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Found 7 papers, 1 papers with code
Machine Unlearning with Minimal Gradient Dependence for High Unlearning Ratios
This lightweight, scalable method significantly enhances model accuracy and strengthens resistance to membership inference attacks.
Online Anomaly Detection over Live Social Video Streaming
After that, we propose a novel model update scheme that incrementally maintains CLSTM and decoder.
Trustworthy Privacy-preserving Hierarchical Ensemble and Federated Learning in Healthcare 4.0 with Blockchain
The advancement of Internet and Communication Technologies (ICTs) has led to the era of Industry 4. 0.
Blockchain-based Federated Learning with Secure Aggregation in Trusted Execution Environment for Internet-of-Things
In FL, local models can be tampered with by attackers.
Committed Private Information Retrieval
A PIR scheme is $v$-verifiable if the client can verify the correctness of the retrieved $x_i$ even when $v \leq k$ servers collude and try to fool the client by sending manipulated data.
Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization
In this paper, we present a system design which offers efficient protection of individual model updates throughout the learning procedure, allowing clients to only provide obscured model updates while a cloud server can still perform the aggregation.
Privacy-Aware Identity Cloning Detection based on Deep Forest
We propose a novel method to detect identity cloning of social-sensor cloud service providers to prevent the detrimental outcomes caused by identity deception.
