Workshop on Data Security and Privacy Preservation

Topics:

Privacy-Preserving Machine Learning
Data Encryption and Access Control
Al Model Security
Secure Knowledge Representation
Privacy in Large Language Models (LLMs)
Secure Data Sharing and Collaboration
Anomaly Detection in Data Streams
Automated Privacy Policy
Secure Data Provenance and Lineage
Privacy Risk Assessment Frameworks
Secure Multi-Party Computation for Al
Privacy Preservation in Edge Al Computing
Differential Privacy in Reinforcement Learning
Privacy-Preserving Data Synthesis and Augmentation
Ethical Al Design for Privacy Protection
Privacy-Enhanced Natural Language Processing

The criteria for assessment will include:

– Relevance to conference vision/topics and attendees
– Potential to bring in participants to the conference from different audiences
– Overall quality of contribution
– Provides a hands-on, collaborative, and/or active learning environment for attendees

Workshop publication

Accepted and presented papers will be published alongside the main conference proceedings as a sub section/chapter. Paper formats should, therefore, correspond to the templates of the publisher of the main conference.

Organizers

Xiangyun Tang received the B.Eng. degree in Computer Science from Minzu University of China, Beijing, China, in 2016, and the Ph.D. degree in Cyberspace Security from the Beijing Institute of Technology, Beijing, in 2022. She is currently an Assistant Professor in the School of Information Engineering at Minzu University of China. Her research interests include secure multiparty computation and machine learning security. Dr. Tang was the recipient of the Best Paper Award at IEEE ICBCTIS 2023 and the Outstanding Paper Award at IEEE IoT 2023. She has served as a guest editor for multiple journals and as a TPC chair and program committee member for various international conferences and workshops.