Thomas Prantl - Chair of Computer Science II

Dr. rer. nat. Thomas Prantl

Chair of Software Engineering (Informatik II)
Department of Computer Science University of Würzburg
Am Hubland, 97074 Würzburg
Informatikgebäude, 1.OG, Room A118
Email: thomas.prantl@uni-wuerzburg.de

Research Interests

Security
Blockchain
IoT
Security and Blockchain Benchmarking

Selected Publications:

Benchmarking secure multiparty computation frameworks for real-world workloads in diverse network settings. Harth-Kitzerow, Christopher; Schiller, Jonas; Schwanke, Nina; Prantl, Thomas; Carle, Georg; in Journal of Information Security and Applications (2026). 102(7) 104571.
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Secure Multiparty Computation (MPC) enables distributed parties to jointly evaluate functions over their combined datasets while preserving the confidentiality of their individual data. Although MPC protocols and frameworks have achieved significant performance improvements in recent years, particularly for complex workloads like secure neural network inference, systematic standardization and benchmarking of these frameworks remain underexplored. This work comprehensively analyzes 65 MPC applications to identify the most common core algorithmic structures in real-world MPC applications. From this analysis, we derive six reference use cases and implement them across four state-of-the-art MPC frameworks: HPMPC, MPyC, MP-SPDZ, and MOTION. We develop an open-source benchmarking framework that evaluates these implementations under varying security settings and network conditions, including bandwidth constraints, latency, packet loss, and input sizes. Using our framework, we conduct a comprehensive analysis that offers new insights into the practical capabilities of MPC. We also deliver evidence-based recommendations for selecting appropriate frameworks across various operational scenarios.

@article{Sardine_MPC_Munich, abstract = {Secure Multiparty Computation (MPC) enables distributed parties to jointly evaluate functions over their combined datasets while preserving the confidentiality of their individual data. Although MPC protocols and frameworks have achieved significant performance improvements in recent years, particularly for complex workloads like secure neural network inference, systematic standardization and benchmarking of these frameworks remain underexplored. This work comprehensively analyzes 65 MPC applications to identify the most common core algorithmic structures in real-world MPC applications. From this analysis, we derive six reference use cases and implement them across four state-of-the-art MPC frameworks: HPMPC, MPyC, MP-SPDZ, and MOTION. We develop an open-source benchmarking framework that evaluates these implementations under varying security settings and network conditions, including bandwidth constraints, latency, packet loss, and input sizes. Using our framework, we conduct a comprehensive analysis that offers new insights into the practical capabilities of MPC. We also deliver evidence-based recommendations for selecting appropriate frameworks across various operational scenarios.}, author = {Harth-Kitzerow, Christopher and Schiller, Jonas and Schwanke, Nina and Prantl, Thomas and Carle, Georg}, journal = {Journal of Information Security and Applications}, keywords = {t_journalmagazine}, month = {08}, number = 7, pages = 104571, title = {Benchmarking secure multiparty computation frameworks for real-world workloads in diverse network settings}, volume = 102, year = 2026 }

%0 Journal Article %1 Sardine_MPC_Munich %A Harth-Kitzerow, Christopher %A Schiller, Jonas %A Schwanke, Nina %A Prantl, Thomas %A Carle, Georg %D 2026 %J Journal of Information Security and Applications %N 7 %P 104571 %R 10.1016/j.jisa.2026.104571 %T Benchmarking secure multiparty computation frameworks for real-world workloads in diverse network settings %U https://doi.org/10.1016/j.jisa.2026.104571 %V 102 %X Secure Multiparty Computation (MPC) enables distributed parties to jointly evaluate functions over their combined datasets while preserving the confidentiality of their individual data. Although MPC protocols and frameworks have achieved significant performance improvements in recent years, particularly for complex workloads like secure neural network inference, systematic standardization and benchmarking of these frameworks remain underexplored. This work comprehensively analyzes 65 MPC applications to identify the most common core algorithmic structures in real-world MPC applications. From this analysis, we derive six reference use cases and implement them across four state-of-the-art MPC frameworks: HPMPC, MPyC, MP-SPDZ, and MOTION. We develop an open-source benchmarking framework that evaluates these implementations under varying security settings and network conditions, including bandwidth constraints, latency, packet loss, and input sizes. Using our framework, we conduct a comprehensive analysis that offers new insights into the practical capabilities of MPC. We also deliver evidence-based recommendations for selecting appropriate frameworks across various operational scenarios.
Homomorphic approximation of non-linear activation functions using the CKKS cryptosystem of the OpenFHE library. Engel, Simon; Prantl, Thomas; Horn, Lukas; Bonilla, Rafael; Kounev, Samuel; in Discover Artificial Intelligence (2026). 6(1)
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@article{engel2026homomorphic, author = {Engel, Simon and Prantl, Thomas and Horn, Lukas and Bonilla, Rafael and Kounev, Samuel}, journal = {Discover Artificial Intelligence}, keywords = {t_journalmagazine}, month = {08}, number = 1, publisher = {Springer Science and Business Media LLC}, title = {Homomorphic approximation of non-linear activation functions using the CKKS cryptosystem of the OpenFHE library}, volume = 6, year = 2026 }

%0 Journal Article %1 engel2026homomorphic %A Engel, Simon %A Prantl, Thomas %A Horn, Lukas %A Bonilla, Rafael %A Kounev, Samuel %D 2026 %I Springer Science and Business Media LLC %J Discover Artificial Intelligence %N 1 %R 10.1007/s44163-026-01915-8 %T Homomorphic approximation of non-linear activation functions using the CKKS cryptosystem of the OpenFHE library %V 6
Performance analysis of the homomorphic implementation of K-Means using CKKS. Prantl, Thomas; Amann, Patrick; Horn, Lukas; Engel, Simon; Bauer, Andr{é}; Bonilla, Rafael; Benhnini, Anwar; Kounev, Samuel; in Discover Applied Sciences (2026). 8(7) 744.
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Modern data science requires large amounts of data and computational power to perform effectively. However, there is a lot of sensitive data that should not be shared with others. To still do data science, methods like Homomorphic Encryption exist that enable calculations on encrypted data. One well-known data science algorithm is K-Means, which clusters data points into a previously fixed number of clusters. We provided a homomorphic implementation by demonstrating how comparisons and assignments of clusters can be calculated. Furthermore, the algorithm is evaluated in an offline approach with bootstrapping and an online approach with client re-encryption. Both achieve an accuracy of 100{\%}, but take significantly longer, ranging from 50,000 to 16 million times compared to the non-encrypted case.

@article{Sardine_k-Means_1, abstract = {Modern data science requires large amounts of data and computational power to perform effectively. However, there is a lot of sensitive data that should not be shared with others. To still do data science, methods like Homomorphic Encryption exist that enable calculations on encrypted data. One well-known data science algorithm is K-Means, which clusters data points into a previously fixed number of clusters. We provided a homomorphic implementation by demonstrating how comparisons and assignments of clusters can be calculated. Furthermore, the algorithm is evaluated in an offline approach with bootstrapping and an online approach with client re-encryption. Both achieve an accuracy of 100{\%}, but take significantly longer, ranging from 50,000 to 16 million times compared to the non-encrypted case.}, author = {Prantl, Thomas and Amann, Patrick and Horn, Lukas and Engel, Simon and Bauer, Andr{\'e} and Bonilla, Rafael and Benhnini, Anwar and Kounev, Samuel}, journal = {Discover Applied Sciences}, keywords = {t_journalmagazine}, month = {07}, note = {https://doi.org/10.1007/s42452-026-09088-w}, number = 7, pages = 744, title = {Performance analysis of the homomorphic implementation of K-Means using CKKS}, volume = 8, year = 2026 }

%0 Journal Article %1 Sardine_k-Means_1 %A Prantl, Thomas %A Amann, Patrick %A Horn, Lukas %A Engel, Simon %A Bauer, Andr{é} %A Bonilla, Rafael %A Benhnini, Anwar %A Kounev, Samuel %D 2026 %J Discover Applied Sciences %N 7 %P 744 %R 10.1007/s42452-026-09088-w %T Performance analysis of the homomorphic implementation of K-Means using CKKS %U https://doi.org/10.1007/s42452-026-09088-w %V 8 %X Modern data science requires large amounts of data and computational power to perform effectively. However, there is a lot of sensitive data that should not be shared with others. To still do data science, methods like Homomorphic Encryption exist that enable calculations on encrypted data. One well-known data science algorithm is K-Means, which clusters data points into a previously fixed number of clusters. We provided a homomorphic implementation by demonstrating how comparisons and assignments of clusters can be calculated. Furthermore, the algorithm is evaluated in an offline approach with bootstrapping and an online approach with client re-encryption. Both achieve an accuracy of 100{\%}, but take significantly longer, ranging from 50,000 to 16 million times compared to the non-encrypted case.
Towards Performance-Oriented Planning and Development of IoT Applications and Networks. Prantl, Thomas; Horn, Lukas; Engel, Simon; Meissner, Maximilian; Bonilla, Rafael; Kounev, Samuel; in Companion of the 17th ACM/SPEC International Conference on Performance Engineering (2026). 92–93.
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The planning of IoT applications requires consideration of the performance, energy consumption, and security of resource-constrained devices. In particular, n-to-n communication patterns and security mechanisms significantly affect the runtime, energy consumption, and reliability of IoT systems. In this article, we summarize our previous work on the performance and security analysis of secure group communication and attribute-based encryption methods, as well as on the evaluation of publish/subscribe brokers. Based on measurements on real-world IoT hardware, we outline an approach for modeling and combining individual IoT operations to estimate time and energy consumption in advance. The goal is to support developers in performance-oriented planning and development of energy-efficient, secure IoT applications.

@inproceedings{10.1145/3777911.3799728, abstract = {The planning of IoT applications requires consideration of the performance, energy consumption, and security of resource-constrained devices. In particular, n-to-n communication patterns and security mechanisms significantly affect the runtime, energy consumption, and reliability of IoT systems. In this article, we summarize our previous work on the performance and security analysis of secure group communication and attribute-based encryption methods, as well as on the evaluation of publish/subscribe brokers. Based on measurements on real-world IoT hardware, we outline an approach for modeling and combining individual IoT operations to estimate time and energy consumption in advance. The goal is to support developers in performance-oriented planning and development of energy-efficient, secure IoT applications.}, address = {New York, NY, USA}, author = {Prantl, Thomas and Horn, Lukas and Engel, Simon and Meissner, Maximilian and Bonilla, Rafael and Kounev, Samuel}, booktitle = {Companion of the 17th ACM/SPEC International Conference on Performance Engineering}, keywords = {t_poster}, pages = {92–93}, publisher = {Association for Computing Machinery}, series = {ICPE Companion '26}, title = {Towards Performance-Oriented Planning and Development of IoT Applications and Networks}, year = 2026 }

%0 Conference Paper %1 10.1145/3777911.3799728 %A Prantl, Thomas %A Horn, Lukas %A Engel, Simon %A Meissner, Maximilian %A Bonilla, Rafael %A Kounev, Samuel %B Companion of the 17th ACM/SPEC International Conference on Performance Engineering %C New York, NY, USA %D 2026 %I Association for Computing Machinery %P 92–93 %R 10.1145/3777911.3799728 %T Towards Performance-Oriented Planning and Development of IoT Applications and Networks %U https://doi.org/10.1145/3777911.3799728 %X The planning of IoT applications requires consideration of the performance, energy consumption, and security of resource-constrained devices. In particular, n-to-n communication patterns and security mechanisms significantly affect the runtime, energy consumption, and reliability of IoT systems. In this article, we summarize our previous work on the performance and security analysis of secure group communication and attribute-based encryption methods, as well as on the evaluation of publish/subscribe brokers. Based on measurements on real-world IoT hardware, we outline an approach for modeling and combining individual IoT operations to estimate time and energy consumption in advance. The goal is to support developers in performance-oriented planning and development of energy-efficient, secure IoT applications. %@ 9798400723261
Quo Vadis CKKS: Comparison of the Realization of Basic Mathematical Functions for the Homomorphic Cryptosystem CKKS using De Bello and Polynomial Approximations. Prantl, Thomas; Horn, Lukas; Engel, Simon; Bauer, André; Kounev, Samuel; in Journal of Information Security and Applications (2025). 93
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@article{HE_Sardinen_2025, author = {Prantl, Thomas and Horn, Lukas and Engel, Simon and Bauer, André and Kounev, Samuel}, journal = {Journal of Information Security and Applications}, keywords = {t_journalmagazine}, month = {09}, note = {Published online June 2025}, publisher = {Elsevier}, title = {Quo Vadis CKKS: Comparison of the Realization of Basic Mathematical Functions for the Homomorphic Cryptosystem CKKS using De Bello and Polynomial Approximations}, volume = 93, year = 2025 }

%0 Journal Article %1 HE_Sardinen_2025 %A Prantl, Thomas %A Horn, Lukas %A Engel, Simon %A Bauer, André %A Kounev, Samuel %D 2025 %I Elsevier %J Journal of Information Security and Applications %R 10.1016/j.jisa.2025.104110 %T Quo Vadis CKKS: Comparison of the Realization of Basic Mathematical Functions for the Homomorphic Cryptosystem CKKS using De Bello and Polynomial Approximations %U https://www.sciencedirect.com/science/article/pii/S2214212625001474 %V 93

List of all publications: Thomas Prantl

Teaching

Provisioning of topics for "Seminar Software Engineering" and supervision of participating students
Supervisions of software project in the "Softwarepraktikum" (practical course teaching students to complete software projects in a team)
Coordination of the exercises on the bachelor's lecture "Softwaretechnik" by Prof. Samuel Kounev, University of Würzburg

Conference and Workshop Organisation

ACM/SPEC International Conference on Performance Evaluation (ICPE) 2022 as Web Chair
SPS Special Session on Cyber Resilience and Antifragility in Complex Distributed Systems (CyRA) 2021 as PC member
Workshop on Self-Aware Computing (SEAC) 2020 as Publicity Chair

Selected Reviewer Activities

Mascots 2020
Mascots 2019
Subreviewer ICPE 2019

Degrees

Master Informatik (Master of Computer Science)
1. Staatsexamen für das Lehramt am Gymnasium (Physik/Informatik)
Bachelor Informatik (Bachelor of Computer Science)
Bachelor Naturwissenschaftliche Grundlagen (Bachelor of Natural Science Foundations)

List of all publications: Thomas Prantl

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