HoneyDecoy: A Comprehensive Web-Based Parasitic Honeypot System for Enhanced Cybersecurity
Hexuan Fan, Qingfeng Tan, Runnan Tan, Bohang Nie · 2023
In recent years, the proliferation of web technologies has led to an increase in cyber threats targeting web applications and servers. As a result, honeypots have emerged as a promising tool for understanding and mitigating these threats. This paper presents the design and implementation of HoneyDecoy, a novel web-based parasitic honeypot system that leverages behavior analysis and a HoneyDecoy Markov Decision Process (HD-MDP) for comprehensive protection of web servers. The HoneyDecoy system consists of three main components: the Behavior Analysis Module, HoneyDecoy Engine, and HoneyDecoy Server. By employing a novel HD-MDP-based method, HoneyDecoy can dynamically generate parasitic honeypots based on observed attack traffic and attacker behavior. Experimental results demonstrate the effectiveness of the proposed system in comparison with existing honeypot solutions. This research not only advances the field of honeypots but also contributes to the development of more secure web environments.