Blockchain-Assisted Federated Learning for Cybersecurity: Combining Isolation Forest, Variational Autoencoders, and Differential Privacy

The complexity of the cyber threats dictates the need for strong, privacy-preservingmechanisms for anomaly detection. This paper introduces a new framework called BAFL, anintegration of Isolation Forest and Variational Autoencoders combined with DifferentialPrivacy, for safe and scalable solutions in cybersecurity applications. Federated Learningallows distributed training across numerous clients without exposure of sensitive information,while the blockchain technology introduces trust and integrity in model updates.