In recent years, the Ubiquitous Privacy Lab, led by Associate Professor Li Meng from our school, has conducted in-depth research on data security and privacy protection in the fields of vehicular networks and cloud computing, achieving a series of research outcomes. One of these outcomes, titled "Privacy-Preserving Traffic Monitoring with False Report Filtering via Fog-assisted Vehicular Crowdsensing," was published in the CCF A-recommended journal IEEE TSC (IEEE Transactions on Services Computing) and was awarded the IEEE-CCF Cloud Computing Best Paper Award on September 13, 2024. This research outcome was a collaboration with Beijing Institute of Technology and the University of Guelph, leveraging cryptography, cloud computing, and edge computing to address the challenge of securely filtering false traffic information in vehicular network traffic monitoring scenarios.

To enhance the international influence of Chinese scientists and engineers in the field of cloud computing, promote international cooperation and exchange, and jointly drive the development of cloud computing theory and technology, the IEEE Technical Community on Cloud Computing and the CCF Service Computing Professional Committee jointly launched the "IEEE-CCF Cloud Computing Outstanding Paper Award" selection activity. The aim is to boost the international influence of Chinese researchers in the field of service computing, facilitate international cooperation and exchange, and jointly promote the development of service computing theory and technology.