Honeypots: Tracking Hackers
Advanced Linux Programming
Probabilistic Finite-State Machines-Part I
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lessons learned from the deployment of a high-interaction honeypot
EDCC '06 Proceedings of the Sixth European Dependable Computing Conference
Bash Cookbook: Solutions and Examples for Bash Users (Cookbooks (O'Reilly))
Bash Cookbook: Solutions and Examples for Bash Users (Cookbooks (O'Reilly))
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FAST'06 Proceedings of the 4th international conference on Formal aspects in security and trust
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Journal in Computer Virology
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WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
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Proceedings of the 27th Annual Computer Security Applications Conference
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High-interaction honeypots are relevant to provide rich and useful information obtained from attackers. Honeypots come in different flavors with respect to their interaction potential. A honeypot can be very restrictive, but then only a few interactions can be observed. If a honeypot is very tolerant though, attackers can quickly achieve their goal. Having the best trade-off between attacker freedom and honeypot restrictions is challenging. In this paper, we address the issue of self adaptive honeypots, that can change their behavior and lure attackers into revealing as much information as possible about themselves. The key idea is to leverage game-theoretic concepts for the configuration and reciprocal actions of high-interaction honeypots.