3 papers
cs.CR2025
Defeating Cerberus: Concept-Guided Privacy-Leakage Mitigation in Multimodal Language Models
Boyang Zhang, Istemi Ekin Akkus, Ruichuan Chen +4
Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in processing and reasoning over diverse modalities, but their advanced abilities also raise sign…
cs.DC2024
Protecting Confidentiality, Privacy and Integrity in Collaborative Learning
Dong Chen, Alice Dethise, Istemi Ekin Akkus +6
A collaboration between dataset owners and model owners is needed to facilitate effective machine learning (ML) training. During this collaboration, however, dataset owners and mod…
cs.CR2024
Model Hijacking Attack in Federated Learning
Zheng Li, Siyuan Wu, Ruichuan Chen +6
Machine learning (ML), driven by prominent paradigms such as centralized and federated learning, has made significant progress in various critical applications ranging from autonom…