Applying MapReduce and network traffic analysis to control access to information resources

Nowadays information security is an important issue. Network traffic analysis is widely used by Internet Service Providers to evaluate network performance, to collect statistics and to detect vulnerabilities. To analyze traffic traces collected from a large network it is required a computer system where both storage and computing resources can be easily scaled out to handle and process multi-Terabyte files. Cloud computing platforms and cluster file systems could provide resizable compute and storage capacity. The MapReduce programming model developed by Google in 2004 allows processing huge amounts of data in distributed manner by defining the map and reduce functions. The given paper proposes a cloud-computing framework based on a MapReduce approach for fast internet traffic analytics.