Paper Title
Detection Attacks Using Traffic Flow Data And Machine Learning Methods

By the development of information technology applications in organizations, from day to day more services are offered on a platform of computer networks. Due to the large volume of applications and the increasing use of computer networks, security threats on the system had developed for commercial and malicious purposes. However with increasing in traffic and analyzing real-time data traffic exchanged by network-based intrusion detection systems for large networks had become a very complex work.One of the ways that we can reduce the complexity of the whole traffic, analyze summary data on traffic flows rather than the entire traffic. One of the standards to generating traffic flows data is NetFlow standards that generates traffic flow data, that summarizes data from the network traffic flow by routers and Cisco switches automatically. This paper presents an efficient way to analyze the traffic and classify it in order to identify traffic related to the attacks and preventive measures, which presented a summary of data on the traditional classification algorithms to do the traffic flows. Keywords- Attacks, Traffic flow data, Net Flow, Classification algorithm, KDDcup99