Fig 1.
Federated learning framework diagram.
Fig 2.
Federated learning classification.
Table 1.
Comparison of homomorphic encryption algorithms.
Fig 3.
Overall model framework.
Table 2.
Data set classification.
Fig 4.
Transformed grayscale image.
Fig 5.
2DCNN-BIGRU framework.
Table 3.
Experimental environment.
Table 4.
Experimental parameters.
Table 5.
Confusion matrix.
Table 6.
Evaluation of model aggregation algorithms.
Fig 6.
Network resource consumption comparison for three methods in learning process under C = 3 scenario.
Fig 7.
Paillier homomorphic encryption and decryption.
Table 7.
Comparison of different key lengths.
Fig 8.
Communication overhead under different key lengths.
Fig 9.
Accuracy and loss variation of the NIDS-FGPA model.
Fig 10.
Classification report for the nids-fgpa model.
Table 8.
Multi-classification performance comparison.