Developing a Digital Trust Score System to Identify Deepfake Content using AI

Registration ID: IJNRD_325889

Published ID: IJNRD2606043

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Prince S, Dhinaya Berin B.S

Deepfake Detection, Digital Trust Score, Digital Media Authentication, Content Verification, Fake News, Cybersecurity, Information Integrity, Digital Forensics, Multimedia Security, Trust Evaluation System.

The widespread use of digital technologies and social media platforms has significantly increased the creation and sharing of multimedia content across the world. Images, videos, and audio recordings have become important sources of information for individuals, organizations, and governments. However, the emergence of deepfake technology has created serious challenges in verifying the authenticity of digital content. Deepfakes are artificially manipulated images, videos, or audio recordings that appear realistic and can be used to imitate real individuals, alter events, or spread misleading information. The rapid advancement of deepfake generation techniques has made it increasingly difficult for users to distinguish genuine content from manipulated content using visual observation alone. The misuse of deepfake technology has raised concerns in various sectors, including journalism, politics, education, business, and cybersecurity. False information created through deepfakes can damage reputations, influence public opinion, create social unrest, and reduce trust in digital media. Existing detection systems often classify content as either real or fake. While such classification methods are useful, they do not provide sufficient information about the level of authenticity or reliability of the content. Users may require a more detailed assessment to make informed decisions regarding the credibility of digital media. This research proposes a Digital Trust Score System for the detection and evaluation of deepfake content. The proposed system analyzes multiple characteristics of digital media, including facial expressions, eye movements, image consistency, visual artifacts, frame irregularities, and metadata information. Based on the results of this analysis, the system generates a numerical trust score that represents the likelihood of the content being authentic. A higher trust score indicates greater confidence in the originality and reliability of the content, while a lower score suggests a higher probability of manipulation. The primary objective of this study is to develop a framework that not only detects deepfake content but also provides a transparent and user-friendly method for evaluating digital authenticity. By presenting a trust score rather than a simple binary classification, the system enables users to better understand the credibility of the content they encounter online. The framework can be integrated into social media platforms, news verification systems, digital forensic applications, and content moderation tools to support the identification of misleading or manipulated media. The proposed Digital Trust Score System is expected to enhance digital media verification, reduce the spread of misinformation, and strengthen public confidence in online information sources. Furthermore, it can contribute to improving cybersecurity practices and promoting responsible digital communication. As deepfake technologies continue to evolve, the development of reliable authenticity assessment systems will become increasingly important in maintaining trust, transparency, and security within the digital ecosystem.

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Prince S & Dhinaya Berin B.S (June-2026). Developing a Digital Trust Score System to Identify Deepfake Content using AI. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(6), a349-a359. https://ijnrd.org/papers/IJNRD2606043.pdf

Volume 11 Issue 6, June-2026

Pages : a349-a359

Paper Reg. ID: IJNRD_325889

Published Paper Id: IJNRD2606043

Research Area: Other area not in list

Author Type: Indian Author

Country: kannikumari, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2606043.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2606043

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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