Cite this DOI
10.46243/jst.2025.v10.i02.pp95-107 · Blockchain-Assisted Federated Learning for Cybersecurity: Combining Isolation Forest, Variational Autoencoders, and Differential Privacy
APA (7th edition)
Durga Praveen Devi, Naga Sushma Allur, Koteswararao Dondapati, Himabindu Chetlapalli, Sharadha Kodadi, & Aravindhan Kurunthachalam (2025). Blockchain-Assisted Federated Learning for Cybersecurity: Combining Isolation Forest, Variational Autoencoders, and Differential Privacy. *Journal of Science & Technology*, *10*(2), 95–107. https://doi.org/10.46243/jst.2025.v10.i02.pp95-107
⬇ text Italics are shown as *asterisks* in plain text — the journal or book title and the volume.
BibTeX
@article{durgapraveendevi2025blockchainassisted,
author = {Durga Praveen Devi and Naga Sushma Allur and Koteswararao Dondapati and Himabindu Chetlapalli and Sharadha Kodadi and Aravindhan Kurunthachalam},
title = {{Blockchain-Assisted Federated Learning for Cybersecurity: Combining Isolation Forest, Variational Autoencoders, and Differential Privacy}},
journal = {Journal of Science \& Technology},
year = {2025},
month = {feb},
volume = {10},
number = {2},
pages = {95--107},
publisher = {Longman Publishers},
issn = {2456-5660},
doi = {10.46243/jst.2025.v10.i02.pp95-107},
url = {https://doi.org/10.46243/jst.2025.v10.i02.pp95-107},
abstract = {The complexity of the cyber threats dictates the need for strong, privacy-preservingmechanisms for anomaly detection. This paper introduces a new framework called BAFL, anintegration of Isolation Forest and Variational Autoencoders combined with DifferentialPrivacy, for safe and scalable solutions in cybersecurity applications. Federated Learningallows distributed training across numerous clients without exposure of sensitive information,while the blockchain technology introduces trust and integrity in model updates.}
}RIS (EndNote, Zotero, Mendeley)
TY - JOUR TI - Blockchain-Assisted Federated Learning for Cybersecurity: Combining Isolation Forest, Variational Autoencoders, and Differential Privacy AU - Durga Praveen Devi AU - Naga Sushma Allur AU - Koteswararao Dondapati AU - Himabindu Chetlapalli AU - Sharadha Kodadi AU - Aravindhan Kurunthachalam JO - Journal of Science & Technology PY - 2025 DA - 2025/02/28/ VL - 10 IS - 2 SP - 95 EP - 107 PB - Longman Publishers SN - 2456-5660 AB - The complexity of the cyber threats dictates the need for strong, privacy-preservingmechanisms for anomaly detection. This paper introduces a new framework called BAFL, anintegration of Isolation Forest and Variational Autoencoders combined with DifferentialPrivacy, for safe and scalable solutions in cybersecurity applications. Federated Learningallows distributed training across numerous clients without exposure of sensitive information,while the blockchain technology introduces trust and integrity in model updates. DO - 10.46243/jst.2025.v10.i02.pp95-107 UR - https://doi.org/10.46243/jst.2025.v10.i02.pp95-107 ER -
CSL-JSON
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} ⬇ .json What citeproc and reference managers read; the DOI system hands it out for Accept: application/vnd.citationstyles.csl+json, and so does this registry's resolver.
From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2025.v10.i02.pp95-107 gives all four in one JSON answer.
