Explain the concept of model poisoning in Federated Learning and how to mitigate it.

Instruction: Describe what model poisoning is, its impact on Federated Learning, and discuss methods to prevent it.

Context: This question evaluates the candidate’s awareness of security threats in Federated Learning and their knowledge of techniques to safeguard against such vulnerabilities.

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The way I'd explain it in an interview is this: Model poisoning happens when malicious or compromised clients send manipulated updates to distort the global model. The attacker may try to degrade general performance or implant a targeted backdoor while...

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