IPFed: Identity protected federated learning for user authentication

no code implementations • 7 May 2024 • Yosuke Kaga, Yusei Suzuki, Kenta Takahashi

Experiments on face image datasets show that IPFed can protect the privacy of personal data while maintaining the accuracy of the state-of-the-art method.

Federated Learning Privacy Preserving

PDH : Probabilistic deep hashing based on MAP estimation of Hamming distance

no code implementations • 21 May 2019 • Yosuke Kaga, Masakazu Fujio, Kenta Takahashi, Tetsushi Ohki, Masakatsu Nishigaki

In recent years, various hashing methods based on deep neural networks have been proposed and achieved higher precision than the other hashing methods.

Deep Hashing Image Retrieval

Cancelable Indexing Based on Low-rank Approximation of Correlation-invariant Random Filtering for Fast and Secure Biometric Identification

no code implementations • 5 Apr 2018 • Takao Murakami, Tetsushi Ohki, Yosuke Kaga, Masakazu Fujio, Kenta Takahashi

Furthermore, existing biometric indexing schemes cannot be used in conjunction with template protection schemes to speed up biometric identification, since a biometric index leaks some information about the original feature.