DarkNOC: Dashboard for Honeypot Management Bertrand Sobesto, Michel Cukier Matti Hiltunen, Dave Kormann, Gregg Vesonder Clark School of Engineering AT&T Labs Research University of Maryland 180 Park Ave. College Park, MD, USA Florham Park, NJ, USA fbsobesto,
[email protected] fhiltunen, davek,
[email protected] Robin Berthier Coordinated Science Laboratory Information Trust Institute University of Illinois Urbana-Champaign, IL, USA
[email protected] Abstract been used to conduct various studies of attackers [1, 9] and analysis of cyber crimes such as unsollicited elec- Protecting computer and information systems from secu- tronic mails, phishing [10], identity theft and denial of rity attacks is becoming an increasingly important task service. The computer security community has used hon- for system administrators. Honeypots are a technol- eypots to analyze different techniques deployed by the ogy often used to detect attacks and collect information attackers to reach their objectives. Attackers’ arsenal about techniques and targets (e.g., services, ports, oper- includes distributed denial of service [24], botnets [2], ating systems) of attacks. However, managing a large worms [11] or SPAM [15]. However few studies focus and complex network of honeypots becomes a challenge on the usage of honeypots data to help network adminis- given the amount of data collected as well as the risk that trators to better protect their production networks. Hon- the honeypots may become infected and start attacking eypot deployment is challenging and the architecture of other machines. In this paper, we present DarkNOC, a such networks is complex. For example, distributed hon- management and monitoring tool for complex honeynets eynets require secure tunnels and different levels of pro- consisting of different types of honeypots as well as other tection must be in place to ensure a total containment of data collection devices.