Fuzzy Threat Assessment on Service Availability with Data Fusion Approach

Service Availability is important for any organization. This has become more important with the increase of DoS attacks. It is therefore essential to assess the threat on service availability. We have proposed a new model for threat assessment on service availability with a data fusion approach. We have selected three more important criteria for evaluating the threat on service availability and used anomaly detection algorithms to evaluate the network behavior. Anomaly of each parameter over time was measured based on its past behavior. The results of each algorithm were aggregated using the order weighted average (OWA) and finally using fuzzy inference system (FIS), threat has been calculated. We have evaluated our proposed model with data from a web server monitoring. The results show that it can provide network administrator with useful information about the status of service availability and help them to reduce threats and losses due to their actual activation.