M. Sc. Jonas Sander

Jens Alich, Thomas Eisenbarth, Hossein Hadipour, Gregor Leander, Felix Mächtle, Yevhen Perehuda, Shahram Rasoolzadeh, Jonas Sander, and Cihangir Tezcan,
Attacks and Remedies for Randomness in AI: Cryptanalysis of PHILOX and THREEFRY, 2025. Cryptology ePrint Archive, Paper 2025/2161.

File:

2161

Felix Mächtle, Nils Loose, Jan-Niclas Serr, Jonas Sander, and Thomas Eisenbarth,
AutoStub: Genetic Programming-Based Stub Creation for Symbolic Execution, in Proceedings of the 18th ACM/IEEE International Workshop on Search-Based and Fuzz Testing, SBFT 2025 , 2025.

Qifan Wang, Jonas Sander, Minmin Jiang, Thomas Eisenbarth, and David F. Oswald,
BarkBeetle: Stealing Decision Tree Models with Fault Injection, CoRR , vol. abs/2507.06986, 2025.

DOI:	10.48550/ARXIV.2507.06986
File:	arXiv.2507.06986

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

Felix Mächtle, Jan-Niclas Serr, Nils Loose, Jonas Sander, and Thomas Eisenbarth,
OCEAN: Open-World Contrastive Authorship Identification, in Applied Cryptography and Network Security (ACNS) 2025 , 2025.

Weblink:	https://arxiv.org/abs/2412.05049
Bibtex:	@misc{maechtle2024oceanopenworldcontrastiveauthorship, title={OCEAN: Open-World Contrastive Authorship Identification}, author={Felix Mächtle and Jan-Niclas Serr and Nils Loose and Jonas Sander and Thomas Eisenbarth}, year={2024}, eprint={2412.05049}, archivePrefix={arXiv}, primaryClass={cs.AI}, url={https://arxiv.org/abs/2412.05049}, }

Felix Mächtle, Ashwath Shetty, Jonas Sander, Nils Loose, Sören Pirk, and Thomas Eisenbarth,
Prompt Pirates Need a Map: Stealing Seeds helps Stealing Prompts, 2025.

Weblink:	https://arxiv.org/pdf/2509.09488
Bibtex:	@misc{maechtle2025promptpirates, title={Prompt Pirates Need a Map: Stealing Seeds helps Stealing Prompts}, author={Felix Mächtle and Ashwath Shetty and Jonas Sander and Nils Loose and Sören Pirk and Thomas Eisenbarth}, year={2025}, eprint={2509.09488}, archivePrefix={arXiv}, primaryClass={cs.CR}, url={https://arxiv.org/abs/2509.09488}, }

Felix Maurer, Jonas Sander, and Thomas Eisenbarth,
ReDASH: Fast and Efficient Scaling in Arithmetic Garbled Circuits for Secure Outsourced Inference, in Applied Cryptography and Network Security Workshops - ACNS 2025 Satellite Workshops: AIHWS, AIoTS, QSHC, SCI, PrivCrypt, SPIQE, SiMLA, and CIMSS 2025, Munich, Germany, June 23-26, 2025, Revised Selected Papers, Part III , Mark Manulis, Eds. Springer, 2025. pp. 43—51.

DOI:	10.1007/978-3-032-01823-6_3
File:	978-3-032-01823-6_3

Jonas Sander, and Thomas Eisenbarth,
Silenzio: Secure Non-Interactive Outsourced MLP Training, CoRR , vol. abs/2504.17785, 2025.

DOI:	10.48550/ARXIV.2504.17785
File:	arXiv.2504.17785

Roland Stenger, Steffen Busse, Jonas Sander, Thomas Eisenbarth, and Sebastian Fudickar,
Evaluating the Impact of Face Anonymization Methods on Computer Vision Tasks: A Trade-off Between Privacy and Utility, IEEE Access , pp. 1-1, 2024.

DOI:	10.1109/ACCESS.2024.3519441
Weblink:	https://ieeexplore.ieee.org/document/10804775
File:	ACCESS.2024.3519441

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