Denial-of-service attack detection system

Use of online applications in day-to-day life is increasing. In parallel to this increase the threat to the security of these applications is also increasing. The security of these applications is breached by different cyber attacks. Denial-of-Service (DoS) is one such type of cyber attack. DoS makes the online application or the resources of the server unavailable to the intended users. For detecting these DoS attacks a detection system is proposed which can be used for detecting both known and unknown attacks. In the proposed system makes use of multivariate correlation analysis (MCA) technique which extracts the geometrical correlation between network traffic. This geometrical correlation is used for detecting DoS attack. Triangle area based technique to used enhance and speedup the MCA process. KDD cup 99 dataset is for examining the effectiveness of the proposed system. To increase the detection rate and to reduce the complexity of the proposed system a subset of features of the record is used. This subset is used in the whole detection process.