Advanced Honeypot Architecture for Network Threats Quantification

Advanced Honeypot Architecture for Network Threats Quantification

Abstract :-
Honeypots were introduced to monitor unused IP spaces to learn about attackers. The advantage of honeypots over other monitoring solutions is to collect only suspicious activity. However, current honeypots are expensive to deploy and complex to administrate especially in the context of large organization networks. This study addresses the challenge of improving the scalability and flexibility of honeypots by introducing a novel hybrid honeypot architecture. This architecture is based on a Decision Engine and a Redirection Engine that automatically filter attacks and save resources by reducing the size of the attack data collection and allow researchers to actively specify the type of attack they want to collect. For a better integration into the organization network, this architecture was combined with network flows collected at the border of the production network. Continue reading Advanced Honeypot Architecture for Network Threats Quantification