区块链技术对使用Deepfake分析仪保护图像和视频完整性的影响

Jefferson A. Costales, Shikhar Shiromani, M. Devaraj
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引用次数: 1

摘要

深度造假是一个严重威胁视觉媒体真实性和完整性的问题。虽然计算机视觉和模式识别在以前的研究中已经被采用,但在允许使用的层数上存在限制。为了解决这个问题,本文提出了一种基于去中心化区块链的策略来创建一个安全可靠的系统,该系统可以确定内容的真实性。追踪原始视频,保护媒体完整性免受身份盗窃。该方法采用区块链、加密、媒体过滤等技术,采用卷积神经网络、共识算法和SHA-256哈希算法来保证媒体的保护和完整性。此外,建议使用Deepfake分析仪来增强介质保护。通过利用GitHub上的可用数据集来评估所提出方法的有效性,并对结果进行了广泛的检查。这项研究为如何利用区块链技术来保护图像、视频的完整性以及减少媒体中错误信息的传播提供了有价值的视角。提议的Deepfake分析器增加了额外的保护层,确保视频和图像的完整性,防止身份盗窃。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Impact of Blockchain Technology to Protect Image and Video Integrity from Identity Theft using Deepfake Analyzer
Deepfake is a critical problem that poses a significant threat to the authenticity and integrity of visual media. Although computer vision and pattern recognition have been employed in previous studies, there exist limitations on the quantity of layers that are permissible for use. This article proposes a strategy based on decentralized blockchain to create a secure and reliable system that can determine the authenticity of content in order to tackle this problem. tracing the original video, and safeguarding media integrity from identity theft. The proposed approach employs a combination of technologies including Blockchain, the encryption, media filtering, The proposed approach utilizes the The Convolutional Neural Network, Consensus Algorithm, and SHA-256 Hashing Algorithm are employed to ensure the protection and integrity of the media. Additionally, the implementation of a Deepfake Analyzer is recommended to augment media protection. The proposed method's efficacy is assessed by utilizing an available dataset from GitHub, and the outcomes are extensively examined. This research offers valuable perspectives on how blockchain technology can be leveraged to safeguard the integrity of images, videos, and reduce the spread of misinformation in the media. The proposed Deepfake Analyzer adds an additional layer of protection, ensuring video and image integrity against identity theft.
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