4 papers
Training-Free Private Synthesis with Validation: A New Frontier for Practical Educational Data Sharing
Hibiki Ito, Chia-Yu Hsu, Hiroaki Ogata
While secondary use of real-world data (RWD) in education offers substantial research opportunities, data sharing is often limited by privacy constraints. Differentially private sy…
Cyclic Adaptive Private Synthesis for Sharing Real-World Data in Education
Hibiki Ito, Chia-Yu Hsu, Hiroaki Ogata
The rapid adoption of digital technologies has greatly increased the volume of real-world data (RWD) in education. While these data offer significant opportunities for advancing le…
Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning
Marlon Tobaben, Hibiki Ito, Joonas Jälkö +2
Membership inference attacks (MIAs) are used to test practical privacy of machine learning models. MIAs complement formal guarantees from differential privacy (DP) under a more rea…
The Third-Party Access Effect: An Overlooked Challenge in Secondary Use of Educational Real-World Data
Hibiki Ito, Chia-Yu Hsu, Hiroaki Ogata
Secondary use of growing real-world data (RWD) in education offers significant opportunities for research, yet privacy practices intended to enable third-party access to such RWD a…