A Cloud Security Situational Awareness Model Based on Parallel Apriori Algorithm

Abstract:

Network Security Situation Awareness (NSSA) is a hot topic in network security field, and cloud computing is a new technology integrated virtual storage and distributed computing. It has become the challenging questions how to provide efficient and reliable service for NSSA based on the cloud computing.This paper proposes a cloud security situation awareness model based on data mining, and puts forwarda parallelfrequent-tree Apriori algorithm (PFT-Apriori) for mining association rules. Compare with the traditional Apriori algorithm, the experimental results show that the performance of system is increased by 51% under PFT-algorithm.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 6294-6297
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.6294
• Online since: May 2014
• Authors: Xiao Liang, Hong Wu Lv, Fang Fang Guo, Hui Qiang Wang*
• Keywords: Association Rule, Cloud Security Situation Awareness, Parallel Apriori Algorithm

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