.0%. WER of target attack between enhanced adversarial example and target example is low to 33.75% . Adversarial perturbation can bring the rate of change to the original example to more than 1.4430. This work can prevent the malicious extraction of speech., Comment: 5 pages, 6 figures

Published
2022

5. Transferability of Adversarial Attacks on Synthetic Speech Detection

Author

Deng, Jiacheng, Chen, Shunyi, Dong, Li, Yan, Diqun, and Wang, Rangding

Subjects
Computer Science - Sound, Computer Science - Cryptography and Security, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Synthetic speech detection is one of the most important research problems in audio security. Meanwhile, deep neural networks are vulnerable to adversarial attacks. Therefore, we establish a comprehensive benchmark to evaluate the transferability of adversarial attacks on the synthetic speech detection task. Specifically, we attempt to investigate: 1) The transferability of adversarial attacks between different features. 2) The influence of varying extraction hyperparameters of features on the transferability of adversarial attacks. 3) The effect of clipping or self-padding operation on the transferability of adversarial attacks. By performing these analyses, we summarise the weaknesses of synthetic speech detectors and the transferability behaviours of adversarial attacks, which provide insights for future research. More details can be found at https://gitee.com/djc_QRICK/Attack-Transferability-On-Synthetic-Detection., Comment: 5 pages, submit to Interspeech2022

Published
2022

6. Adversarial Example Devastation and Detection on Speech Recognition System by Adding Random Noise

Author

Dong, Mingyu, Yan, Diqun, Gong, Yongkang, and Wang, Rangding

Subjects
Computer Science - Sound, Computer Science - Cryptography and Security, Computer Science - Multimedia, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

An automatic speech recognition (ASR) system based on a deep neural network is vulnerable to attack by an adversarial example, especially if the command-dependent ASR fails. A defense method against adversarial examples is proposed to improve the robustness and security of the ASR system. We propose an algorithm of devastation and detection on adversarial examples that can attack current advanced ASR systems. We choose an advanced text- and command-dependent ASR system as our target, generating adversarial examples by an optimization-based attack on text-dependent ASR and the GA-based algorithm on command-dependent ASR. The method is based on input transformation of adversarial examples. Different random intensities and kinds of noise are added to adversarial examples to devastate the perturbation previously added to normal examples. Experimental results show that the method performs well. For the devastation of examples, the original speech similarity after adding noise can reach 99.68%, the similarity of adversarial examples can reach zero, and the detection rate of adversarial examples can reach 94%., Comment: 20 pages, 5 figures, Submitted to Computer Speech and Language

Published
2021

8. Physical Anti-copying Semi-robust Random Watermarking for QR Code

Author

Chen, Jiale, Dong, Li, Wang, Rangding, Yan, Diqun, Sun, Weiwei, Fan, Hang-Yu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Zhao, Xianfeng, editor, Tang, Zhenjun, editor, Comesaña-Alfaro, Pedro, editor, and Piva, Alessandro, editor

Published
2023
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9. High-Capacity Adaptive Steganography Based on Transform Coefficient for HEVC

Author

Yang, Lin, Wang, Rangding, Xu, Dawen, Dong, Li, He, Songhan, Liu, Fan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Zhao, Xianfeng, editor, Tang, Zhenjun, editor, Comesaña-Alfaro, Pedro, editor, and Piva, Alessandro, editor

Published
2023
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13. Efficient Generation of Speech Adversarial Examples with Generative Model

Author

Wang, Donghua, Wang, Rangding, Dong, Li, Yan, Diqun, Ren, Yiming, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Zhao, Xianfeng, editor, Shi, Yun-Qing, editor, Piva, Alessandro, editor, and Kim, Hyoung Joong, editor

Published
2021
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17. Detection of Operation Type and Order for Digital Speech

Author

Wu, Tingting, Yan, Diqun, Xiang, Li, Wang, Rangding, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Li, Haifeng, editor, Li, Shengchen, editor, Ma, Lin, editor, Fang, Chunying, editor, and Zhu, Yidan, editor

Published
2020
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18. A Replay Speech Detection Algorithm Based on Sub-band Analysis

Author

Lin, Lang, Wang, Rangding, Diqun, Yan, Rannenberg, Kai, Editor-in-Chief, Sakarovitch, Jacques, Series Editor, Goedicke, Michael, Series Editor, Tatnall, Arthur, Series Editor, Neuhold, Erich J., Series Editor, Pras, Aiko, Series Editor, Tröltzsch, Fredi, Series Editor, Pries-Heje, Jan, Series Editor, Whitehouse, Diane, Series Editor, Reis, Ricardo, Series Editor, Furnell, Steven, Series Editor, Furbach, Ulrich, Series Editor, Winckler, Marco, Series Editor, Rauterberg, Matthias, Series Editor, Shi, Zhongzhi, editor, Mercier-Laurent, Eunika, editor, and Li, Jiuyong, editor

Published
2018
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19. AAC Audio Compression Detection Based on QMDCT Coefficient

Author

Huang, Qijuan, Wang, Rangding, Yan, Diqun, Zhang, Jian, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Sun, Xingming, editor, Pan, Zhaoqing, editor, and Bertino, Elisa, editor

Published
2018
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20. A Replay Voice Detection Algorithm Based on Multi-feature Fusion

Author

Lin, Lang, Wang, Rangding, Yan, Diqun, Li, Can, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Sun, Xingming, editor, Pan, Zhaoqing, editor, and Bertino, Elisa, editor

Published
2018
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25. Two-Dimensional Histogram Modification for Reversible Data Hiding in Partially Encrypted H.264/AVC Videos

Author

Xu, Dawen, Zhu, Yani, Wang, Rangding, Fu, Jianjing, Chen, Kai, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shi, Yun Qing, editor, Kim, Hyoung Joong, editor, Perez-Gonzalez, Fernando, editor, and Liu, Feng, editor

Published
2017
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26. Source Cell-Phone Identification Using Spectral Features of Device Self-noise

Author

Jin, Chao, Wang, Rangding, Yan, Diqun, Tao, Biaoli, Chen, Yanan, Pei, Anshan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shi, Yun Qing, editor, Kim, Hyoung Joong, editor, Perez-Gonzalez, Fernando, editor, and Liu, Feng, editor

Published
2017
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29. Completely Separable Reversible Data Hiding in Encrypted Images

Author

Xu, Dawen, Chen, Kai, Wang, Rangding, Su, Shubing, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shi, Yun-Qing, editor, Kim, Hyoung Joong, editor, Pérez-González, Fernando, editor, and Echizen, Isao, editor

Published
2016
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30. Detection of Double Compression for HEVC Videos Based on the Co-occurrence Matrix of DCT Coefficients

Author

Huang, Meiling, Wang, Rangding, Xu, Jian, Xu, Dawen, Li, Qian, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shi, Yun-Qing, editor, Kim, Hyoung Joong, editor, Pérez-González, Fernando, editor, and Echizen, Isao, editor

Published
2016
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31. Multiple MP3 Compression Detection Based on the Statistical Properties of Scale Factors

Author

Zhou, Jinglei, Wang, Rangding, Jin, Chao, Yan, Diqun, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shi, Yun-Qing, editor, Kim, Hyoung Joong, editor, Pérez-González, Fernando, editor, and Echizen, Isao, editor

Published
2016
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32. Audio Tampering Detection Based on Quantization Artifacts

Author

Tao, Biaoli, Wang, Rangding, Yan, Diqun, Jin, Chao, Chen, Yanan, Zhang, Li, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sun, Xingming, editor, Liu, Alex, editor, Chao, Han-Chieh, editor, and Bertino, Elisa, editor

Published
2016
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33. An Information Hiding Algorithm for HEVC Based on Differences of Intra Prediction Modes

Author

Sheng, Qi, Wang, Rangding, Pei, Anshan, Wang, Bin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sun, Xingming, editor, Liu, Alex, editor, Chao, Han-Chieh, editor, and Bertino, Elisa, editor

Published
2016
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35. Detecting Fake-Quality WAV Audio Based on Phase Differences

Author

Zhou, Jinglei, Wang, Rangding, Jin, Chao, Yan, Diqun, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shi, Yun-Qing, editor, Kim, Hyoung Joong, editor, Pérez-González, Fernando, editor, and Yang, Ching-Nung, editor

Published
2015
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36. Reversible Data Hiding in Encrypted Images Using Interpolation and Histogram Shifting

Author

Xu, Dawen, Wang, Rangding, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shi, Yun-Qing, editor, Kim, Hyoung Joong, editor, Pérez-González, Fernando, editor, and Yang, Ching-Nung, editor

Published
2015
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42. A Huffman Table Index Based Approach to Detect Double MP3 Compression

Author

Ma, Pengfei, Wang, Rangding, Yan, Diqun, Jin, Chao, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shi, Yun Qing, editor, Kim, Hyoung-Joong, editor, and Pérez-González, Fernando, editor

Published
2014
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43. Reversible Data Hiding in Encrypted H.264/AVC Video Streams

Author

Xu, Dawen, Wang, Rangding, Shi, Yun Qing, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shi, Yun Qing, editor, Kim, Hyoung-Joong, editor, and Pérez-González, Fernando, editor

Published
2014
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44. Robust Text Image Tampering Localization via Forgery Traces Enhancement and Multiscale Attention

Author

Dong, Li, Liang, Weipeng, and Wang, Rangding

Abstract

Text images, such as scanned documents, certificates, and chat-box screenshots, are commonly used for multimodal communication. However, the rise of advanced deep image editing tools raises concerns about the authenticity of text images. Unlike natural images, even subtle tampering in text images, like a single character, can substantially alter the semantics. To address this issue, we propose a robust network framework for detecting and localizing text image forgeries. This framework involves forgery traces enhancement and multiscale attention-based forgery localization. Specifically, we introduce a deep module to enhance forgery traces from multiple domains, reducing distraction from the image background and facilitating the forgery localization. An efficient encoder-decoder network is devised by fusing high-level semantics with low-level details using a multiscale attention module. Through joint restoration and multiscale forgery feature learning, even delicately tampered regions can be effectively exposed. To evaluate the framework under real-world distortion scenarios, we create a large-scale dataset featuring various tampering methods and distortions. Experimental results demonstrate that the proposed method outperforms the state-of-the-art methods in terms of both accuracy and robustness, especially for the small tampering regions.

Published
2024
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45. Mixed-Bit Sampling Graphic: When Watermarking Meets Copy Detection Pattern

Author

Chen, Jiale, Dong, Li, Wang, Rangding, Yan, Diqun, and Peng, Chengbin

Abstract

Copy Detection Pattern (CDP) is a high-density random noise-alike image that exhibits a different noise pattern after physical copying, and is thus treated as a promising anti-counterfeiting solution. However, CDP cannot convey any message, and it is often used in combination with additional carriers, such as QR codes. In this letter, we take the first step towards extending CDP with watermarking functionality. Specifically, we devise a scheme called Mixed-bit Sampling Graphic (MSG), which could realize invisible watermarking and anti-counterfeiting simultaneously. Compared with conventional CDP, the noise pattern generation of MSG is controlled by the portions of sampling over two bit templates. We formulate this mixed-bit sampling process as an optimization problem and solve it using a block coordinate descent sampling algorithm. Experimental results validate that the proposed MSG can effectively communicate watermark bits while retaining the anti-counterfeiting capability of CDP.

Published
2024
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