most citedFedDef: Defense Against Gradient Leakage in Federated Learning-based Network Intrusion Detection Systems

48 citations · 89 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CR2022★ 48 cited

FedDef: Defense Against Gradient Leakage in Federated Learning-based Network Intrusion Detection Systems

Jiahui Chen, Yi Zhao, Qi Li +2

Deep learning (DL) methods have been widely applied to anomaly-based network intrusion detection system (NIDS) to detect malicious traffic. To expand the usage scenarios of DL-base…

cs.CR2020★ 41 cited

Off-Path TCP Exploits of the Mixed IPID Assignment

Xuewei Feng, Chuanpu Fu, Qi Li +2

In this paper, we uncover a new off-path TCP hijacking attack that can be used to terminate victim TCP connections or inject forged data into victim TCP connections by manipulating…