A new evolutionary neural networks based on intrusion detection systems using locust swarm optimization

Author:

Benmessahel IlyasORCID,Xie Kun,Chellal Mouna,Semong Thabo

Funder

nnsfc

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Vision and Pattern Recognition,Mathematics (miscellaneous)

Reference49 articles.

1. Xie G, Xie K, Huang J, Wang X, Chen Y, Wen J (2017) Fast low-rank matrix approximation with locality sensitive hashing for quick anomaly detection. In: 2017 IEEE Conference on computer communications (INFOCOM)

2. Bamakan SMH, Amiri B, Mirzabagheri M, Shi Y (2015) A new intrusion detection approach using pso based multiple criteria linear programming. Procedia Comput Sci 55:231–237

3. Demertzis K, Iliadis L (2014) A hybrid network anomaly and intrusion detection approach based on evolving spiking neural network classification. Springer International Publishing, Cham, pp 11–23

4. Dash T (2017) A study on intrusion detection using neural networks trained with evolutionary algorithms. Soft Comput 21(10):2687–2700

5. Tang A, Sethumadhavan S, Stolfo SJ (2014) Unsupervised anomaly-based malware detection using hardware features. Springer International Publishing, Cham, pp 109–129

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