The rapid adoption of Generative Artificial Intelligence (AI), particularly ChatGPT and other large language models, has transformed higher education and raised significant concerns regarding academic integrity. This study aims to analyze global research trends on intervention strategies for maintaining academic integrity in the era of Generative AI through a bibliometric approach. Data were collected from the Scopus database, resulting in 100 publications published between 2021 and 2024. Bibliometric analysis was conducted using VOSviewer to examine publication trends, country contributions, keyword co-occurrence networks, and thematic developments. The findings indicate a substantial increase in scholarly attention following the emergence of Generative AI technologies. Five major thematic clusters were identified: academic integrity and plagiarism prevention, Generative AI integration in higher education, assessment redesign and pedagogical intervention, AI literacy and ethical education, and student behavior and psychological responses. The results reveal a notable shift from detection- and punishment-based approaches toward preventive and educational strategies, including AI literacy programs, authentic assessment redesign, ethics education, and institutional policy development. The study also highlights the growing importance of holistic intervention frameworks that integrate technological adaptation, pedagogical innovation, and ethical awareness. These findings provide a comprehensive overview of the evolving research landscape and offer valuable insights for developing sustainable academic integrity frameworks in higher education.