An Adaptive Decoy-Based Security Framework Using Dynamic Honeypots and Fake Operating Environment

Traditional cybersecurity systems such as firewalls, antivirus software, and intrusion detection systems are mainly designed to block or detect attacks. However, in today’s digital world, attackers use advanced techniques like ransomware, zero-day exploits, and advanced persistent threats that can bypass these traditional defenses. Honeypots were introduced as decoy systems to attract attackers and study their behavior without harming real systems. Although honeypots are useful, most of them are static and can be easily identified by experienced attackers. In this paper, an Adaptive Decoy-Based Security Framework is proposed that improves traditional honeypot systems by making them dynamic and behavior-based. The proposed system includes a Dynamic Fake Operating Environment (DFOE) that can change operating system fingerprints, services, and system behavior depending on how the attacker interacts with it. A Behavioral Deception Engine is used to analyze attacker activities and generate realistic responses. In addition, a Psychological Delay Mechanism is introduced to intentionally increase the attacker’s time and effort. The main objective of this framework is not only to detect intrusions but also to mislead attackers, protect real infrastructure, and collect useful threat intelligence. This approach helps in transforming cybersecurity from passive defense to active deception.