Network Safety Policy Research for Analyzing Static and Dynamic Traffic Volume on the Basis of Data Mining

ABSTRACT

With popularization of network, higher requirement is proposed to intrusion detection system IDS for network safety consideration. The traditional electronic data processing is combined with safety auditing, which has become a necessary part of constituting integrated network safety technology at present, thus the methods as optimal matching mode and statistics, etc of intrusion detection system shall be adopted. This project shall respectively make comprehensive description to current situations of intrusion detection research via the aspects of intrusion detection research method (anomaly detection, misuse detection), intrusion detection system monitoring object (network based, host based), to comprehensively analyze the impact of intrusion detection system to system architecture. On this basis a network-based anomaly intrusion detection system NAIDS is designed to network anomaly intrusion, the association rules mining and frequent scenario mining are adopted to scan the intrusion characteristic, through static mining mode and dynamic mining mode, safety detection is conducted at single layer and domain layer, new type attack can be detected via improved NAIDS system. Next, NAIDS system performance shall be evaluated by aiming at various intrusion data. Generally speaking, the system performance can detect the rejection service attack and detection attack.

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