An Enhanced LSTM Approach for Detecting IoT-Based DDoS Attacks Using Honeypot Data

An Enhanced LSTM Approach for Detecting IoT-Based DDoS Attacks Using Honeypot Data

Abstract One of the widening perils in network security is the Distributed Denial of Service (DDoS) attacks on the Internet of Things (IoT) ecosystem. This paper presents an enhanced Intrusion Detection System (IDS) through the proposal of an enhanced version of the long short-term memory (LSTM) mod...

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Bibliografiska uppgifter
Huvudupphovsmän: Arjun Kumar Bose Arnob, M. F. Mridha, Mejdl Safran, Md Amiruzzaman, Md. Rajibul Islam
Materialtyp: Artikel
Språk:English
Publicerad: Springer 2025-02-01
Serie:International Journal of Computational Intelligence Systems
Ämnen:
IoT
DDoS attacks
Intrusion detection
Enhanced LSTM
Honeypot
IoT-DH Dataset
Länkar:https://doi.org/10.1007/s44196-025-00741-7

Internet

https://doi.org/10.1007/s44196-025-00741-7

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