Research Article
User-Level Membership Inference for Federated Learning in Wireless Network Environment
Algorithm 1
Participant’s attack procedure.
Input: The GANs iteration round , the federated learning model (), generator , discriminator . | Output: The generated dataset :(x,y) and the inference result ‘IN’ or ‘OUT’. | 1: Procedure Adversary Execution. | 2: Initialize | 3: Set | 4: for (;;) do | 5: Run to generate sample | 6: Update based on Eq (8) | 7: end for | 8: | 9: Output: | 10: | 11: Attack Phase: | 12: Train CNN model using dataset. | 13: Perform membership inference attack against dataset. | 14: Compare the inference results with the claimed information. | 15: Output: Mark every record as ‘IN’ or ‘OUT’, where ‘IN’represents the Victim’s training sample. |
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