Author

Wenjian Luo

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Preprint Jul 2026

FedCVESA: Taking Away Training Data in Federated Learning via Correlation Value Encoding and Segmented Aggregation

The proposed FedCVESA, a federated variant of Correlation Value Encoding Attack, is proposed by adding a Pearson-correlation regularizer to the loss function of target clients, so that private training data are gradually encoded into selected model parameters, referred to as carrier parameters.

Chongkai Li, Bang Zhang, Wenjian Luo · 0 citations

An Automated Framework for Extracting Reachable Attack Chains from Cyber Threat Intelligence Reports

This paper proposes an automated framework that extracts reachable attack chains by modeling each attack step as an attack unit of preconditions, an attack behavior, and postconditions, and produces attack units that are more complete and consistent than those generated by end-to-end LLM baselines.

Wenbo Hou, N. Hu, Xueping Wang et al. · 0 citations