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CT-ISG: Trustworthy Media: Blind Passive Media Forensics for Content Integrity Verification

CT-ISG: Trustworthy Media: Blind Passive Media Forensics for Content Integrity Verification
CT-ISG:值得信赖的媒体:用于内容完整性验证的盲目被动媒体取证
批准号:
0716203
负责人:
Shih-Fu Chang
金额:
$35.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-09-01 至 2011-08-31

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Proposal: 0716203Shih-Fu ChangColumbia UniversityCT-ISG: Trustworthy Media: Blind Passive Media Forensics for Content Integrity VerificationAbstract:Digital audio-visual content can nowadays be modified and simulated with unprecedented realism. In response to the challenge of malicious media manipulation, we propose to develop new theories, methods, and a comprehensive suite of tools that can be used to verify content integrity in both audio and visual modalities at multiple levels under diverse contexts. The results will have significant impacts in scientific areas as well as many practical applications of national interest, such as trustworthy news reporting, surveillance security, intelligence gathering, criminal investigation, financial transactions, and medical information management. Our efforts will be based on an important paradigm, called blind passive media forensics, which fundamentally differs from conventional approaches using cryptographic signatures and watermarking. The proposed methods extract latent, unique signatures from the signals and sensing devices to detect tampering anomalies, so that verification requires only the media content at hand without any additional information or preparation. Specifically, we propose a systematic framework for device signature consistency checking and a joint multi-modal approach for verifying media integrity. We will also analyze various attack scenarios, construct rigorous benchmark datasets and performance metrics, and take proactive steps in disseminating results and promoting awareness of this critical area through public testing of online systems.
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ACM Multimedia 2013 Student Travel Grant
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    2009
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CRI: CRD: Collaborative Research: Large Analytics Library and Scalable Concept Ontology for Multimedia Research
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    $28.5万
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    2008
  • 负责人:
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