Evolutionary gravitational neocognitron neural network espoused blockchain-based intrusion detection framework for enhancing cybersecurity in a cloud computing environment

Cloud computing offers scalable, on-demand resources but remains highly vulnerable to cyberattacks, where the nonlinear and dynamic nature of network traffic makes detection especially challenging. This study introduces EGNNN-GROA-BGPoW-IDS-CC, a novel intrusion detection framework that explicitly a...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Ain Shams Engineering Journal Ročník 16; číslo 12; s. 103805
Hlavní autoři:	Ravi Kanth, R., Prem Jacob, T.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.12.2025
Témata:	Blockchain Green Proof of Work (BGPoW) Cloud computing Cybersecurity Dynamic Recursive Feature Selection Algorithm (DRFSA) Evolutionary Gravitational Neocognitron Neural Network (EGNNN) GarraRufa Fish Optimization (GROA) Intrusion Detection Systems (IDS) Nonlinear attack patterns Cloud computing EGNNN ABC DBF DoS SVM IoT ResNet MLP DBN LLS QoS Blockchain Green Proof of Work (BGPoW) XGBoost IDS SRCC GA GROA GWO SSA Nonlinear attack patterns Evolutionary Gravitational Neocognitron Neural Network (EGNNN) DRFSA Dynamic Recursive Feature Selection Algorithm (DRFSA) Intrusion Detection Systems (IDS) HEPDA HCD GarraRufa Fish Optimization (GROA) Cybersecurity BiLSTM PSO R2L BGPoW PCC RST WSN U2R DRFLLS PPSC BCAI
ISSN:	2090-4479
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!