Table 5 Privacy evaluation metrics between original and reconstructed images under the iDLG attack.

From: ALDP-FL for adaptive local differential privacy in federated learning

Dataset

Approach

MSE

PSNR

MAE

SSIM

MNIST

FedAvg

0.0659

11.81

0.1609

0.5368

Fed-DPA

0.2025

6.93

0.2949

0.1891

GFL-ALDPA

0.2213

6.36

0.3234

0.0974

LDP-Fed

0.2088

6.80

0.2972

0.1090

ALDP-FL

0.2226

6.5

0.3004

0.0525

Fashion MNIST

FedAvg

0.0341

14.67

0.1306

0.5085

Fed-DPA

0.1279

8.93

0.2624

0.2494

GFL-ALDPA

0.1317

8.8

0.2594

0.1468

LDP-Fed

0.1492

8.26

0.2745

0.1354

ALDP-FL

0.1852

7.32

0.2827

0.0882

CIFAR-10

FedAvg

0.0310

0.0753

15.08

0.4895

Fed-DPA

0.1003

0.2320

9.9

0.1870

GFL-ALDPA

0.1214

0.2716

9.16

0.1231

LDP-Fed

0.1062

0.2489

9.74

0.1403

ALDP-FL

0.1836

0.3352

7.36

0.0808