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  4. Vol 11, Issue 1, 2026

Federated Learning for Enterprise Information Systems: Security, Privacy, Architecture, and Deployment Challenges—A Review

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DOI: 10.23977/jeis.2026.110112 | Downloads: 0 | Views: 41

Author(s)

Li Fei 1

Affiliation(s)

1 School of Artificial Intelligence, Neijiang Normal University, No. 1 Hongqiao Street, Dongxing District, Neijiang, Sichuan, 641100, China

Corresponding Author

Li Fei

ABSTRACT

Federated learning enables organizations to develop shared models while retaining local control of training records. Exchanged updates can nevertheless reveal sensitive information, making privacy protection a central system-design requirement. This narrative review examines cross-silo collaboration from the choice of data architecture to the operation of a shared prediction service. It compares differential privacy, secure aggregation, secure multi-party computation, homomorphic encryption, and trusted execution environments, explaining their protection boundaries and the costs of putting them into practice. Evidence from communication-efficient learning and encrypted-training systems makes the computational trade-offs concrete. Healthcare, credit-risk, and energy studies supply examples of cross-institutional prediction and its operating requirements. The synthesis distinguishes confidentiality during computation from disclosure through released outputs, and examines the tension between hidden updates and integrity checks. A seven-stage technical deployment framework turns these findings into a workflow for selecting protections, validating local performance, and maintaining the federation as its participants and services change. The review provides a basis for choosing complementary controls and planning deployment around both the learning task and its operational requirements.

KEYWORDS

Federated Learning; Enterprise Information Systems; Information Systems Security; Privacy-Enhancing Technologies; Cross-Silo Learning

CITE THIS PAPER

Li Fei. Federated Learning for Enterprise Information Systems: Security, Privacy, Architecture, and Deployment Challenges—A Review. Journal of Electronics and Information Science (2026). Vol. 11, No. 1, 95-102. DOI: http://dx.doi.org/10.23977/10.23977/jeis.2026.110112.

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