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Cited by 11

The DOI matches its Crossref record, with a small difference in title or year.

Hybrid DNN-BiLSTM-aided intrusion detection and trust-clustering and routing-based intrusion prevention system in VANET

Sontakke, Prakash V., Chopade, Nilkanth B.·2025·Journal of Control and Decision
DOI 10.1080/23307706.2023.2212684
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Abstract

This paper focuses on developing an intrusion prevention and detection Vehicular Ad Hoc Network system by expert systems. The node data are composed of online sources. The gathered node data is fed to the extraction phase which can be done by using the autoencoder model. The extraction of features was given to the selection of feature stage to select the optimal features using the Beetle-Whale Swarm Optimization. The selected accurate features are employed in the intrusion detection stage with the help of a hybrid Deep Neural Network and Bidirectional Long Short Term Memory approach for the detection of network intrusion. The intrusion prevention takes place with the Trust-based routing protocol, where the malicious node is prevented by optimally selecting the routing path using the same B-WSO. The experimental analyses are performed to check the efficiency of the developed method by testing with conventional techniques.

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Metadata

Authors
Sontakke, P. V., & Chopade, N. B.
Affiliations
Savitribai Phule Pune University
Venue
Journal of Control and Decision
Publisher
Informa UK Limited
Published
2023-07-13
Volume
12
Issue
2
Pages
209-226
ISSN
  • 2330-7706
  • 2330-7714
DOI
10.1080/23307706.2023.2212684
Cited by
11
References
0
Language
en

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CoChat. (2026). Citation check: Hybrid DNN-BiLSTM-aided intrusion detection and trust-clustering and routing-based intrusion prevention system in VANET. https://app.cochat.ai/papers/10.1080/23307706.2023.2212684
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Sontakke, P. V., & Chopade, N. B. (2025). Hybrid DNN-BiLSTM-aided intrusion detection and trust-clustering and routing-based intrusion prevention system in VANET. Journal of Control and Decision. https://doi.org/10.1080/23307706.2023.2212684

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