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MARTSIA: Enabling Data Confidentiality for Blockchain-Based Process Execution

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Enterprise Design, Operations, and Computing (EDOC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14367))

Abstract

Multi-party business processes rely on the collaboration of various players in a decentralized setting. Blockchain technology can facilitate the automation of these processes, even in cases where trust among participants is limited. Transactions are stored in a ledger, a replica of which is retained by every node of the blockchain network. The operations saved thereby are thus publicly accessible. While this enhances transparency, reliability, and persistence, it hinders the utilization of public blockchains for process automation as it violates typical confidentiality requirements in corporate settings. In this paper, we propose MARTSIA: A Multi-Authority Approach to Transaction Systems for Interoperating Applications. MARTSIA enables precise control over process data at the level of message parts. Based on Multi-Authority Attribute-Based Encryption (MA-ABE), MARTSIA realizes a number of desirable properties, including confidentiality, transparency, and auditability. We implemented our approach in proof-of-concept prototypes, with which we conduct a case study in the area of supply chain management. Also, we show the integration of MARTSIA with a state-of-the-art blockchain-based process execution engine to secure the data flow.

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Notes

  1. 1.

    Cyber 4.0 project BRIE: https://brie.moveax.it/en. Accessed: 09 June 2023.

  2. 2.

    ipfs.tech. Accessed: 09 June 2023.

  3. 3.

    Notice that metadata are known to all the authorities and all the actors involved in the process. Therefore, non-malicious authorities are expected to create an identical file. The (same) hash is thus at the basis of the resource locator. As a consequence, anyone can verify whether the authorities behave properly in this step by checking that the resource locators are equal, with no need to load the file from the Data Store.

  4. 4.

    Goerli: sepolia.etherscan.io; Mumbai: mumbai.polygonscan.com; Avalanche: testnet.snowtrace.io. Accessed: 09 June 2023.

  5. 5.

    github.com/orlenyslp/Caterpillar. Accessed: 10 June 2023.

  6. 6.

    github.com/apwbs/MARTSIA-Ethereum/tree/main/caterpillar-interaction.

  7. 7.

    github.com/apwbs/MARTSIA-Ethereum/tree/main/tests. Accessed: 10 June 2023.

  8. 8.

    A preliminary version is available at github.com/apwbs/MARTSIA-Algorand.

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Acknowledgements

The work of E. Marangone and C. Di Ciccio was partially funded by the Cyber 4.0 project BRIE, the Sapienza project DRONES, by project SERICS (PE00000014) under the NRRP MUR program funded by the EU-NGEU, and by project PINPOINT (B87G22000450001) under the PRIN MUR program.

Author information

Authors and Affiliations

  1. Sapienza University of Rome, Rome, Italy

    Edoardo Marangone, Claudio Di Ciccio, Daniele Friolo, Eugenio Nerio Nemmi & Daniele Venturi

  2. Technical University of Munich, School of CIT, Munich, Germany

    Ingo Weber

  3. Fraunhofer Gesellschaft, Munich, Germany

    Ingo Weber

Authors
  1. Edoardo Marangone
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  2. Claudio Di Ciccio
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  3. Daniele Friolo
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  4. Eugenio Nerio Nemmi
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  5. Daniele Venturi
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  6. Ingo Weber
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Corresponding author

Correspondence to Edoardo Marangone .

Editor information

Editors and Affiliations

  1. Vienna University of Technology, Vienna, Austria

    Henderik A. Proper

  2. Technical University of Berlin, Berlin, Germany

    Luise Pufahl

  3. University of Groningen, Groningen, The Netherlands

    Dimka Karastoyanova

  4. University of Twente, Enschede, The Netherlands

    Marten van Sinderen

  5. University of Twente, Enschede, The Netherlands

    João Moreira

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Marangone, E., Di Ciccio, C., Friolo, D., Nemmi, E.N., Venturi, D., Weber, I. (2024). MARTSIA: Enabling Data Confidentiality for Blockchain-Based Process Execution. In: Proper, H.A., Pufahl, L., Karastoyanova, D., van Sinderen, M., Moreira, J. (eds) Enterprise Design, Operations, and Computing. EDOC 2023. Lecture Notes in Computer Science, vol 14367. Springer, Cham. https://doi.org/10.1007/978-3-031-46587-1_4

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  • DOI: https://doi.org/10.1007/978-3-031-46587-1_4

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