| Title | DOS and Brute Force Attacks Faults Detection Using an Optimised Fuzzy C-Means |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Qader, Karwan, Adda, Mo |
| Conference Name | 2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA) |
| Keywords | brute force attacks, Clustering algorithms, clustering methods, computer network security, computer network systems, computer networks, DOS brute force attacks faults detection, Fault Clustering, fault detection, Force, Fuzzy Cluster Means, fuzzy set theory, human factors, Management information base, MIB feature, network administrators, Network Fault Attacks, network issues, network performance, optimised fuzzy c-means, policy-based governance, Protocols, pubcrawl, Servers, SFCM method, SNMP-MIB parameter datasets, SNMP-MIB variables, specialised MIB dataset, Subtractive Clustering |
| Abstract | This paper explains how the commonly occurring DOS and Brute Force attacks on computer networks can be efficiently detected and network performance improved, which reduces costs and time. Therefore, network administrators attempt to instantly diagnose any network issues. The experimental work used the SNMP-MIB parameter datasets, which are collected via a specialised MIB dataset consisting of seven types of attack as noted in section three. To resolves such issues, this researched carried out several important contributions which are related to fault management concerns in computer network systems. A central task in the detection of the attacks relies on MIB feature behaviours using the suggested SFCM method. It was concluded that the DOS and Brute Force fault detection results for three different clustering methods demonstrated that the proposed SFCM detected every data point in the related group. Consequently, the FPC approached 1.0, its highest record, and an improved performance solution better than the EM methods and K-means are based on SNMP-MIB variables. |
| DOI | 10.1109/INISTA.2019.8778238 |
| Citation Key | qader_dos_2019 |
DOS and Brute Force Attacks Faults Detection Using an Optimised Fuzzy C-Means