Aurum: A blockchain based decentralized video streaming platform

Sathish, Sailesh; Patankar, Anish Anil; Khanna, Harshit

doi:10.1109/wcnc.2019.8886050

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…In Ref. [25], the authors use machine learning to monitor data transactions and analyze correlations in video content through text and speech analysis. Neural networks are used in Ref.…”

Section: Blockchain Technology Applied In Streaming Platformsmentioning

confidence: 99%

Towards a New Business Model for Streaming Platforms Using Blockchain Technology

Soares,

Araújo

2024

Future Internet

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Streaming platforms have revolutionized the digital entertainment industry, but challenges and research opportunities remain to be addressed. One current concern is the lack of transparency in the business model of video streaming platforms, which makes it difficult for content creators to access viewing metrics and receive payments without the intermediary of third parties. Additionally, there is no way to trace payment transactions. This article presents a computational architecture based on blockchain technology to enable transparency in audience management and payments in video streaming platforms. Smart contracts will define the business rules of the streaming services, while middleware will integrate the metadata of the streaming platforms with the proposed computational solution. The proposed solution has been validated through data transactions on different blockchain networks and interviews with content creators from video streaming platforms. The results confirm the viability of the proposed solution in enhancing transparency and auditability in the realm of audience control services and payments on video streaming platforms.

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“…In Ref. [25], the authors use machine learning to monitor data transactions and analyze correlations in video content through text and speech analysis. Neural networks are used in Ref.…”

Section: Blockchain Technology Applied In Streaming Platformsmentioning

confidence: 99%

Towards a New Business Model for Streaming Platforms Using Blockchain Technology

Soares,

Araújo

2024

Future Internet

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“…The integrity verification method (IVM) applied by Ghimire, et al in the blockchain platform shows that blockchain brings a new transparent and community-oriented approach to content verification in the digital age. In addition, Sathish, et al developed Aurum [29], a new multimedia streaming platform that hosts user-generated channels with authenticated content through the use of a blockchain-driven creative process. The platform requires public content verification and the goal of community-driven development in which the research paper also mentions that the Aurum system uses effective support protocols to ensure QoS.…”

Section: Related Workmentioning

confidence: 99%

Towards an YouTube Verified Content System based on Blockchain Approach

Trong¹,

Vo²,

Huong³

et al. 2022

IJACSA

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YouTube connects people with each other through an online video sharing service platform. With the great development of the entertainment industry, content on YouTube is accessible to many people of different ages. However, verifying the content posted on YouTube is clean or not is a difficult problem. Dirty content is violent, pornographic and vulgar content that causes serious psychological harm to the segment of users under the age of 18, i.e., especially those of an age who are not yet aware of the harmful effects of content. Toxic will bring to the child's behavior. Agree that Google (i.e., YouTube) has developed a YouTube Kid application where the videos are only for children under the age of 13. However, cultural and educational differences between regions strongly influence the choice of children. Select content for children. Therefore, the content restrictions on the YouTube Kid application have not yet met all the requirements of parents around the world. There have been many development directions to identify videos containing malicious content based on deep learning. However, there is no method to build a tool to support parents of children to share and identify videos with objectionable content (e.g., violence, pornography, obscene words) on the YouTube platform. In this research paper, we introduce YVC, a YouTube-verified content platform by applying blockchain's distributed, public validation. This tool helps parents validate YouTube content and issue a report to reduce dirty content on YouTube. To demonstrate the effectiveness of our approach, we implement the proof-of-concept in the three most popular EVM platforms: Ethereum, Fantom, and the Binance smart chain. Compared to the YouTube Kids (i.e., the most common shared video platform for the under 13-year-old kid), our approach is able to capture the video preferences of the parents covering the difference areas/countries.

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“…Hashing video footage has been particularly useful in ensuring integrity for applications related to surveillance, sharing, evidence gathering, and video processing. Additionally, attention has been given to the secure exchange of medical images and the application of distributed learning for medical data sharing, simplifying the sharing of CT and X-ray images through blockchain transactions(Seo and Cho, 2020).Innovations like distributed video transcoding have improved video streaming applications by reducing computational costs and enabling distributed storage(Sathish et al, 2019;Chen et al, 2017;Cheng et al, 2012). Challenges in public blockchains, such as limited block sizes, have led to investigations into techniques like video hashing with merkle hash and other hashing algorithms to handle large amounts of data.…”

mentioning

confidence: 99%

Design and Implementation of Blockchain-Enabled Immutability Mechanism for Enhanced Machine Visual Data Integrity

Umar,

Jatoi,

Abid

et al. 2024

Preprint

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In the realm of Machine Vision, the progress in cinematography and image processing has empowered computers to comprehend images and videos. Cameras and infrared (IR) technology have become nearly omnipresent, facilitating the acquisition of crucial information about individuals and their surroundings. They are applied across various sectors, including high-security access, biometric cards, and modern surveillance systems embedded in the Internet of Things (IoT) ecosystem. However, an issue arises with the surge in information and its dissemination, raising concerns regarding safety, confidentiality, and secure storage as these systems interact with others, potentially leading to problems. To tackle these challenges, experts in computer vision are exploring the integration of blockchain technology. This article presents an overview of blockchain applications in computer vision, encompassing biometrics, video surveillance, and the sharing of image and video data. The objective is to demonstrate how blockchain could augment the safety, privacy, and reliability of these applications. The paper also delves into the tools and methodologies contributing to these goals, shedding light on prospective developments. Essentially, this review seeks to furnish clear insights into the collaboration between blockchain and computer vision. It achieves this by examining the latest advancements, existing challenges, and opportunities for leveraging visual data in a blockchain-driven environment. Ultimately, the focus is on understanding how these technologies can harmonize to influence the future landscape of Machine Vision.

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Aurum: A blockchain based decentralized video streaming platform

Cited by 7 publications

References 11 publications

Towards a New Business Model for Streaming Platforms Using Blockchain Technology

Towards a New Business Model for Streaming Platforms Using Blockchain Technology

Towards an YouTube Verified Content System based on Blockchain Approach

Design and Implementation of Blockchain-Enabled Immutability Mechanism for Enhanced Machine Visual Data Integrity

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