An effective denial of service detection method using kernel based data

Today much research is being done on host based intrusion detection systems using of kernel based data. However, kernel based data also known as system calls, have a vast variety, which leads to large amounts of preprocessing time when implementing to intrusion detection systems. This paper proposes a method to efficiently detect denial of service attacks, which are continuous threat. Principal Component Analysis will be used to derive the principal components, a Bayesian network will be composed and the Bayesian classifier will be used for the detection.