ÜNAL, Ali Burak; AKGÜN, Mete; PFEIFER, Nico. ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare. Proceedings of the AAAI Conference on Artificial Intelligence, [S. l.], v. 35, n. 11, p. 9988–9996, 2021. DOI: 10.1609/aaai.v35i11.17199. Disponível em: https://ojs.aaai.org/index.php/AAAI/article/view/17199. Acesso em: 13 may. 2026.