555 research outputs found

    Exploration of media blockchain technologies for JPEG privacy and security

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    Privacy and security, copyright violations and fake news are emerging challenges in digital media. Social media and data leaks increase risk of user privacy. Creative media particularly images are often susceptible to copyright violations which poses a serious problem to the industry. On the other hand, doctored images using photo editing tools and computer generated images may give a false impression of reality and add to the problem of fake news. These problems demand solutions to protect images and associated metadata as well as methods that can proof the integrity of digital media. For these reasons, the JPEG standardization committee has been working on a new Privacy and Security standard that provides solutions to support privacy and security focused workflows. The standard defines tools to support protection and integrity across the wide range of JPEG image standards. Related to image integrity, blockchain technology provides a solution for creating tamper proof distributed ledgers. However, adopting blockchain technology for digital image integrity poses several challenges at the technology level as well as at the level of privacy legislation. In addition, if blockchain technology is adopted to support media applications, it needs to be closely integrated with a widely adopted standard to ensure broad interoperability. Therefore, the JPEG committee initiated an activity to explore standardization needs related to media blockchain and distributed ledger technologies (DLT). This paper explains the scope and implementation of the JPEG Privacy and Security standard and presents the current state of the exploration on standardization needs related to media blockchain applications

    Blockchain for Healthcare: Securing Patient Data and Enabling Trusted Artificial Intelligence

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    Advances in information technology are digitizing the healthcare domain with the aim of improved medical services, diagnostics, continuous monitoring using wearables, etc., at reduced costs. This digitization improves the ease of computation, storage and access of medical records which enables better treatment experiences for patients. However, it comes with a risk of cyber attacks and security and privacy concerns on this digital data. In this work, we propose a Blockchain based solution for healthcare records to address the security and privacy concerns which are currently not present in existing e-Health systems. This work also explores the potential of building trusted Artificial Intelligence models over Blockchain in e-Health, where a transparent platform for consent-based data sharing is designed. Provenance of the consent of individuals and traceability of data sources used for building and training the AI model is captured in an immutable distributed data store. The audit trail of the data access captured using Blockchain provides the data owner to understand the exposure of the data. It also helps the user to understand the revenue models that could be built on top of this framework for commercial data sharing to build trusted AI models

    FrameProv: Towards End-To-End Video Provenance

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    Video feeds are often deliberately used as evidence, as in the case of CCTV footage; but more often than not, the existence of footage of a supposed event is perceived as proof of fact in the eyes of the public at large. This reliance represents a societal vulnerability given the existence of easy-to-use editing tools and means to fabricate entire video feeds using machine learning. And, as the recent barrage of fake news and fake porn videos have shown, this isn't merely an academic concern, it is actively been exploited. I posit that this exploitation is only going to get more insidious. In this position paper, I introduce a long term project that aims to mitigate some of the most egregious forms of manipulation by embedding trustworthy components in the video transmission chain. Unlike earlier works, I am not aiming to do tamper detection or other forms of forensics -- approaches I think are bound to fail in the face of the reality of necessary editing and compression -- instead, the aim here is to provide a way for the video publisher to prove the integrity of the video feed as well as make explicit any edits they may have performed. To do this, I present a novel data structure, a video-edit specification language and supporting infrastructure that provides end-to-end video provenance, from the camera sensor to the viewer. I have implemented a prototype of this system and am in talks with journalists and video editors to discuss the best ways forward with introducing this idea to the mainstream

    Big Data Security (Volume 3)

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    After a short description of the key concepts of big data the book explores on the secrecy and security threats posed especially by cloud based data storage. It delivers conceptual frameworks and models along with case studies of recent technology
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