Kali Prasad Chiruvelli

Federated Behavioral Intelligence: A Privacy-Preserving Framework for Distributed Customer Behavioral Modeling in Cross-Silo Environments

The paper proposes a systematic analysis framework for investigating five structural aspects, which need behavioral-specific adjustment beyond regular federated learning approaches in the following contexts: feature engineering with data locality; communication efficiency during distributed behavioral model training; differential privacy in behavioral prediction pipelines; non-IID distribution of behaviors in cross-silo federations; and secure aggregation with Byzantine resilience.