most citedEnabling Privacy-Preserving Cyber Threat Detection with Federated Learning

3 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CR2024

SpamDam: Towards Privacy-Preserving and Adversary-Resistant SMS Spam Detection

Yekai Li, Rufan Zhang, Wenxin Rong +1

In this study, we introduce SpamDam, a SMS spam detection framework designed to overcome key challenges in detecting and understanding SMS spam, such as the lack of public SMS spam…

cs.CR2024★ 3 cited

Enabling Privacy-Preserving Cyber Threat Detection with Federated Learning

Yu Bi, Yekai Li, Xuan Feng +1

Despite achieving good performance and wide adoption, machine learning based security detection models (e.g., malware classifiers) are subject to concept drift and evasive evolutio…