Enhancing cybersecurity using optimized anti-interference dynamic integral neural network-based intrusion detection system

Cybersecurity has become a critical concern due to the exponential growth of the Internet of Things (IoT), computer networks, and associated applications, which have introduced new vulnerabilities and increased the risk of cyberattacks. Detecting such anomalies and designing an efficient intrusion d...

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Vydáno v:	Knowledge and information systems Ročník 67; číslo 6; s. 5413 - 5435
Hlavní autoři:	Chaudhary, Deevesh, Shekhawat, Deepika, Gupta, Sunita, Kalwar, Anju, Mishra, Neha, Nawal, Meenakshi
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.06.2025 Springer Nature B.V
Témata:	Accuracy Algorithms Brief Report Computer Science Computing time Cybersecurity Data Mining and Knowledge Discovery Database Management Datasets Information Storage and Retrieval Information Systems and Communication Service Information Systems Applications (incl.Internet) Internet of Things Intrusion detection systems IT in Business Neural networks Optimization Optimization algorithms CIC IoT 2022 dataset Industrial control systems Anti-interference dynamic integral neural network Smoothing–sharpening filter Capuchin search optimization algorithm Tyrannosaurus optimization algorithm
ISSN:	0219-1377, 0219-3116
On-line přístup:	Získat plný text
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