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primary topic: A scalable and secure federated learning authentication scheme for IoT

A scalable and secure federated learning authentication scheme for IoT
type: AcademicArticle
type: Article
abstract: Secure and scalable authentication remains a fundamental challenge in Internet of Things (IoT) networks due to constrained device resources, dynamic topology, and the absence of centralized trust infrastructures. Conventional password-based and certificate-driven authentication schemes incur high computation, storage, and communication overhead, limiting their suitability for large-scale deployments. To address these limitations, this paper proposes ScLBS, a federated learning (FL)–based self-certified authentication scheme for distributed and sustainable IoT environments. ScLBS integrates self-certified public key cryptography with FL-driven trust adaptation, enabling decentralized public key derivation without reliance on third-party certificate authorities or exposure of private credentials. A zero-knowledge mechanism combined with location-aware authentication strengthens resistance to impersonation, Sybil, and replay attacks. Hierarchical key management supported by a -tree enables efficient group rekeying and preserves forward and backward secrecy under dynamic membership. Formal security verification is conducted under the Dolev–Yao adversary model using ProVerif, confirming secrecy of private and session keys (SKs) and correctness of authentication. Extensive NS-3 simulations and ablation analysis demonstrate that ScLBS achieves lower authentication delay, reduced message overhead, improved network utilization, and decreased energy consumption compared to representative IoT authentication schemes, while maintaining bounded FL overhead. These results indicate that ScLBS provides a balanced trade-off between security strength, scalability, and resource efficiency for constrained IoT networks.
date: 2026-02
is part of: Scientific Reports
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ArticleEPrint
is part of: repository
has document: A scalable and secure federated learning authentication scheme for IoT (Texto)
has document: A scalable and secure federated learning authentication scheme for IoT (Otro)
subject: Engineering

A scalable and secure federated learning authentication scheme for IoT (Texto)
type: Document
has file: s41598-026-37541-8_reference.pdf
has part: s41598-026-37541-8_reference.pdf

Scientific Reports
type: Collection
issn: 20452322

B. Veera Jyothi
type: Person
given name: B. Veera
family name: Jyothi

Ravi Kumar Rachavaram
type: Person
given name: Ravi Kumar
family name: Rachavaram

M. Ramchander
type: Person
given name: M.
family name: Ramchander

Fahd S. Alharithi
type: Person
given name: Fahd S.
family name: Alharithi

Aman Singh
type: Person
given name: Aman
family name: Singh

Premkumar Chithaluru
type: Person
given name: Premkumar
family name: Chithaluru

Wojciech Ksiazek
type: Person
given name: Wojciech
family name: Ksiazek

A scalable and secure federated learning authentication scheme for IoT (Otro)
type: Document
is version of: A scalable and secure federated learning authentication scheme for IoT (Texto)
is volatile version of: A scalable and secure federated learning authentication scheme for IoT (Texto)
is index codes version of: A scalable and secure federated learning authentication scheme for IoT (Texto)
has file: indexcodes.txt
has part: indexcodes.txt

HTML Summary of #27554 A scalable and secure federated learning authentication scheme for IoT
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primary topic: A scalable and secure federated learning authentication scheme for IoT

Engineering
type: Concept
preferred label: Ingeniería @es