On May 4, 2022, our Faculty specially invited Professor Hong Shen of Sun Yat-sen University as the speaker to give a lecture titled Privacy-preserving Data Sharing against Malicious Attacks.

During the lecture, Professor Shen led the students to review Cyber ​​Attacks with the main characteristics of Discover Privacy, Disable Software and Damage Hardware from a global perspective, and combined cases of different privacy security attacks using Adversary Models, respectively. Describes the difference between Semi-honest adversary – passive inference and Malicious adversary – active inference.

Professor Shen explained the definition of privacy-preserving computing and explained that the key to the deployment of privacy-preserving computing is to ensure that the data released in the cloud has a high degree of privacy protection and utility. He also proposed that today's cloud data sharing security has important implications for the security environment, heterogeneous computing protection, and communication channels. And big data privacy protection faces higher challenges. Facing existing technical challenges, Professor Shen conducted two case studies focusing on differential privacy applications. Firstly, Professor Shen's team proposed a partition probabilistic neighbor selection strategy to address the collusion attack problem of active inference. Secondly, it optimized the previous privacy-preserving k-means clustering related algorithms and proposed differential private k-means clustering with guaranteed convergence. The algorithm improves defense measures against inference attacks on individual privacy.

Professor Shen and his team have achieved key research results in the field of data sharing security and have published 13 top journal papers so far. Through on-site demonstration analysis, Professor Shen combined cutting-edge research theories with practical cases and explained in detail privacy protection measures under data sharing. This lecture was vivid and profound, inspiring students to think about privacy protection security, and laying a solid foundation for students' subsequent academic research on privacy protection. In recent years, the privacy and security protection of shared data has also become an important research area of ​​our school. Our school actively carries out diversified professional academic lectures to improve the academic ability of graduate students.