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  <titleInfo>
    <title>Digital Forensics and Watermarking</title>
    <subTitle>18 th International Workshop, IWDW 2019, Chengdu,China, november 2-4, 2019 Revised Selected Papers</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Kim, Gwangsu.</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
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  </name>
  <name type="personal">
    <namePart>Kim, Hyoung Joong.</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Piva, Alessandro.</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Shi, Yun-Qing.</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Yoo, Chang D.</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
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    <dateIssued encoding="marc">2019</dateIssued>
    <edition>2020</edition>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
    <extent>1 online resource (XI, 392 pages 167 illustrations, 101 illustrations in color.)</extent>
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  <abstract>This book constitutes the refereed proceedings of the 17th International Workshop on Digital Forensics and Watermarking, IWDW 2018, held on Jeju Island, Korea, in October 2018. The 25 papers presented in this volume were carefully reviewed and selected from 43 submissions. The contributions are covering the following topics: deep neural networks for digital forensics; steganalysis and identification; watermarking; reversible data hiding; steganographic algorithms; identification and security; deep generative models for forgery and its detection. .</abstract>
  <tableOfContents>Deep Neural Networks for Digital Forensics -- Steganalysis and Identification -- Watermarking -- Reversible Data Hiding -- Steganographic Algorithms -- Identification and Security -- Deep Generative Models for Forgery and Its Detection.</tableOfContents>
  <note type="statement of responsibility">edited b h ongxia Wang,Xianfeng Zhao, Yunqing Shi, Hyoung Joong Kim,Alessandro Piva </note>
  <subject authority="lcsh">
    <topic>Artificial intelligence</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Coding theory</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Computer crimes</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Computer security</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Data encryption (Computer science)</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Information theory</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Optical data processing</topic>
  </subject>
  <subject>
    <topic>Cryptology</topic>
  </subject>
  <subject>
    <topic>Artificial Intelligence</topic>
  </subject>
  <subject>
    <topic>Coding and Information Theory</topic>
  </subject>
  <subject>
    <topic>Computer Crime</topic>
  </subject>
  <subject>
    <topic>Image Processing and Computer Vision</topic>
  </subject>
  <subject>
    <topic>Systems and Data Security</topic>
  </subject>
  <classification authority="lcc">QA76.9 .D335 2020</classification>
  <classification authority="ddc" edition="23">005.82</classification>
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      <title>Digital forensics and watermarking</title>
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    <titleInfo>
      <title>Security and Cryptology ; 11378</title>
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  <identifier type="isbn">9783030435745</identifier>
  <identifier type="lccn">2019736118</identifier>
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