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Adaptive Ensemble Multi-Agent Based Intrusion Detection Model

Adaptive Ensemble Multi-Agent Based Intrusion Detection Model

Tarek Helmy
Copyright: © 2010 |Pages: 13
ISBN13: 9781615209736|ISBN10: 1615209735|ISBN13 Softcover: 9781616923396|EISBN13: 9781615209743
DOI: 10.4018/978-1-61520-973-6.ch003
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MLA

Helmy, Tarek. "Adaptive Ensemble Multi-Agent Based Intrusion Detection Model." Developing Advanced Web Services through P2P Computing and Autonomous Agents: Trends and Innovations, edited by Khaled Ragab, et al., IGI Global, 2010, pp. 36-48. https://doi.org/10.4018/978-1-61520-973-6.ch003

APA

Helmy, T. (2010). Adaptive Ensemble Multi-Agent Based Intrusion Detection Model. In K. Ragab, T. Helmy, & A. Hassanien (Eds.), Developing Advanced Web Services through P2P Computing and Autonomous Agents: Trends and Innovations (pp. 36-48). IGI Global. https://doi.org/10.4018/978-1-61520-973-6.ch003

Chicago

Helmy, Tarek. "Adaptive Ensemble Multi-Agent Based Intrusion Detection Model." In Developing Advanced Web Services through P2P Computing and Autonomous Agents: Trends and Innovations, edited by Khaled Ragab, Tarek Helmy, and Aboul Ella Hassanien, 36-48. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-61520-973-6.ch003

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Abstract

The system that monitors the events occurring in a computer system or a network and analyzes the events for sign of intrusions is known as intrusion detection system. The performance of the intrusion detection system can be improved by combing anomaly and misuse analysis. This chapter proposes an ensemble multi-agent-based intrusion detection model. The proposed model combines anomaly, misuse, and host-based detection analysis. The agents in the proposed model use rules to check for intrusions, and adopt machine learning algorithms to recognize unknown actions, to update or create new rules automatically. Each agent in the proposed model encapsulates a specific classification technique, and gives its belief about any packet event in the network. These agents collaborate to determine the decision about any event, have the ability to generalize, and to detect novel attacks. Empirical results indicate that the proposed model is efficient, and outperforms other intrusion detection models.

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