SPGC: An Integrated Framework of Secure Computation and Differential Privacy for Collaborative Learning. - Kazuki Iwahana; Naoto Yanai; Jason Paul Cruz; Toru Fujiwara (DPM/CBT@ESORICS, 2021)

MADMAX: Browser-Based Malicious Domain Detection Through Extreme Learning Machine. - Kazuki Iwahana; Tatsuya Takemura; Ju Chien Cheng; Nami Ashizawa; Naoki Umeda; Kodai Sato; Ryota Kawakami; Rei Shimizu; Yuichiro Chinen; Naoto Yanai (IEEE Access, 2021)

First to Possess His Statistics: Data-Free Model Extraction Attack on Tabular Data. - Masataka Tasumi; Kazuki Iwahana; Naoto Yanai; Katsunari Shishido; Toshiya Shimizu; Yuji Higuchi; Ikuya Morikawa; Jun Yajima (CoRR, 2021)

MOTUS: How Quantized Parameters Improve Protection of Model and Its Inference Input. - Hiromasa Kitai; Naoto Yanai; Kazuki Iwahana; Masataka Tatsumi; Jason Paul Cruz (SecITC, 2022)

SPGC: Integration of Secure Multiparty Computation and Differential Privacy for Gradient Computation on Collaborative Learning. - Kazuki Iwahana; Naoto Yanai; Jason Paul Cruz; Toru Fujiwara (J. Inf. Process., 2022)

Can Inputs' Reconstruction Information Be Coded into Machine Learning Model's Outputs? - Kazuki Iwahana; Osamu Saisho; Takayuki Miura; Akira Ito 002 (ESORICS Workshops (2), 2023)

Backdoor Attacks Leveraging Latent Representation in Competitive Learning. - Kazuki Iwahana; Naoto Yanai; Toru Fujiwara (ESORICS Workshops (2), 2023)

Sandbox AI: We Don't Trust Each Other but Want to Create New Value Efficiently Through Collaboration Using Sensitive Data. - Osamu Saisho; Keiichiro Kashiwagi; Sakiko Kawai; Kazuki Iwahana; Koki Mitani (UbiComp/ISWC Adjunct, 2023)

A Study on Quantized Parameters for Protection of a Model and Its Inference Input. - Hiromasa Kitai; Naoto Yanai; Kazuki Iwahana; Masataka Tatsumi; Jason Paul Cruz (J. Inf. Process., 2023)

SETSUBUN: Revisiting Membership Inference Game for Evaluating Synthetic Data Generation. - Takayuki Miura; Masanobu Kii; Toshiki Shibahara; Kazuki Iwahana; Tetsuya Okuda; Atsunori Ichikawa; Naoto Yanai (J. Inf. Process., 2024)

Efficient Privacy-Preserving Data Annotation via Active PrivBayes Synthetic Data Generation. - Osamu Saisho; Takayuki Miura; Kazuki Iwahana; Masanobu Kii; Rina Okada (PerCom Workshops, 2025)

Backdoor Attacks by Leveraging Latent Representation in Competitive Learning for Resistance to Removal. - Kazuki Iwahana; Naoto Yanai; Atsuo Inomata; Toru Fujiwara (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2025)