Systematic Analysis of Label-flipping Attacks against Federated Learning in Collaborative Intrusion Detection Systems-Reference-Cited by-同舟云学术

Systematic Analysis of Label-flipping Attacks against Federated Learning in Collaborative Intrusion Detection Systems

Published:2024-07-30 Issue: Volume: Page:1-12
ISSN:
Container-title:Proceedings of the 19th International Conference on Availability, Reliability and Security
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Author:

Lavaur Léo¹^ORCID,Busnel Yann²^ORCID,Autrel Fabien³^ORCID

Affiliation:

1. Dept. SRCD, IMT Atlantique, France and SOTERN, IRISA, France and Chair Cyber CNI, France

2. IMT Nord Europe, France and SOTERN, IRISA, France

3. Dept. SRCD, IMT Atlantique, France and SOTERN, IRISA, France

Funder

European Regional Development Fund

Chaire Cyber CNI

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3664476.3670434

Reference44 articles.

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3. Mamoun Alazab Swarna Priya R M Parimala M Praveen Reddy Thippa Reddy Gadekallu and Quoc-Viet Pham. [n. d.]. Federated Learning for Cybersecurity: Concepts Challenges and Future Directions. ([n. d.]) 1–1. https://doi.org/10/gnm4dj

4. CONTRA: Defending Against Poisoning Attacks in Federated Learning

5. Daniel J Beutel Taner Topal Akhil Mathur Xinchi Qiu Titouan Parcollet and Nicholas D Lane. [n. d.]. Flower: A Friendly Federated Learning Research Framework. ([n. d.]). arxiv:2007.14390

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