Standard
Distributed and Adversarial Resistant Workflow Execution on the Algorand Blockchain. / Xu, Yibin; Slaats, Tijs; Düdder, Boris; Debois, Søren; Wu, Haiqin.
Financial Cryptography and Data Security. FC 2022 International Workshops - CoDecFin, DeFi, Voting, WTSC, Revised Selected Papers. ed. / Shin’ichiro Matsuo; Lewis Gudgeon; Daniel Perez Hernandez; Sam Werner; Ariah Klages-Mundt; Thomas Haines; Aleksander Essex; Andrea Bracciali; Massimiliano Sala. Springer, 2023. p. 583-597 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13412 LNCS).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Xu, Y, Slaats, T, Düdder, B, Debois, S
& Wu, H 2023,
Distributed and Adversarial Resistant Workflow Execution on the Algorand Blockchain. in S Matsuo, L Gudgeon, D Perez Hernandez, S Werner, A Klages-Mundt, T Haines, A Essex, A Bracciali & M Sala (eds),
Financial Cryptography and Data Security. FC 2022 International Workshops - CoDecFin, DeFi, Voting, WTSC, Revised Selected Papers. Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13412 LNCS, pp. 583-597, 26th International Conference on Financial Cryptography and Data Security, FC 2022, Saint George, Grenada,
02/05/2022.
https://doi.org/10.1007/978-3-031-32415-4_35
APA
Xu, Y., Slaats, T., Düdder, B., Debois, S.
, & Wu, H. (2023).
Distributed and Adversarial Resistant Workflow Execution on the Algorand Blockchain. In S. Matsuo, L. Gudgeon, D. Perez Hernandez, S. Werner, A. Klages-Mundt, T. Haines, A. Essex, A. Bracciali, & M. Sala (Eds.),
Financial Cryptography and Data Security. FC 2022 International Workshops - CoDecFin, DeFi, Voting, WTSC, Revised Selected Papers (pp. 583-597). Springer. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13412 LNCS
https://doi.org/10.1007/978-3-031-32415-4_35
Vancouver
Xu Y, Slaats T, Düdder B, Debois S
, Wu H.
Distributed and Adversarial Resistant Workflow Execution on the Algorand Blockchain. In Matsuo S, Gudgeon L, Perez Hernandez D, Werner S, Klages-Mundt A, Haines T, Essex A, Bracciali A, Sala M, editors, Financial Cryptography and Data Security. FC 2022 International Workshops - CoDecFin, DeFi, Voting, WTSC, Revised Selected Papers. Springer. 2023. p. 583-597. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13412 LNCS).
https://doi.org/10.1007/978-3-031-32415-4_35
Author
Xu, Yibin ; Slaats, Tijs ; Düdder, Boris ; Debois, Søren ; Wu, Haiqin. / Distributed and Adversarial Resistant Workflow Execution on the Algorand Blockchain. Financial Cryptography and Data Security. FC 2022 International Workshops - CoDecFin, DeFi, Voting, WTSC, Revised Selected Papers. editor / Shin’ichiro Matsuo ; Lewis Gudgeon ; Daniel Perez Hernandez ; Sam Werner ; Ariah Klages-Mundt ; Thomas Haines ; Aleksander Essex ; Andrea Bracciali ; Massimiliano Sala. Springer, 2023. pp. 583-597 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13412 LNCS).
Bibtex
@inproceedings{19e78cfa5a4f44279694e5c8e0fd4f20,
title = "Distributed and Adversarial Resistant Workflow Execution on the Algorand Blockchain",
abstract = "We provide a practical translation from the Dynamic Condition Response (DCR) process modelling language to the Transaction Execution Approval Language (TEAL) used by the Algorand blockchain. Compared to earlier implementations of business process notations on blockchains, particularly Ethereum, the present implementation is four orders of magnitude cheaper. This translation has the following immediate ramifications: (1) It allows decentralised execution of DCR-specified business processes in the absence of expensive intermediaries (lawyers, brokers) or counterparty risk. (2) It provides a possibly helpful high-level language for implementing business processes on Algorand. (3) It demonstrates that despite the strict limitations on Algorand smart contracts, they are powerful enough to encode models of a modern process notation.",
keywords = "Algorand, Applications of blockchain, Inter-institutional collaboration, Smart contracts",
author = "Yibin Xu and Tijs Slaats and Boris D{\"u}dder and S{\o}ren Debois and Haiqin Wu",
note = "Funding Information: Acknowledgements. This material is based upon work partially supported by (1) the Christian-Doppler-Laboratory for Security and Quality Improvement in the Production System Lifecycle; The financial support by the Austrian Federal Ministry for Digital and Economic Affairs, the Nation Foundation for Research, Technology and Development and University of Vienna, Faculty of Computer Science, Security & Privacy Group is gratefully acknowledged; (2) SBA Research; the competence center SBA Research (SBA-K1) funded within the framework of COMET Competence Centers for Funding Information: Excellent Technologies by BMVIT, BMDW, and the federal state of Vienna, managed by the FFG; (3) the FFG Industrial PhD projects 878835 and 878736. (4) the FFG ICT of the Future project 874019 dIdentity & dApps. (5) the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No 826078 (FeatureCloud). We would also like to thank our anonymous reviewers for their valuable feedback and suggestions. Funding Information: Acknowledgments. This research is based upon work partially supported by (1) SBA Research (SBA-K1); SBA Research is a COMET Center within the COMET – Competence Centers for Excellent Technologies Programme and funded by BMK, BMDW, and the federal state of Vienna. The COMET Programme is managed by FFG. (2) the FFG ICT of the Future project 874019 dIdentity & dApps. (3) the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No 826078 (FeatureCloud) (4) OEAD (Austria{\textquoteright}s agency for education and internationalization) Special Grant. Funding Information: J. Hsin-yu Chiang—This work was supported by the PhD School of DTU Compute. B. David—This work was supported by the Concordium Foundation and by the Independent Research Fund Denmark (IRFD) grants number 9040-00399B (TrA2C), 9131-00075B (PUMA) and 0165-00079B. T. K. Frederiksen—This work was supported by “Sikker brug af f{\o}lsomme data”, Performance Contract 2020 and “Digital sikkerhed, tillid og dataetik”, Performance Contract 2021–2024, Ministry of Higher Education and Science, Denmark”. L. Gentile—This work was supported by the Concordium Foundation. Funding Information: Acknowledgement. We would like to thank Sven Heiberg for confirming that the attack scenario described in this paper would succeed on the current implementation of the IVXV protocol and for his helpful and constructive comments. We also would like to thank Vanessa Teague for so many interesting discussions on the security of voting systems and for her review of a previous version of this document. Eventually, we would like to thank the Voting{\textquoteright}22 reviewers for their interesting and helpful suggestions. The author was supported by the F.R.S.-FNRS project SeVoTe and by the FEDER-Cryptomedia Project. Funding Information: Johannes M{\"u}ller was supported by the Luxembourg National Research Fund (FNR), under the CORE Junior project FP2 (C20/IS/14698166/FP2/Mueller). Funding Information: This work was partially supported by the Australian Research Council: Discovery Project DP220101012, OPTIMA ITTC IC200100009. Funding Information: Acknowledgements. We thank Josh Benaloh and Olivier Pereira for insightful discussions and feedback. This work was supported by the Andrew Carnegie Fellowship, the U.S. National Science Foundation under grant no. CNS-1518888, and a gift from Microsoft. Funding Information: Acknowledgments. We would like to thank Patrik Keller and Bernhard Haslhofer for their valuable feedback. This work has received funding from the Austrian Research Promotion Agency (FFG) and the Austrian Security Research Programme (KIRAS). Funding Information: Acknowledgements. Support for this research was provided by the FCT through project SafeSessions, ref. PTDC/CCI-COM/6453/2020, by the LASIGE Research Unit, ref. UIDB/00408/2020 and ref. UIDP/00408/2020. Funding Information: Acknowledgements. The authors thank the AMF (Autorit{\'e} des March{\'e}s Financiers) for supporting this research project. J. Clark also acknowledges partial funding from the National Sciences and Engineering Research Council (NSERC)/Raymond Chabot Grant Thornton/Catallaxy Industrial Research Chair in Blockchain Technologies, as well as NSERC through a Discovery Grant. M. Moosavi acknowledges support from Fonds de Recherche du Qu{\'e}bec - Nature et Technologies (FRQNT). Funding Information: and we acknowledge EPSRC and the PETRAS Research Centre EP/S035362/1 for the FIRE Project. Publisher Copyright: {\textcopyright} 2023, International Financial Cryptography Association.; 26th International Conference on Financial Cryptography and Data Security, FC 2022 ; Conference date: 02-05-2022 Through 06-05-2022",
year = "2023",
doi = "10.1007/978-3-031-32415-4_35",
language = "English",
isbn = "9783031324147",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "583--597",
editor = "Shin{\textquoteright}ichiro Matsuo and Lewis Gudgeon and {Perez Hernandez}, Daniel and Sam Werner and Ariah Klages-Mundt and Thomas Haines and Aleksander Essex and Andrea Bracciali and Massimiliano Sala",
booktitle = "Financial Cryptography and Data Security. FC 2022 International Workshops - CoDecFin, DeFi, Voting, WTSC, Revised Selected Papers",
address = "Switzerland",
}
RIS
TY - GEN
T1 - Distributed and Adversarial Resistant Workflow Execution on the Algorand Blockchain
AU - Xu, Yibin
AU - Slaats, Tijs
AU - Düdder, Boris
AU - Debois, Søren
AU - Wu, Haiqin
N1 - Funding Information:
Acknowledgements. This material is based upon work partially supported by (1) the Christian-Doppler-Laboratory for Security and Quality Improvement in the Production System Lifecycle; The financial support by the Austrian Federal Ministry for Digital and Economic Affairs, the Nation Foundation for Research, Technology and Development and University of Vienna, Faculty of Computer Science, Security & Privacy Group is gratefully acknowledged; (2) SBA Research; the competence center SBA Research (SBA-K1) funded within the framework of COMET Competence Centers for
Funding Information:
Excellent Technologies by BMVIT, BMDW, and the federal state of Vienna, managed by the FFG; (3) the FFG Industrial PhD projects 878835 and 878736. (4) the FFG ICT of the Future project 874019 dIdentity & dApps. (5) the European Union’s Horizon 2020 research and innovation programme under grant agreement No 826078 (FeatureCloud). We would also like to thank our anonymous reviewers for their valuable feedback and suggestions.
Funding Information:
Acknowledgments. This research is based upon work partially supported by (1) SBA Research (SBA-K1); SBA Research is a COMET Center within the COMET – Competence Centers for Excellent Technologies Programme and funded by BMK, BMDW, and the federal state of Vienna. The COMET Programme is managed by FFG. (2) the FFG ICT of the Future project 874019 dIdentity & dApps. (3) the European Union’s Horizon 2020 research and innovation programme under grant agreement No 826078 (FeatureCloud) (4) OEAD (Austria’s agency for education and internationalization) Special Grant.
Funding Information:
J. Hsin-yu Chiang—This work was supported by the PhD School of DTU Compute. B. David—This work was supported by the Concordium Foundation and by the Independent Research Fund Denmark (IRFD) grants number 9040-00399B (TrA2C), 9131-00075B (PUMA) and 0165-00079B. T. K. Frederiksen—This work was supported by “Sikker brug af følsomme data”, Performance Contract 2020 and “Digital sikkerhed, tillid og dataetik”, Performance Contract 2021–2024, Ministry of Higher Education and Science, Denmark”. L. Gentile—This work was supported by the Concordium Foundation.
Funding Information:
Acknowledgement. We would like to thank Sven Heiberg for confirming that the attack scenario described in this paper would succeed on the current implementation of the IVXV protocol and for his helpful and constructive comments. We also would like to thank Vanessa Teague for so many interesting discussions on the security of voting systems and for her review of a previous version of this document. Eventually, we would like to thank the Voting’22 reviewers for their interesting and helpful suggestions. The author was supported by the F.R.S.-FNRS project SeVoTe and by the FEDER-Cryptomedia Project.
Funding Information:
Johannes Müller was supported by the Luxembourg National Research Fund (FNR), under the CORE Junior project FP2 (C20/IS/14698166/FP2/Mueller).
Funding Information:
This work was partially supported by the Australian Research Council: Discovery Project DP220101012, OPTIMA ITTC IC200100009.
Funding Information:
Acknowledgements. We thank Josh Benaloh and Olivier Pereira for insightful discussions and feedback. This work was supported by the Andrew Carnegie Fellowship, the U.S. National Science Foundation under grant no. CNS-1518888, and a gift from Microsoft.
Funding Information:
Acknowledgments. We would like to thank Patrik Keller and Bernhard Haslhofer for their valuable feedback. This work has received funding from the Austrian Research Promotion Agency (FFG) and the Austrian Security Research Programme (KIRAS).
Funding Information:
Acknowledgements. Support for this research was provided by the FCT through project SafeSessions, ref. PTDC/CCI-COM/6453/2020, by the LASIGE Research Unit, ref. UIDB/00408/2020 and ref. UIDP/00408/2020.
Funding Information:
Acknowledgements. The authors thank the AMF (Autorité des Marchés Financiers) for supporting this research project. J. Clark also acknowledges partial funding from the National Sciences and Engineering Research Council (NSERC)/Raymond Chabot Grant Thornton/Catallaxy Industrial Research Chair in Blockchain Technologies, as well as NSERC through a Discovery Grant. M. Moosavi acknowledges support from Fonds de Recherche du Québec - Nature et Technologies (FRQNT).
Funding Information:
and we acknowledge EPSRC and the PETRAS Research Centre EP/S035362/1 for the FIRE Project.
Publisher Copyright:
© 2023, International Financial Cryptography Association.
PY - 2023
Y1 - 2023
N2 - We provide a practical translation from the Dynamic Condition Response (DCR) process modelling language to the Transaction Execution Approval Language (TEAL) used by the Algorand blockchain. Compared to earlier implementations of business process notations on blockchains, particularly Ethereum, the present implementation is four orders of magnitude cheaper. This translation has the following immediate ramifications: (1) It allows decentralised execution of DCR-specified business processes in the absence of expensive intermediaries (lawyers, brokers) or counterparty risk. (2) It provides a possibly helpful high-level language for implementing business processes on Algorand. (3) It demonstrates that despite the strict limitations on Algorand smart contracts, they are powerful enough to encode models of a modern process notation.
AB - We provide a practical translation from the Dynamic Condition Response (DCR) process modelling language to the Transaction Execution Approval Language (TEAL) used by the Algorand blockchain. Compared to earlier implementations of business process notations on blockchains, particularly Ethereum, the present implementation is four orders of magnitude cheaper. This translation has the following immediate ramifications: (1) It allows decentralised execution of DCR-specified business processes in the absence of expensive intermediaries (lawyers, brokers) or counterparty risk. (2) It provides a possibly helpful high-level language for implementing business processes on Algorand. (3) It demonstrates that despite the strict limitations on Algorand smart contracts, they are powerful enough to encode models of a modern process notation.
KW - Algorand
KW - Applications of blockchain
KW - Inter-institutional collaboration
KW - Smart contracts
U2 - 10.1007/978-3-031-32415-4_35
DO - 10.1007/978-3-031-32415-4_35
M3 - Article in proceedings
AN - SCOPUS:85172673938
SN - 9783031324147
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 583
EP - 597
BT - Financial Cryptography and Data Security. FC 2022 International Workshops - CoDecFin, DeFi, Voting, WTSC, Revised Selected Papers
A2 - Matsuo, Shin’ichiro
A2 - Gudgeon, Lewis
A2 - Perez Hernandez, Daniel
A2 - Werner, Sam
A2 - Klages-Mundt, Ariah
A2 - Haines, Thomas
A2 - Essex, Aleksander
A2 - Bracciali, Andrea
A2 - Sala, Massimiliano
PB - Springer
T2 - 26th International Conference on Financial Cryptography and Data Security, FC 2022
Y2 - 2 May 2022 through 6 May 2022
ER -
