Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning. - Tanveer Khan; Khoa Nguyen 005; Antonis Michalas (EDBT/ICDT Workshops, 2023)

A More Secure Split: Enhancing the Security of Privacy-Preserving Split Learning. - Tanveer Khan; Khoa Nguyen 005; Antonis Michalas (NordSec, 2023)

Love or Hate? Share or Split? Privacy-Preserving Training Using Split Learning and Homomorphic Encryption. - Tanveer Khan; Khoa Nguyen 005; Antonis Michalas; Alexandros Bakas (PST, 2023)

Split Without a Leak: Reducing Privacy Leakage in Split Learning. - Khoa Nguyen 005; Tanveer Khan; Antonis Michalas (SecureComm (2), 2023)

A Pervasive, Efficient and Private Future: Realizing Privacy-Preserving Machine Learning Through Hybrid Homomorphic Encryption. - Khoa Nguyen 005; Mindaugas Budzys; Eugene Frimpong; Tanveer Khan; Antonis Michalas (DASC, 2024)

GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption. - Eugene Frimpong; Khoa Nguyen 005; Mindaugas Budzys; Tanveer Khan; Antonis Michalas (SAC, 2024)

Wildest Dreams: Reproducible Research in Privacy-preserving Neural Network Training. - Tanveer Khan; Mindaugas Budzys; Khoa Nguyen 005; Antonis Michalas (CoRR, 2024)

SoK: Wildest Dreams: Reproducible Research in Privacy-preserving Neural Network Training. - Tanveer Khan; Mindaugas Budzys; Khoa Nguyen 005; Antonis Michalas (Proc. Priv. Enhancing Technol., 2024)

A Privacy-Centric Approach: Scalable and Secure Federated Learning Enabled by Hybrid Homomorphic Encryption. - Khoa Nguyen 005; Tanveer Khan; Antonis Michalas (CoRR, 2025)