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A Systematic Review of Federated Learning Approaches for Privacy-Preserving Artificial Intelligence

https://doi.org/10.2139/ssrn.6574603
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Outgoing claims: the papers this work cites, builds on, or argues with.

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From Injection to Detection: Analyzing the Impact of Anomalous Data in Federated Learning
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SecureIoT-FL: A Federated Learning Framework for Privacy-Preserving Real-Time Environmental Monitoring in Industrial IoT Applications
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FusionFedBlock: Fusion of blockchain and federated learning to preserve privacy in industry 5.0
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Algorithmic bias in machine learning-based marketing models
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Intelligent financial system: How AI is transforming finance
inferredcites →https://doi.org/10.1016/j.patter.2024.100974openalex-snapshot
Privacy preservation for federated learning in health care
inferredcites →https://doi.org/10.1016/j.sysarc.2025.103364openalex-snapshot
An effective and verifiable secure aggregation scheme with privacy-preserving for federated learning
inferredcites →https://doi.org/10.1038/s41598-025-31769-6openalex-snapshot
A hybrid federated learning framework with generative AI for privacy-preserving and sustainable security in IOT-enabled smart environments
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities
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A lightweight encryption algorithm for resource-constrained IoT devices using quantum and chaotic techniques with metaheuristic optimization
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Vulnerabilities in Federated Learning
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A Comprehensive Review of Cryptographic Techniques in Federated Learning for Secure Data Sharing and Applications
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Federated Learning With Non-IID Data: A Survey
inferredcites →https://doi.org/10.1145/3501811openalex-snapshot
GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning
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Benchmarking Relaxed Differential Privacy in Private Learning: A Comparative Survey
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Machine learning concepts for correlated Big Data privacy
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Adapting security and decentralized knowledge enhancement in federated learning using blockchain technology: literature review
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Comprehensive review of federated learning challenges: a data preparation viewpoint
inferredcites →https://doi.org/10.1371/journal.pone.0163477openalex-snapshot
Where Is Current Research on Blockchain Technology?—A Systematic Review
inferredcites →https://doi.org/10.3390/electronics13234744openalex-snapshot
Federated Learning: Navigating the Landscape of Collaborative Intelligence
inferredcites →https://doi.org/10.3390/electronics14050954openalex-snapshot
A Novel User Behavior Modeling Scheme for Edge Devices with Dynamic Privacy Budget Allocation
inferredcites →https://doi.org/10.3390/electronics14081541openalex-snapshot
Efficient Adversarial Training for Federated Image Systems: Crafting Client-Specific Defenses with Robust Trimmed Aggregation
inferredcites →https://doi.org/10.3390/electronics14132512openalex-snapshot
A Review on Federated Learning Architectures for Privacy-Preserving AI: Lightweight and Secure Cloud–Edge–End Collaboration
inferredcites →https://doi.org/10.3390/fi17070308openalex-snapshot
A Review of Research on Secure Aggregation for Federated Learning
inferredcites →https://doi.org/10.3390/healthcare12242587openalex-snapshot
Federated Learning in Smart Healthcare: A Comprehensive Review on Privacy, Security, and Predictive Analytics with IoT Integration
inferredcites →https://doi.org/10.3390/s20247030openalex-snapshot
A Comprehensive Survey on Local Differential Privacy toward Data Statistics and Analysis
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