Steganography Research Landscape: A Brief Century-long Bibliometric Study

This study presents a century-long bibliometric review of steganography based on 8,241 articles and 49,572 citation links. Using direct citation analysis, we mapped the field’s intellectual landscape and identified nine major clusters, ranging from classical image-based methods and foundational theory to audio, text, reversible, video-based techniques, and emerging AI-driven paradigms such as deep learning and GANs. Temporal mapping reveals a shift from foundational principles to AI-enabled and quantum informed approaches, while geographic analysis highlights China’s leading role, followed by India and the United States. The review also identifies critical gaps in unified security frameworks, evaluation metrics, and human factors, and outlines future opportunities in quantum steganography, blockchain, coverless methods, and application-driven domains.