CORE A/A* ranked venues marked in bold.
Yaniv Ben-Itzhak, Helen Möllering, Benny Pinkas, Thomas Schneider, Ajith Suresh, Oleksandr Tkachenko, Shay Vargaftik, Christian Weinert, Hossein Yalame, and Avishay Yanai. ScionFL: Secure quantized aggregation for federated learning. In 2. IEEE Conference on Secure and Trustworthy Machine Learning (SaTML'24), IEEE, Toronto, Canada, April 9-11, 2024. To appear. Runner-up distinguished paper award. Online: https://arxiv.org/abs/2210.07376. [ pdf | web ]
Hannah Keller, Helen Möllering, Thomas Schneider, Oleksandr Tkachenko, and Liang Zhao. Secure noise sampling for DP in MPC with finite precision. Cryptology ePrint Archive, Report 2023/1594, October 17, 2023. https://ia.cr/2023/1594.
Lennart Braun, Moritz Huppert, Nora Khayata, Thomas Schneider, and Oleksandr Tkachenko. FUSE - Flexible file format and intermediate representation for secure multi-party computation. In 18. ACM ASIA Conference on Computer and Communications Security (ASIACCS'23), pages 649–663, ACM, Melbourne, Australia, July 10-14, 2023. Full version: https://ia.cr/2023/563. Code: https://encrypto.de/code/FUSE. Acceptance rate 17.3%. CORE rank A. [ DOI | pdf | web ]
Lennart Braun, Moritz Huppert, Nora Khayata, Thomas Schneider, and Oleksandr Tkachenko. CONTRIBUTED TALK: FUSE - Flexible file format and intermediate representation for secure multi-party computation. 9. Theory and Practice of Multi-Party Computation Workshop (TPMPC'23), June 8-9, 2023. [ web ]
Kay Hamacher, Tobias Kussel, Thomas Schneider, and Oleksandr Tkachenko. PEA: Practical private epistasis analysis using MPC. In 27. European Symposium on Research in Computer Security (ESORICS'22), volume 13556 of LNCS, pages 320–339, Springer, Copenhagen, Denmark, September 26-30, 2022. Full version: https://ia.cr/2022/1185. Acceptance rate 18.5%. CORE rank A. [ DOI | pdf | web ]
Oleksandr Tkachenko. Towards Deployable MPC: Flexible and Efficient Tools for Real-World Applications. PhD thesis, TU Darmstadt, Germany, July 21, 2022. [ pdf ]
Lennart Braun, Daniel Demmler, Thomas Schneider, and Oleksandr Tkachenko. MOTION - A framework for mixed-protocol multi-party computation. ACM Transactions on Privacy and Security (TOPS), 25(2):8:1–8:35, March 4, 2022. Online: https://ia.cr/2020/1137. Code: https://encrypto.de/code/MOTION. CORE rank A. [ DOI | pdf | web ]
Tim Heldmann, Thomas Schneider, Oleksandr Tkachenko, Christian Weinert, and Hossein Yalame. LLVM-based circuit compilation for practical secure computation. In 19. International Conference on Applied Cryptography and Network Security (ACNS'21), volume 12727 of LNCS, pages 99–121, Springer, Virtual Event, June 21-24, 2021. Online: https://ia.cr/2021/797. Code: https://encrypto.de/code/LLVM. Acceptance rate 19.9%. CORE rank B. [ DOI | pdf | web ]
Kimmo Järvinen, Ágnes Kiss, Thomas Schneider, Oleksandr Tkachenko, and Zheng Yang. Faster privacy-preserving location proximity schemes for circles and polygons. IET Information Security, 14(3):254–265, May, 2020. CORE rank C. [ DOI | pdf | web ]
Robert Nikolai Reith, Thomas Schneider, and Oleksandr Tkachenko. Efficiently stealing your machine learning models. In 18. Workshop on Privacy in the Electronic Society (WPES'19), pages 198–210, ACM, London, UK, November 11, 2019. Acceptance rate 20.9%. [ DOI | pdf | web ]
Thomas Schneider and Oleksandr Tkachenko. EPISODE: Efficient Privacy-PreservIng Similar Sequence Queries on Outsourced Genomic DatabasEs. In 14. ACM ASIA Conference on Computer and Communications Security (ASIACCS'19), pages 315–327, ACM, Auckland, New Zealand, July 7-12, 2019. Online: https://ia.cr/2021/029. Acceptance rate 17.1%. CORE rank A. [ DOI | pdf | web ]
Kimmo Järvinen, Helena Leppäkoski, Elena Simona Lohan, Philipp Richter, Thomas Schneider, Oleksandr Tkachenko, and Zheng Yang. PILOT: Practical privacy-preserving Indoor Localization using OuTsourcing. In 4. IEEE European Symposium on Security and Privacy (EuroS&P'19), pages 448–463, IEEE, Stockholm, Sweden, June 17-19, 2019. Acceptance rate 20.0%. [ DOI | pdf | web ]
Benny Pinkas, Thomas Schneider, Oleksandr Tkachenko, and Avishay Yanai. Efficient circuit-based PSI with linear communication. In 38. Advances in Cryptology - EUROCRYPT'19, volume 11478 of LNCS, pages 122–153, Springer, Darmstadt, Germany, May 19-23, 2019. Online: https://ia.cr/2019/241. Code: https://encrypto.de/code/OPPRF-PSI. Acceptance rate 23.2%. CORE rank A*. [ DOI | pdf | web ]
Oleksandr Tkachenko and Thomas Schneider. Towards efficient privacy-preserving similar sequence queries on outsourced genomic databases. In 17. Workshop on Privacy in the Electronic Society (WPES'18), pages 71–75, ACM, Toronto, Canada, October 15, 2018. Short paper. Acceptance rate 36.5%. [ DOI | pdf | web ]
Kimmo Järvinen, Ágnes Kiss, Thomas Schneider, Oleksandr Tkachenko, and Zheng Yang. Faster privacy-preserving location proximity schemes. In 17. International Conference on Cryptology And Network Security (CANS'18), volume 11124 of LNCS, pages 3–22, Springer, Naples, Italy, September 30-October 3, 2018. Full version: https://ia.cr/2018/694. Acceptance rate 32.9%. CORE rank B. [ DOI | pdf | web ]
Oleksandr Tkachenko. Privacy-preserving genomics on a large scale. In 29. Kryptotag (crypto day matters), Gesellschaft für Informatik e.V. / FG KRYPTO, Bosch Renningen, Germany, September 6-7, 2018.
Philipp Richter, Zheng Yang, Oleksandr Tkachenko, Helena Leppäkoski, Kimmo Järvinen, Thomas Schneider, and Elena Simona Lohan. Received signal strength quantization for secure indoor positioning via fingerprinting. In 8. International Conference on Localization and GNSS (ICL-GNSS'18), pages 1–6, IEEE, Guimarães, Portugal, June 26-28, 2018. [ DOI | pdf | web ]
Oleksandr Tkachenko, Christian Weinert, Thomas Schneider, and Kay Hamacher. Large-scale privacy-preserving statistical computations for distributed genome-wide association studies. In 13. ACM ASIA Conference on Computer and Communications Security (ASIACCS'18), pages 221–235, ACM, Songdo, South Korea, June 4-8, 2018. Acceptance rate 16.8%. CORE rank A. [ DOI | pdf | web ]
M. Sadegh Riazi, Christian Weinert, Oleksandr Tkachenko, Ebrahim M. Songhori, Thomas Schneider, and Farinaz Koushanfar. Chameleon: A hybrid secure computation framework for machine learning applications. In 13. ACM ASIA Conference on Computer and Communications Security (ASIACCS'18), pages 707–721, ACM, Songdo, South Korea, June 4-8, 2018. Preliminary version: https://ia.cr/2017/1164. Acceptance rate 16.8%. CORE rank A. [ DOI | pdf | web ]
Oleksandr Tkachenko. Large-scale privacy-preserving statistical computations for distributed genome-wide association studies. Master's thesis, TU Darmstadt, Germany, September 12, 2017.
Oleksandr Tkachenko. Methods of adaptive filtering in speech input systems. Master's thesis, Kherson National Technical University, Ukraine, April, 2012.