PCDS 2024 is the 10th of a conference series started in 2015, which is dedicated to research on privacy computing and data security. The conference provides a forum for researchers, engineers and practitioners in academia, industry and the public sector around the world to report latest research work and exchange ideas in all aspects of privacy computing and data security, including those for improving the efficiency, performance, reliability, and interoperability of privacy computing and data security systems.

Following the traditions of the previous successful PriComp conferences held in Fuzhou, China (2015); Qingdao, China (2016); Melbourne, Australia (2017); Boppard, Germany (2018); Canterbury, UK (2019); Hainan, China (2020) and Xi’an, Shanghai, China (online, 2021); PriComp 2024 will be held in Momi Bay, Fiji. PriComp 2024 will focus on an evolving pathway from privacy protection to privacy computing, by serving as an international premier forum for engineers and scientists in academia, industry, and government to address the resulting profound challenges and to present and discuss their new ideas, research results, applications and experience on all aspects of privacy computing. The conference of PriComp 2024 is co-organized by Chinese Information Processing Society of China, Institute of Information Engineering, CAS, and Hainan University.

The IEEE PriComp-2024 focuses on privacy protection and privacy computing. Topics of interest include, but are not limited to the following:

Theories and foundations for privacy computing
Programming languages and compilers for privacy computing
Privacy computing models
Privacy metrics and formalization
Privacy taxonomies and ontologies
Privacy information management and engineering
Privacy operation and modeling
Data utility and privacy loss
Cryptography for privacy protection
Privacy protection based information hiding and sharing
Data analytics oriented privacy control and protection
Privacy-aware information collection
Privacy sensing and distribution
Combined and comprehensive privacy protection
Privacy-preserving data publishing
Private information storage
Private integration and synergy
Private information exchange and sharing
Privacy inference and reasoning
Internet and web privacy
Cloud privacy
Social media privacy
Mobile privacy
Location privacy
IoT privacy
Behavioral advertising
Privacy in large ecosystems such as smart cities
Privacy of AI models and systems
AI for privacy computing
Privacy and blockchain
User-centric privacy protection solutions
Human factors in privacy computing
Privacy nudging
Automated solutions for privacy policies and notices
Legal issues in privacy computing and other interdisciplinary topics