ARCHANGEL: Tamper-proofing Video Archives using Temporal Content Hashes on the Blockchain

We present ARCHANGEL; a novel distributed ledger based system for assuring the long-term integrity of digital video archives. First, we describe a novel deep network architecture for computing compact temporal content hashes (TCHs) from audio-visual streams with durations of minutes or hours. Our TCHs are sensitive to accidental or malicious content modification (tampering) but invariant to the codec used to encode the video. 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, Estonia and Norway participated.Comment: Accepted to CVPR Blockchain Workshop 201

Web-based real-time communication based collaboration: An evaluation study of the DataChannel

Real-time communication evolved from the traditional telephony network to Internet-based audio/video conferencing tools and instant messaging software. Third-party plug-ins and extensions added the same capabilities to Web-based browser applications. Vendor-specific heterogeneity in software and hardware requirements brought up interoperability issues. There were no common set of communication protocols. The Web browser as a universal access point to the Web was facing a challenge in real-time communication. To natively support real-time communication in the Web browser, Web-based Real-Time Communication (WebRTC) was introduced. It provides three main features i.e. access to the user's hardware, peer-to-peer connection between the browsers and arbitrary data exchange through its DataChannel application programming interface (API). These features are added in the browser as one extra protocol stack that can be accessed by a Web application with JavaScript API's. The DataChannel API provides several use cases and it is interesting to examine the behavior of the WebRTC DataChannel from the point of view of developers, enterprises, Web services and service providers. In this thesis we investigate the WebRTC DataChannel API. We design and implement two prototypes of a WebRTC based collaboration application. These were based on the respective specification by the Google Chrome and Mozilla Firefox browsers. A case study is proposed for data communication between two collaborative environments one consisting of an enterprise tool and the other being a non-enterprise tool based on WebRTC DataChannel and IP Multimedia Subsystem. The performance evaluation of the implementation is also carried out by comparing various other tools in a controlled environment

ARCHANGEL: Tamper-Proofing Video Archives Using Temporal Content Hashes on the Blockchain

We present ARCHANGEL; a novel distributed ledger based system for assuring the long-term integrity of digital video archives. First, we describe a novel deep network architecture for computing compact temporal content hashes (TCHs) from audio-visual streams with durations of minutes or hours. Our TCHs are sensitive to accidental or malicious content modification (tampering) but invariant to the codec used to encode the video. 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, Estonia and Norway participated

Tamper-proofing Video with Hierarchical Attention Autoencoder Hashing on Blockchain

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 hourlong 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