| Title | Anomaly-based Intrusion Detection System Using Fuzzy Logic |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Almseidin, Mohammad, Al-Sawwa, Jamil, Alkasassbeh, Mouhammd |
| Conference Name | 2021 International Conference on Information Technology (ICIT) |
| Date Published | jul |
| Keywords | Computer crime, denial-of-service attack, distributed denial of service attack, feature extraction, feature selection, Fuzzy logic, information technology, Intrusion detection, intrusion detection system, Metrics, Open Source Software, pubcrawl, resilience, Resiliency, security |
| Abstract | Recently, the Distributed Denial of Service (DDOS) attacks has been used for different aspects to denial the number of services for the end-users. Therefore, there is an urgent need to design an effective detection method against this type of attack. A fuzzy inference system offers the results in a more readable and understandable form. This paper introduces an anomaly-based Intrusion Detection (IDS) system using fuzzy logic. The fuzzy logic inference system implemented as a detection method for Distributed Denial of Service (DDOS) attacks. The suggested method was applied to an open-source DDOS dataset. Experimental results show that the anomaly-based Intrusion Detection system using fuzzy logic obtained the best result by utilizing the InfoGain features selection method besides the fuzzy inference system, the results were 91.1% for the true-positive rate and 0.006% for the false-positive rate. |
| DOI | 10.1109/ICIT52682.2021.9491742 |
| Citation Key | almseidin_anomaly-based_2021 |
Anomaly-based Intrusion Detection System Using Fuzzy Logic