Company Filing History:
Years Active: 2017-2023
Title: Yu-Hsuan Pan: Innovator in Data Anonymity
Introduction
Yu-Hsuan Pan is a prominent inventor based in Taipei, Taiwan. He has made significant contributions to the field of data anonymity, focusing on methods and systems that enhance data privacy. With a total of 3 patents to his name, Pan is recognized for his innovative approaches to data protection.
Latest Patents
Yu-Hsuan Pan's latest patents include a data anonymity method and a data anonymity system. The data anonymity method involves obtaining a data set that includes direct-identifiers, quasi-identifiers, and event logs. The method replaces the content of direct-identifiers with pseudonyms and classifies quasi-identifiers using a group-by algorithm with k-anonymity. Additionally, it links activities to timestamps to create event sequences, which are then grouped according to a similarity hierarchy tree. This process ensures that the event sequences are generalized while maintaining privacy.
Another notable patent is the data de-identification method, which includes a data de-identification apparatus and a non-transitory computer-readable storage medium. This method involves obtaining original data with identification, condition, and record fields. It extracts event fragment sequences based on identification data and conditions, ultimately adjusting the sequence data to produce de-identification data.
Career Highlights
Yu-Hsuan Pan is affiliated with the Industrial Technology Research Institute, where he continues to develop innovative solutions in data privacy. His work has garnered attention for its practical applications in protecting sensitive information.
Collaborations
Pan collaborates with notable colleagues, including Ming-Chih Kao and Pang-Chieh Wang, who contribute to his research and development efforts.
Conclusion
Yu-Hsuan Pan is a key figure in the realm of data anonymity, with a focus on innovative methods that enhance data privacy. His contributions are vital in addressing the growing concerns surrounding data security in today's digital landscape.