The 4th IEEE International Congress on AI Privacy and Protection

With the development of Artificial Intelligence (AI) technology, many AI-enabled algorithms have deeply changed our daily lives. Reinforcement Learning (RL) algorithms are intensively studied in recent years especially on advocated game domains. There are several highlights of the numerous studies of RL in various game domains presented in the very recent years. However, there are also other research works shown that the RL can be applied on many other research topics. Thus, we held this symposium on drawing a larger perpsective on what we have learned from studying RL.

The conference proceedings will be published by IEEE xplore to be indexed by EI Compendex, Web of Science, and Scopus.

Call for Papers

Artificial Intelligence (AI) has been developing rapidly and shown us a great potential in the past decades. Today, many AI-enabled algorithms have deeply changed our daily lives. However, it is well known that novel privacy issues are still remaining in the AI systems. Moreover, such privacy issues still exist when applying AI to real-world scenarios. To investigate such issues in AI systems, we held this congress on drawing a larger perpsective on the state-of-the-art research on the privacy issues in AI systems.

IEEE ICAPP 2022 aims to collect recent academic achievements in novel techniques, developments, empirical studies, and new developments in AI privacy research. Innovative applications to protect the privacy issues in AI are highly encouraged. The objective of IEEE ICAPP 2022 is to provide a forum for scientists, engineers, and researchers to discuss and exchange their new ideas, novel results, work in progress and experience on all aspects of AI privacy research. Topics of particular interest include, but are not limited to:

  • Privacy of AI techniques
  • Novel algorithms and applications related to AI privacy
  • Other machine learning algorithms and applications
  • Adversarial examples of deep neural network systems
  • Backdoor attack and defense of AI systems
  • Privacy on federated learning systems


Submissions should include abstract, 5-10 keywords, and the e-mail address of the corresponding author and be in PDF format. Each submission should be in the IEEE 8.5 x 11 inches two-column format with 10-12 point font (Template: DOC or LaTeX), including tables, figures, and references.

Organization Commitees

  • General Chair
  • Meikang Qiu, Texas A&M University, USA
  • Program Chair
  • Cheng Zhang, Waseda University, Japan
  • Technical Program Committee
  • Weipeng Cao, Shenzhen University, China
  • Petr Matousek, Brno University of Technology, Czechia
  • Xiaofu He, Columbia University Medical Center, USA
  • Qiang Wang, Southern University of Science and Technology, China
  • Peng Gou, DNVGL Software, Norway
  • Yongxin Zhu, Shanghai Jiaotong University, China
  • Han Qiu, Telecom Paris, France
  • Junjie Peng, Shanghai University, China
  • Denis Trystram, Grenoble university, France
  • Guangjie Han, Beihang University, China


If you have any questions or queries on ICAPP 2022, please contact us via an email.











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