M. Sc. Ida Bruhns

Jonas Sander, Sebastian Berndt, Ida Bruhns, and Thomas Eisenbarth,
Dash: Accelerating Distributed Private Convolutional Neural Network Inference with Arithmetic Garbled Circuits, IACR Transactions on Cryptographic Hardware and Embedded Systems , vol. 2025, pp. 420-449, 2025. IACR.

DOI:	10.46586/tches.v2025.i1.420-449

Ida Bruhns, Sebastian Berndt, Jonas Sander, and Thomas Eisenbarth,
Slalom at the Carnival: Privacy-preserving Inference with Masks from Public Knowledge, IACR Commun. Cryptol. , vol. 1, no. 3, pp. 40, 2024.

DOI:	10.62056/AKP-49QGXQ
File:	akp-49qgxq

Samira Briongos, Ida Bruhns, Pedro Malagón, Thomas Eisenbarth, and José Manuel Moya,
Aim, Wait, Shoot: How the CacheSniper Technique Improves Unprivileged Cache Attacks, in IEEE European Symposium on Security and Privacy, EuroS&P 2021 , IEEE, 2021. pp. 683-700.

DOI:	10.1109/EuroSP51992.2021.00051
Weblink:	https://doi.ieeecomputersociety.org/10.1109/EuroSP51992.2021.00051

Saad Islam, Ahmad Moghimi, Ida Bruhns, Moritz Krebbel, Berk Gulmezoglu, Thomas Eisenbarth, and Berk Sunar,
SPOILER: Speculative Load Hazards Boost Rowhammer and Cache Attacks, in 28th USENIX Security Symposium (USENIX Security 19) , Santa Clara, CA: USENIX Association, 2019. pp. 621-637.

ISBN:	978-1-939133-06-9
File:	islam