Work

Anomaly-based Intrusion Detection System Using Fuzzy Logic

Year: 2021

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2107.12299

Authors: Almseidin, Mohammad, Al-Sawwa, Jamil, Alkasassbeh, Mouhammd

Institutions: Tafila Technical University, University of Miskolc, Princess Sumaya University for Technology

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W3186169234

Cites: 19

Cited by:

Related to: 20