Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System

Ali, Mohammed Hasan; Zolkipli, Mohamed Fadli Bin

doi:10.1007/978-3-030-00979-3_15

Cited by 2 publications

(2 citation statements)

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“…In PSO algorithm, many creatures, are called particles, are distributed in the search space that belongs to the function that is required to be optimized. The objective function value is calculated by each particle according to its position that can be set according to its best previous position and according to its neighbour's best previous position [10]. The calculation of the objective function and the position are repeated several times until it converged to the desired goal.…”

Section: Neural Network and Particle Swarm Optimization Algorithmmentioning

confidence: 99%

“…Finally, the function of the system is substantially improved in terms of the precision of detecting attacks faced by the networks and the time complexities reduction. Mohammed Hasan Ali, Alyani Ismail and Mohamad Fadli Zolkipli [10], proposed a developed learning model for fast learning network (FLN) based on PSO. This learning model is called PSO-FLN.…”

Section: Literature Reviewmentioning

confidence: 99%

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Review of neural networks and particle swarm optimization contribution in intrusion detection

Mahmood

Al‐Khateeb

2019

PEN

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The progress in the field of computer networks and internet is increasing with tremendous volume in recent years. This raises important issues concerning security. Several solutions emerged in the past, which provide security at the host or network level. These traditional solutions like antivirus, firewall, spyware and authentication mechanism provide security to some extents but they still face the challenges of inherent system flaws and social engineering attacks. Some interesting solution emerged like intrusion detection and prevention systems but these too have some problems like detecting and responding in real time and discovering novel attacks. Because the network intrusion behaviors are characterized with uncertainty, complexity and diversity, an intrusion detection method based on neural network and Particle Swarm Optimization (PSO) algorithm is widely used in order to address the problem. This paper gives an insight into how PSO and its variants can be combined with various neural network techniques in order to be used for anomaly detection in network intrusion detection system in order to enhance the performance of intrusion detection system.

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Section: Neural Network and Particle Swarm Optimization Algorithmmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%