Abstract
There are various host-based methods and network-based methods to monitor network intrusions in real time, but they are limited in the context of identifying anomalies activities in the network. In this research study, in order to boost security in network intrusion systems, one method is to apply signal processing strategies which include powerful continuous wavelet transform methods that consist of different mother wavelets to detect any anomalies in network site traffic data. The percentage deviation metric was used to assess the quality of performance of the wavelets in detecting anomalous network activities such as brute force, port scan and DoS attacks. Results obtained from the analysis showed that Morlet wavelet performed better than the other implemented wavelets for detecting anomalies in traffic signal data based on the lowest percentage deviation value.