RRPOT: A Record and Replay Based Honeypot System

Abstract

The honeypot system is a critical defense facility in cybersecurity. It captures and analyzes the attack behavior for constructing a more robust defense system. However, considering the overhead caused by analysis, the system cannot support fine-grained analysis. This paper proposes RRPOT, a novel honeypot system based on the record and replay (RnR) framework of virtual machine (VM). By combining the native honeypot system with an RnR framework, the system supports to postpone the time-consuming analysis to the replay stage, thereby enables fine-grained analysis. Moreover, we propose an on-demand record mechanism to reduce performance and storage costs during the record stage and employ an on-demand replay mechanism to improve replay efficiency. Leveraging these approaches, we develop a flexible and efficient honeypot system, and it was proven useful in the practical scenario.