TY - GEN
T1 - Proactive intrusion detection
AU - Liebald, Benjamin
AU - Roth, Dan
AU - Shah, Neelay
AU - Srikumar, Vivek
PY - 2008
Y1 - 2008
N2 - Machine learning systems are deployed in many adversarial conditions like intrusion detection, where a classifier has to decide whether a sequence of actions come from a legitimate user or not. However, the attacker, being an adversarial agent, could reverse engineer the classifier and successfully masquerade as a legitimate user. In this paper, we propose the notion of a Proactive Intrusion Detection System (IDS) that can counter such attacks by incorporating feedback into the process. A proactive IDS influences the user's actions and observes them in different situations to decide whether the user is an intruder. We present a formal analysis of proactive intrusion detection and extend the adversarial relationship between the IDS and the attacker to present a game theoretic analysis. Finally, we present experimental results on real and synthetic data that confirm the predictions of the analysis.
AB - Machine learning systems are deployed in many adversarial conditions like intrusion detection, where a classifier has to decide whether a sequence of actions come from a legitimate user or not. However, the attacker, being an adversarial agent, could reverse engineer the classifier and successfully masquerade as a legitimate user. In this paper, we propose the notion of a Proactive Intrusion Detection System (IDS) that can counter such attacks by incorporating feedback into the process. A proactive IDS influences the user's actions and observes them in different situations to decide whether the user is an intruder. We present a formal analysis of proactive intrusion detection and extend the adversarial relationship between the IDS and the attacker to present a game theoretic analysis. Finally, we present experimental results on real and synthetic data that confirm the predictions of the analysis.
UR - http://www.scopus.com/inward/record.url?scp=57749197356&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:57749197356
SN - 9781577353683
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 772
EP - 777
BT - AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference
T2 - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08
Y2 - 13 July 2008 through 17 July 2008
ER -