Transforming Iran’s Judicial System with AI and Blockchain: A Deepfake Detection Framework for Document Authentication

The rapid advancement of Artificial Intelligence (AI) has introduced significant challenges to document authentication in judicial systems, particularly in Iran, where document forgery undermines justice and public trust. This study proposes JudiciaryGuard, an innovative framework that integrates AI-driven deepfake detection with blockchain technology to ensure the authenticity of judicial documents. Utilizing Convolutional Neural Networks (CNNs) for forgery detection with ۹۶ percent accuracy and blockchain for tamper-proof record-keeping, JudiciaryGuard aims to reduce document fraud by ۷۰ percent, potentially impacting thousands of cases annually in Iran. Through a qualitative methodology, this paper explores the synergy of AI and blockchain, identifies the core needs of Iran’s judicial system, addresses legal, technical, and cultural challenges, and proposes tailored solutions such as regulatory sandboxes, offline access mechanisms, and public education initiatives. JudiciaryGuard enhances judicial integrity in Iran while offering a scalable model for other sanctioned economies, fostering a more transparent and equitable legal framework. This research contributes to the global discourse on technology-driven judicial reform, emphasizing practical, context-specific solutions.

کلیدواژه ها:

JudiciaryGuard ، Artificial Intelligence ، Deepfake Detection ، Blockchain ، Document Authentication ، Iran’s Judiciary