<![CDATA[The rapid advancement of artificial intelligence has enabled the creation of highly convincing hoax information, posing serious challenges to information integrity and public trust. This study aims to understand the characteristics of AI-generated hoaxes and propose effective strategies to detect and mitigate their impact. A mixed-method framework was adopted, combining content analysis of AI-generated texts to identify patterns, vulnerabilities, and intervention points, with machine learning techniques for detection and social analysis to capture human and policy dimensions. Validation of the framework demonstrated improved detection accuracy, reduced misinformation reach, and stronger user resilience when supported by transparency measures and digital literacy efforts. The study contributes by offering a structured detection–response cycle that integrates technical, social, and policy approaches. This framework provides governments, organizations, and individuals with practical tools to anticipate and respond to the risks of AI-driven misinformation, ultimately strengthening digital resilience.]]>
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