Oleksandr Tkachenko M.Sc.
work +49 6151 16-27303
I am a doctoral researcher and member of the Cryptography and Privacy Engineering Group (ENCRYPTO) at the Department of Computer Science of Technische Universität Darmstadt, Germany.
My research focuses on the design and evaluation of compilers for privacy-preserving protocols, and the scalability of these protocols. In addition, my interests include the application of secure multi-party computation for privacy-preserving genome research and data mining.
- Since 2017/10 Doctoral Researcher at ENCRYPTO
- 2020/07 – 2020/10 Research Internship at Google
- 2016/01 – 2017/09 Student Research Assistant at ENCRYPTO
- 2015/08 – 2015/11 Student Research Assistant at Fraunhofer SIT, Germany
- 2014/12 – 2015/07 Student Research Assistant at FSR Institute, Technical University of Darmstadt, Germany
CORE A/A* ranked venues marked in bold.
Lennart Braun, Daniel Demmler, Thomas Schneider, and Oleksandr Tkachenko. MOTION - a framework for mixed-protocol multi-party computation. Cryptology ePrint Archive, Report 2020/1137, September 18, 2020. https://ia.cr/2020/1137. Code: https://encrypto.de/code/MOTION.
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 Information, 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 B. [ 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. 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. Workshop der Fachgruppe Kryptographie in der Gesellschaft für Informatik (Kryptotag), 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 Information, Computer and Communications Security (ASIACCS'18), pages 221–235, ACM, Songdo, South Korea, June 4-8, 2018. Acceptance rate 16.8%. CORE rank B. [ 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 Information, 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 B. [ 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. ÐœÐµÑ‚Ð¾Ð´Ð¸ Ð°Ð´Ð°Ð¿Ñ‚Ð¸Ð²Ð½Ð¾i Ñ„iÐ»ÑŒÑ‚Ñ€Ð°Ñ†iÑ— Ð² ÑÐ¸ÑÑ‚ÐµÐ¼Ð°Ñ… Ð¼Ð¾Ð²Ð½Ð¾Ð³Ð¾ Ð²Ð²Ð¾Ð´Ñƒ. Master's thesis, Kherson National Technical University, Ukraine, Aril, 2016.