Unleashing the power of Bat optimized CNN-BiLSTM model for advanced network anomaly detection: Enhancing security and performance in IoT environments

Unleashing the power of Bat optimized CNN-BiLSTM model for advanced network anomaly detection: Enhancing security and performance in IoT environments

The growth of IoT (Internet of Things) devices has revolutionized several industries and brought about novel security threats. Recognizing network anomalies that may point to malicious activity or system flaws is a major issue. Traditional anomalous identification methods frequently need to catch up...

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Bibliographic Details
Main Authors: Franciskus Antonius, J.C. Sekhar, Vuda Sreenivasa Rao, Rahul Pradhan, S. Narendran, Ricardo Fernando Cosio Borda, Susan Silvera-Arcos
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Alexandria Engineering Journal
Subjects:
Internet of Things (IoT)
Bidirectional Long Short-Term Memory (BiLSTM)
Convolutional Neural Network (CNN)
Particle Swarm Optimisation (PSO)
Anomaly Detection
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016823009924

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http://www.sciencedirect.com/science/article/pii/S1110016823009924

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