Digital forensics and watermarking 18th International Workshop, IWDW 2019, Chengdu, China, November 2-4, 2019, revised selected papers /: 18th International Workshop, IWDW 2019, Chengdu, China, November 2-4, 2019, revised selected papers. (©2020)

• Record Type: Book
• Further Information: Note: Hongxia Wang, Xianfeng Zhao, Yunqing Shi, Hyoung Joong Kim, Alessandro Piva (eds.).
• Other Names: Wang, Hongxia; Zhao, Xianfeng; Shi, Yunqing; Piva, Alessandro, 1968-; Kim, Hyoung Joong, 1954-; IWDW (Conference), 18th
• Contents: Intro -- Preface -- Organization -- Contents -- Deep Learning for Multimedia Security -- GAN-Based Steganography with the Concatenation of Multiple Feature Maps -- 1 Introduction -- 2 Related Work -- 2.1 ASDL-GAN Model -- 2.2 Yang's Model -- 3 Proposed Scheme Based on Reconstructed GAN -- 3.1 The Overall Introduction of Proposed Scheme -- 3.2 Generator Reconstruction -- 3.3 Discriminator Design -- 3.4 Training of Network -- 3.5 Practical Steganographic Scheme -- 4 Experimental Results and Discussion -- 4.1 Experimental Setup -- 4.2 Steganographic Results 4.3 Testing for Different Concatenations of Feature Maps -- 4.4 Comparison with State-of-the-Arts -- 5 Conclusion -- References -- GAN-TStega: Text Steganography Based on Generative Adversarial Networks -- 1 Introduction -- 2 Related Works -- 2.1 Text Generation-Based Steganography -- 2.2 GANs for Text Generation -- 3 GAN-TStega Model -- 3.1 Generator -- 3.2 Discriminator -- 4 Update Strategy -- 5 Information Hiding and Extraction -- 6 Experiments and Results -- 7 Conclusion -- References -- Optimized CNN with Point-Wise Parametric Rectified Linear Unit for Spatial Image Steganalysis 1 Introduction -- 2 The Proposed Architecture -- 2.1 Architecture Overview -- 2.2 Point-Wise PReLU Activation Function -- 2.3 Feature Fusion -- 3 Experiment -- 3.1 Setup -- 3.2 Results -- 4 Conclusion -- References -- Light Multiscale Conventional Neural Network for MP3 Steganalysis -- 1 Introduction -- 2 Related Work -- 2.1 Multiscale Convolution Structure -- 2.2 Convolution Kernel Factorization -- 2.3 Residual Architecture -- 3 The Architecture of Proposed Network -- 3.1 The Input Data and Preprocessing -- 3.2 The Sub-net Block -- 3.3 The Classifier Part -- 4 Experiment 4.1 Setup of Experiment -- 4.2 The Selection of Sub-net Structure -- 4.3 The Result of Detecting MP3 Steganography in Different Domains -- 4.4 Comparison with Handcraft Features -- 4.5 Comparison with CNN-Based Methods -- 5 Conclusion -- References -- Improving Audio Steganalysis Using Deep Residual Networks -- 1 Introduction -- 2 Proposed Method -- 2.1 WavSResNet Architecture -- 2.2 Convolutional Layers -- 2.3 Activation Function -- 2.4 Pooling Layers -- 2.5 Shortcut Components -- 3 Experimental Setup -- 3.1 Dataset -- 3.2 Training Part -- 3.3 Testing Part -- 3.4 Evaluation Metric 4 Experiments -- 4.1 Experiments on Three Datasets -- 4.2 Comparison with the Variants -- 4.3 Comparison with Previous Methods -- 5 Conclusion -- References -- Cover-Source Mismatch in Deep Spatial Steganalysis -- 1 Introduction -- 2 Related Works -- 2.1 Deep Steganalysis -- 2.2 Deep Domain Adaptation -- 3 Methodology -- 3.1 Analysis of Cover-Source Mismatch in Deep Steganalysis -- 3.2 J-Net for Cover-Source Mismatch in Deep Steganalysis -- 4 Experiment -- 4.1 Experimental Settings -- 4.2 Validation of Cover-Source Mismatch -- 4.3 Texture Complexity Measurement by A-distance
• Publisher Details: Cham : Springer
• Publication Date: 2020
• Copyright Date: 2020
• Extent: 1 online resource (430 p.)
• Subjects: 005.8/24; Data encryption (Computer science) -- Congresses; Digital watermarking -- Congresses; Data encryption (Computer science); Digital watermarking; Electronic books; Conference papers and proceedings
• Languages: English
• ISBNs: 9783030435752
• Related ISBNs: 303043575X
• Notes: Note: Includes bibliographical references and index.
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