Fed PCA: Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks [INFOCOM2023]
This repository is for the Experiment Section of the paper: "Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks"
Authors: Tung-Anh Nguyen, Jiayu He, Long Tan Le, Nguyen H.Tran
Paper link: https://arxiv.org/pdf/2212.12121.pdf
Software requirements:
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numpy, scipy, pytorch, Pillow, matplotlib.
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To download the dependencies: pip3 install -r requirements.txt
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The code can be run on any pc.
Instruction to run the code
!python3 main.py --algorithm FedPG --learning_rate 0.0001 --num_global_iters 100 --dim 30 --subusers 0.1 --local_epochs 30
!python3 main.py --algorithm FedPE --learning_rate 0.0001 --num_global_iters 100 --dim 30 --subusers 0.1 --local_epochs 30
Estimate training time for FedPG and FedPE
!python3 main.py --algorithm FedPG --learning_rate 0.0001 --num_global_iters 1000 --dim 30 --subusers 0.1 --local_epochs 30 !python3 main.py --algorithm FedPE --learning_rate 0.0001 --num_global_iters 1000 --dim 30 --subusers 0.1 --local_epochs 30 !python3 main.py --algorithm FedPE --learning_rate 0.0001 --num_global_iters 1000 --dim 30 --subusers 0.1 --local_epochs 40 !python3 main.py --algorithm FedPE --learning_rate 0.0001 --num_global_iters 1000 --dim 30 --subusers 0.1 --local_epochs 60 !python3 main.py --algorithm FedPE --learning_rate 0.0001 --num_global_iters 1000 --dim 30 --subusers 0.1 --local_epochs 80
Dataset:
NSL-KDD