Adaptive honeypots: Dynamic deception tactics in modern cyber defense

Honeypots have long served as essential tools in cybersecurity, drawing attackers into controlled environments to analyze their behavior and gather threat intelligence. However, as adversaries employ increasingly sophisticated and automated attack techniques, traditional static honeypots have become less effective. To counter this, adaptive honeypots introduce dynamic deception strategies, continuously modifying their configurations, capabilities, and responses in real time to maintain authenticity and enhance threat intelligence collection. This paper explores the core principles of adaptive honeypot design, examines dynamic deception architectures, and discusses the challenges and opportunities associated with their deployment in modern cyber defense. Finally, we highlight future research directions, emphasizing AI-driven adaptability and advanced threat correlation to improve detection fidelity and threat intelligence accuracy.