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@article{204037,
        author = {Tanisha Suresh Parmar},
        title = {AI Based digital authenticity verification system},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {1069-1071},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204037},
        abstract = {In today’s digital era, the rapid spread of online content has increased the risk of misinformation, deepfakes, and fraudulent digital activities. The AI-Based Digital Authenticity Verification System is developed to detect and verify the authenticity of various types of digital data, including images, videos, documents, URLs, and applications. This system uses techniques from Artificial Intelligence and Machine Learning to analyze patterns, identify anomalies, and classify content as genuine or fake. The proposed system incorporates multiple modules such as deepfake detection, metadata analysis, document verification, and URL safety checking. By applying advanced models based on Deep Learning, the system can effectively detect manipulated media and suspicious digital behavior. It also provides real-time results through a user-friendly interface, enabling users to quickly verify the credibility of content. The primary goal of this project is to enhance digital trust and minimize cyber threats by providing an automated and reliable verification mechanism. This system can be widely used in domains like social media, e-commerce, education, and cybersecurity, contributing to a safer and more trustworthy digital environment.},
        keywords = {It primarily uses Artificial Intelligence and Machine Learning to analyze data patterns and automatically distinguish between genuine and fake content. Advanced techniques from Deep Learning are applied to process complex data such as images, videos, and audio, enabling effective deepfake detection. The system focuses on digital authenticity verification by validating documents, URLs, and multimedia content through methods like metadata analysis and anomaly detection. It also includes URL and website verification to identify phishing or malicious links. With real-time processing capabilities, the system delivers quick and accurate results, helping users make informed decisions and enhancing overall cybersecurity and digital trust.},
        month = {June},
        }