EL MESTARI, S. Z., LENZINI, G., & DEMIRCI, H. (February 2024). Preserving data privacy in machine learning systems. Computers and Security, 137, 103605. doi:10.1016/j.cose.2023.103605 Peer reviewed |
Arenas Correa, M. P., Bingol, M. A., Demirci, H., Fotiadis, G., & Lenzini, G. (06 October 2022). A Secure Authentication Protocol for Cholesteric Spherical Reflectors using Homomorphic Encryption. Lecture Notes in Computer Science, 13503, 23. doi:10.1007/978-3-031-17433-9_18 Peer reviewed |
Arenas Correa, M. P., Demirci, H., & Lenzini, G. (24 February 2022). An Analysis of Cholesteric Spherical Reflector Identifiers for Object Authenticity Verification. Machine Learning and Knowledge Extraction, 4 (1), 222-239. doi:10.3390/make4010010 Peer Reviewed verified by ORBi |
Demirci, H., & Lenzini, G. (2022). Privacy-preserving Copy Number Variation Analysis with Homomorphic Encryption [Paper presentation]. 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Scale-IT-up. doi:10.5220/0011012400003123 |
Demirci, H., & Alves, R. (22 November 2021). Enhancing acetic acid and 5‐hydroxymethyl furfural tolerance of C. saccharoperbutylacetonicum through adaptive laboratory evolution. Process Biochemistry, 101, 179-189. doi:10.1016/j.procbio.2020.11.013 Peer reviewed |
Arenas Correa, M. P., Demirci, H., & Lenzini, G. (17 August 2021). Cholesteric Spherical Reflectors as Physical Unclonable Identifiers in Anti-counterfeiting. Journal of the Association for Computing Machinery, 16, 11. doi:10.1145/3465481.3465766 Peer reviewed |