Tamper-Proofing Video With Hierarchical Attention Autoencoder Hashing on Blockchain
Tamper-Proofing Video With Hierarchical Attention Autoencoder Hashing on Blockchain
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DOI：
10.1109/tmm.2020.2967640
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发表时间：
2020-01
影响因子：
7.3
通讯作者：
Tu Bui;Daniel Cooper;J. Collomosse;Mark Bell;A. Green;John Sheridan;J. Higgins;Arindra Das
中科院分区：
文献类型：
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作者：
Tu Bui;Daniel Cooper;J. Collomosse;Mark Bell;A. Green;John Sheridan;J. Higgins;Arindra Das
我们介绍了大天使；这是一个新的基于分布式分类账的系统，用于确保数字视频档案的长期完整性。首先，我们介绍了一种新的深层网络体系结构，它使用分层注意力自动编码器(HAAE)从几分钟或一小时长的视听流中计算时间内容哈希(TCH)。我们的TCH对意外或恶意的内容修改(篡改)非常敏感。我们自我监督的HAAE的重点是防止内容修改，如帧截断或损坏，但确保格式转换(即编解码器更改)的不变性。这是必要的，因为档案馆要求档案馆随着时间的推移格式化移动的视频，以确保未来的可访问性。其次，我们描述了如何通过分布在多个独立档案中的权威性区块链来保护TCH(以及用于派生它们的模型)。我们在联合王国、美利坚合众国、爱沙尼亚、澳大利亚和挪威的国家政府档案馆参加的试用范围内报告了大天使的功效。
We present ARCHANGEL; a novel distributed ledger based system for assuring the long-term integrity of digital video archives. First, we introduce a novel deep network architecture using a hierarchical attention autoencoder (HAAE) to compute temporal content hashes (TCHs) from minutes or hour-long audio-visual streams. Our TCHs are sensitive to accidental or malicious content modification (tampering). The focus of our self-supervised HAAE is to guard against content modification such as frame truncation or corruption but ensure invariance against format shift (i.e. codec change). This is necessary due to the curatorial requirement for archives to format shift video over time to ensure future accessibility. Second, we describe how the TCHs (and the models used to derive them) are secured via a proof-of-authority blockchain distributed across multiple independent archives. We report on the efficacy of ARCHANGEL within the context of a trial deployment in which the national government archives of the United Kingdom, United States of America, Estonia, Australia and Norway participated.