Simulation and Analysis of the Network Feed-Forward Intrusion Detection Model

Abstract:

Traditional single-packet inspection can only detect isolated intrusion. To detect intrusion of network feed-forward and multi-packet collaboration, a lot of prior knowledge or historical knowledge is required. There are many drawbacks of the traditional methods, such as low detection rates and high missing rate. The paper proposes a detection model considering classification intrusion identification, which builds the detection model by analyzing the intrusion feature. The experiment results show that the proposed method effectively solves the problems of intrusion of network feed-forward and multi-packet, and reduces missing rate, of which the detection speed and accuracy are much higher compared to traditional methods.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 2932-2935
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.2932
• Online since: May 2014
• Authors: Wen Qiang Cui*
• Keywords: Feed Forward, Intrusion Detection, Network

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