EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation
Abstract Background Modern biomedical research is data-driven and relies heavily on the re-use and sharing of data. Biomedical data, however, is subject to strict data protection requirements. Due to the complexity of the data required and the scale of data use, obtaining informed consent is often i...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-12-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-022-05044-8 |
| _version_ | 1811177862225461248 |
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| author | Felix Nikolaus Wirth Tobias Kussel Armin Müller Kay Hamacher Fabian Prasser |
| author_facet | Felix Nikolaus Wirth Tobias Kussel Armin Müller Kay Hamacher Fabian Prasser |
| author_sort | Felix Nikolaus Wirth |
| collection | DOAJ |
| description | Abstract Background Modern biomedical research is data-driven and relies heavily on the re-use and sharing of data. Biomedical data, however, is subject to strict data protection requirements. Due to the complexity of the data required and the scale of data use, obtaining informed consent is often infeasible. Other methods, such as anonymization or federation, in turn have their own limitations. Secure multi-party computation (SMPC) is a cryptographic technology for distributed calculations, which brings formally provable security and privacy guarantees and can be used to implement a wide-range of analytical approaches. As a relatively new technology, SMPC is still rarely used in real-world biomedical data sharing activities due to several barriers, including its technical complexity and lack of usability. Results To overcome these barriers, we have developed the tool EasySMPC, which is implemented in Java as a cross-platform, stand-alone desktop application provided as open-source software. The tool makes use of the SMPC method Arithmetic Secret Sharing, which allows to securely sum up pre-defined sets of variables among different parties in two rounds of communication (input sharing and output reconstruction) and integrates this method into a graphical user interface. No additional software services need to be set up or configured, as EasySMPC uses the most widespread digital communication channel available: e-mails. No cryptographic keys need to be exchanged between the parties and e-mails are exchanged automatically by the software. To demonstrate the practicability of our solution, we evaluated its performance in a wide range of data sharing scenarios. The results of our evaluation show that our approach is scalable (summing up 10,000 variables between 20 parties takes less than 300 s) and that the number of participants is the essential factor. Conclusions We have developed an easy-to-use “no-code solution” for performing secure joint calculations on biomedical data using SMPC protocols, which is suitable for use by scientists without IT expertise and which has no special infrastructure requirements. We believe that innovative approaches to data sharing with SMPC are needed to foster the translation of complex protocols into practice. |
| first_indexed | 2024-04-11T06:09:30Z |
| format | Article |
| id | doaj.art-40a1ef0210bf4e54803eecf5b645c1e2 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-04-11T06:09:30Z |
| publishDate | 2022-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-40a1ef0210bf4e54803eecf5b645c1e22022-12-22T04:41:20ZengBMCBMC Bioinformatics1471-21052022-12-0123111710.1186/s12859-022-05044-8EasySMPC: a simple but powerful no-code tool for practical secure multiparty computationFelix Nikolaus Wirth0Tobias Kussel1Armin Müller2Kay Hamacher3Fabian Prasser4Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Medical Informatics GroupComputational Biology and Simulation, TU DarmstadtBerlin Institute of Health at Charité – Universitätsmedizin Berlin, Medical Informatics GroupComputational Biology and Simulation, TU DarmstadtBerlin Institute of Health at Charité – Universitätsmedizin Berlin, Medical Informatics GroupAbstract Background Modern biomedical research is data-driven and relies heavily on the re-use and sharing of data. Biomedical data, however, is subject to strict data protection requirements. Due to the complexity of the data required and the scale of data use, obtaining informed consent is often infeasible. Other methods, such as anonymization or federation, in turn have their own limitations. Secure multi-party computation (SMPC) is a cryptographic technology for distributed calculations, which brings formally provable security and privacy guarantees and can be used to implement a wide-range of analytical approaches. As a relatively new technology, SMPC is still rarely used in real-world biomedical data sharing activities due to several barriers, including its technical complexity and lack of usability. Results To overcome these barriers, we have developed the tool EasySMPC, which is implemented in Java as a cross-platform, stand-alone desktop application provided as open-source software. The tool makes use of the SMPC method Arithmetic Secret Sharing, which allows to securely sum up pre-defined sets of variables among different parties in two rounds of communication (input sharing and output reconstruction) and integrates this method into a graphical user interface. No additional software services need to be set up or configured, as EasySMPC uses the most widespread digital communication channel available: e-mails. No cryptographic keys need to be exchanged between the parties and e-mails are exchanged automatically by the software. To demonstrate the practicability of our solution, we evaluated its performance in a wide range of data sharing scenarios. The results of our evaluation show that our approach is scalable (summing up 10,000 variables between 20 parties takes less than 300 s) and that the number of participants is the essential factor. Conclusions We have developed an easy-to-use “no-code solution” for performing secure joint calculations on biomedical data using SMPC protocols, which is suitable for use by scientists without IT expertise and which has no special infrastructure requirements. We believe that innovative approaches to data sharing with SMPC are needed to foster the translation of complex protocols into practice.https://doi.org/10.1186/s12859-022-05044-8Secure multi-party computationSMPCSecret sharingGMW protocolUser experienceNo-code |
| spellingShingle | Felix Nikolaus Wirth Tobias Kussel Armin Müller Kay Hamacher Fabian Prasser EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation BMC Bioinformatics Secure multi-party computation SMPC Secret sharing GMW protocol User experience No-code |
| title | EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation |
| title_full | EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation |
| title_fullStr | EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation |
| title_full_unstemmed | EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation |
| title_short | EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation |
| title_sort | easysmpc a simple but powerful no code tool for practical secure multiparty computation |
| topic | Secure multi-party computation SMPC Secret sharing GMW protocol User experience No-code |
| url | https://doi.org/10.1186/s12859-022-05044-8 |
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