FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning

Huimin Li*, Phillip Rieger, Shaza Zeitouni, Stjepan Picek, Ahmad Reza Sadeghi

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


Federated Learning (FL) has become very popular since it enables clients to train a joint model collaboratively without sharing their private data. However, FL has been shown to be susceptible to backdoor and inference attacks. While in the former, the adversary injects manipulated updates into the aggregation process; the latter leverages clients' local models to deduce their private data. Contemporary solutions to address the security concerns of FL are either impractical for real-world deployment due to high-performance overheads or are tailored towards addressing specific threats, for instance, privacy-preserving aggregation or backdoor defenses. Given these limitations, our research delves into the advantages of harnessing the FPGA-based computing paradigm to overcome performance bottlenecks of software-only solutions while mitigating backdoor and inference attacks. We utilize FPGA-based enclaves to address inference attacks during the aggregation process of FL. We adopt an advanced backdoor-aware aggregation algorithm on the FPGA to counter backdoor attacks. We implemented and evaluated our method on Xilinx VMK-180, yielding a significant speed-up of around 300 times on the IoT-Traffic dataset and more than 506 times on the CIFAR-10 dataset.
Original languageEnglish
Title of host publicationProceedings of the 2023 33rd International Conference on Field-Programmable Logic and Applications (FPL)
EditorsL. O’Conner
Place of PublicationPiscataway
Number of pages6
ISBN (Electronic)979-8-3503-4151-5
ISBN (Print)979-8-3503-4152-2
Publication statusPublished - 2023
Event2023 33rd International Conference on Field-Programmable Logic and Applications (FPL) - Gothenburg, Sweden
Duration: 4 Sept 20238 Sept 2023
Conference number: 33rd


Conference2023 33rd International Conference on Field-Programmable Logic and Applications (FPL)

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • FPGA Acceleration
  • Federated Learning (FL)
  • FPGA-based FL
  • Backdoor-aware FL
  • Privacy-preserving FL


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