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)

Make Split, not Hijack: Preventing Feature-Space Hijacking Attacks in Split Learning. - Tanveer Khan; Mindaugas Budzys; Antonis Michalas (SACMAT, 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)

Split Happens: Combating Advanced Threats with Split Learning and Function Secret Sharing. - Tanveer Khan; Mindaugas Budzys; Antonis Michalas (CoRR, 2025)