Fast association rule mining algorithm for network attack data

Abstract

Current risk data generated by network attack data is lack of predictability, in this paper, a fast association rule mining algorithm for network attack data is proposed. Based on the related data, the fuzzy theory is used to introduce the frequency of network attack events into the association rules, and based on the genetic algorithm, the concept of interest degree and approximation are introduced to improve the membership function which can establish the network attack data association rules to achieve rapid data mining. The experimental results showed that the proposed algorithm has certain accuracy and efficiency advantages.

Subject Classification:

• MSC2010
• 94C99

Keywords:

• Network attack data
• Association rules
• Mining algorithm
• Fuzzy theory