Adaptive Web Intrusion Detection Based on Immune and Fuzzy Logic
作者： Lai Xing-rui
DOI:
关键词: Adaptive neuro fuzzy inference system 、 Web application 、 Anomaly-based intrusion detection system 、 Web server 、 Computer science 、 Fuzzy rule 、 Artificial intelligence 、 Fuzzy logic 、 Data mining 、 Intrusion detection system 、 Machine learning 、 Neuro-fuzzy
摘要: Web servers and web applications have become one of the most important communication channels on Internet. Web-based vulnerabilities represent a substantial portion security exposures computer networks. It appears more difficult to detect intrusion. This paper describes an adaptive intrusion detection model based immune fuzzy logic. The creates respectively rule collection natural behaviour mode inspecting with improved generation candidate itemsets. is detected by difference between two collections. Besides, updates rules automatically constantly improve ability detecting new intrusions. Experiment results indicate that has better efficiency in identifying abnormal compared no update non-fuzzy model.
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