README.md

README.md

@@ -1 +1,21 @@
-# Cre-DPSIGN
+# Cre-DPSIGN
+
+## paper info
+
+**Credit-based Differential Privacy Stochastic Model Aggregation Algorithm for Robust Federated Learning via Blockchain** is submitted in 52nd International Conference on Parallel Processing Proceedings.
+
+## Document description
+There are seven executive documents in our experiment, named CreFlip.py, CreGau.py with two differential privacy mechanisms, and baseline: RSA.py, RSA-flip.py, RSA-Gau.py, SGD.py, SIGNSGD.py. 
+
+The options.py has all setting parameters 
+
+## code executing
+For executing CreFlip.py: python CreFlip.py --eps=0.4 --lr=0.04 --byzantinue_users=10 
+
+## running time
+In the MNIST dataset around 6 hours, and in the CIFAR dataset around 5 days. (Our code has the potential for further optimization in terms of time, which will be pursued in future work.)
+
+## experiment results
+The experiment results(.pkl) are automatically stored in different packages to distinguish different attacks, such as sign_flipping, same_value. We also have two evaluation documents named draw.py and draw_cre.py, representing accuracy and robustness respectively.
+
+