Intelligent query in intrusion detection audit system
Fei Gao, Qiang Xue, Ji-Zhou Sun · 2004
With the development of Internet, the audit work of IDS (intrusion detection system) is becoming harder. The way of examining log file in text format cannot adapt to the serious situation. In this paper, the NLP (natural language process) technology is introduced to resolve this problem, which can provide a way to interact with audit log file database easily. The FUG (function unification grammar) in NLP is applied to intelligent query in IDS audit system, and XML (extension markup language) schema is utilized in expression of accidence, syntax, glossary library and grammar. At the same time, the feature structure is used to describe the structure of vocabulary, phrase and sentence. These measures can make the query system more intelligent, extendable and friendly.