Application of meta-heuristic algorithms in intrusion detection system | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 204، دوره 13، شماره 2، مهر 2022، صفحه 2517-2540 اصل مقاله (1.31 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.27338.3563 | ||
| نویسندگان | ||
| Amirreza Saba1؛ Xiang Michelle Liu* 1؛ Marjan Mansourvar2 | ||
| 1School of Technology and Innovation, Marymount University, Virginia, USA | ||
| 2DTU Computer Bioscience Group, Technical University of Denmark (DTU), Lyngby, Denmark | ||
| چکیده | ||
| With the Internet being the dominant tool for global communication in today’s world, the issue of Internet information security has become quite a significant challenge. Wireless sensor networks, like other systems, can be penetrated and it appears that natural communities, due to their adequate capabilities in information processing, can be utilized as a model in these networks. Accordingly, in this study, we shall analyze a model that uses the energy and operational power of the three meta-heuristic algorithms GA, PSO & GSO that occur in natural communities. Furthermore, we introduced four Dos, D-dos, Wormhole, and Sinkhole attacks to these algorithms, and thereafter examined their latency, throughput, and energy. The findings revealed that among these algorithms, the GA algorithm has the highest energy and the PSO algorithm has the highest throughput. | ||
| کلیدواژهها | ||
| Intrusion Detection System؛ Mobile Ad-Hoc Network؛ Glow Worm Optimization Algorithms؛ Genetic Algorithms؛ Particle Swarm Optimization Algorithms | ||
| مراجع | ||
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