Name:Tiegang Gao
Title: Prof.
Education:Doctor
Major:Software Engineering
Email:gaotiegang@nankai.edu.cn
Research direction:Information Security; Software Engineering; Digital Image Processing
Education and Work experience
Tiegang Gao received the Ph. D. degree, Master’s degreeand Bachelor’s degreein operational research and cybernetics from the Nankai University, Tianjin, China, in 2005, Huazhong University of Science and Technology in 1990 and Hebei Teacher’s University in 1988, respectively.
Achievements
Tiegang Gaois currently a professor with the College of Software, Nankai University, Tianjin, China. His research interests include information security, software engineering, image processing. He has authored/coauthored more than 100 papers in related areas, he has been selected highly cited Chinese researchers from 2014-2019.
Publications(Some recently published papers)
1.A lossless self-recovery watermarking scheme with JPEG-LS compression，Journal of Information Security and Applications58 (2021) 102733
2.High capacity reversible data hiding in encrypted image based on image encoding and POB，Journal of the Franklin Institute357 (2020) 9107–9126
5.Double color images compression–encryption via compressive sensing.Neural computing & Application(2021).https://doi.org/10.1007/s00521-021-05921-y
3.DetectPMFL: Privacy-Preserving Momentum Federated Learning Considering Unreliable Industrial Agents,IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2022.3140806.
4.Privacy-enhanced momentum federated learning via differential privacy and chaotic system in industrial Cyber–Physical systems,ISA Transactions, DOI: 10.1016/j.isatra.2021.09.007
5.Hachimoji DNA-based reversible blind color images hiding using Julia set and SVD，Neural Computing andApplications,34(5)(2022) 3811–3827.
6.A secure dual-color image watermarking scheme based 2D DWT, SVD and Chaotic map，Multimedia Tools andApplications, 81(5) (2022) 6159–6190.
7.A secure lossless recovery for medical images based on image encoding and data self-embedding,Cluster Computing,https://doi.org/10.1007/s10586-021-03446-6
8.SVeriFL: Successive verifiable federated learning withprivacy-preserving,Information Sciences 622 (2023) 98–114
