A malicious FL server can steal private training images by encoding them into model parameters via a correlation regularizer and preserving them through segmented aggregation.
Reconfigurable Intelligent Surfaces: A Physical Layer Security Perspective
2 Pith papers cite this work, alongside 3 external citations. Polarity classification is still indexing.
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Pith papers citing it
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2026 2representative citing papers
A multi-objective optimization framework is proposed for RIS deployment location, orientation, size, and ISAC weight allocation in networks supporting communication, sensing, and physical layer security, with simulations showing inherent trade-offs among the three.
citing papers explorer
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FedCVESA: Taking Away Training Data in Federated Learning via Correlation Value Encoding and Segmented Aggregation
A malicious FL server can steal private training images by encoding them into model parameters via a correlation regularizer and preserving them through segmented aggregation.
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Multi-Objective RIS Deployment Optimization for Physical Layer Security in ISAC Networks
A multi-objective optimization framework is proposed for RIS deployment location, orientation, size, and ISAC weight allocation in networks supporting communication, sensing, and physical layer security, with simulations showing inherent trade-offs among the three.