Adversarial AI and Data Poisoning in Federated Learning

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Adversarial AI and Data Poisoning in Federated LearningWith the growing security challenges at the intersection of distributed machine learning and malicious interference, there are growing challenges that federated learning can address. Federated learning enables collaborative model training across devices while preserving data privacy. However, this decentralized nature also opens new vulnerabilities, particularly to adversarial attacks and data poisoning, where malicious actors can inject corrupted

and how generative AI can be utilized in SOC automation

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