Seismic-driven neural intelligence coupled with hybrid evolution strategy for accurate intrusion detection in cloud-IoT systems

Cloud-hosted Internet of Things (IoT) platforms are now the cornerstones of digital infrastructure in today's age, providing scalable, networked spaces for data sharing, processing, and automation. But their open and distributed nature has also made them attractive targets for almost any form o...

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Vydané v:	The Journal of supercomputing Ročník 81; číslo 16; s. 1557
Hlavní autori:	Saravanan, T., Pugalenthi, R.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 12.11.2025 Springer Nature B.V
Predmet:	Algorithms Architecture Artificial intelligence Cloud computing Collaboration Compilers Computer Science Connectivity Construction industry Cybersecurity Data processing Deep learning Digital transformation Effectiveness Intelligence Internet of Things Interpreters Intrusion detection systems Machine learning Pattern recognition Processor Architectures Programming Languages Real time Security systems Software services Workloads Deep learning Cloud computing Feature analysis and classification Intrusion detection system (IDS) Security Internet of things (IoT)
ISSN:	1573-0484, 0920-8542, 1573-0484
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