Efficient and Practical Secure Multiparty Computation in Zero-Trusted Environments

Authors

Oscar G. Bautista Chia, Florida International UniversityFollow

Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Electrical and Computer Engineering

First Advisor's Name

Kemal Akkaya

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Selcuk Uluagac

Second Advisor's Committee Title

Committee member

Third Advisor's Name

Mohammad Ashiqur Rahman

Third Advisor's Committee Title

Committee member

Fourth Advisor's Name

Jason Liu

Fourth Advisor's Committee Title

Committee member

Keywords

secure multiparty computation, privacy-preserving computation, confidentiality, practical MPC, failure recovery, blockchain, pipelining, management protocol

Date of Defense

6-22-2023

Abstract

With the increased awareness of data protection and privacy, there is an urgent need for technologies that enable organizations to compute with private data. One such technology is Secure Multiparty Computation (SMPC), where two or more parties jointly evaluate a function without disclosing their inputs. The parties execute an SMPC protocol in rounds, consisting of a local computation followed by a network exchange. In the last decade, SMPC has progressed from a theoretical-only approach to a promising solution for many real-world applications. Even so, existing challenges related to further efficiency improvements and aspects such as robustness and management prevent the broad adoption of this technology. For instance, since many privacy-preserving applications use large amounts of data, SMPC may take a long time, and any interruption to the computation may lead to a restart of the process, wasting time and computation resources. Additionally, many SMPC approaches focus on the protocol, assuming the parties are already connected and have the input data. However, this is not the case in many applications where the data sources and the computation parties are different. This dissertation aims to fill this gap by proposing a suite of approaches that address these challenges and make SMPC more practical and efficient. First, we propose two approaches that improve performance by (i) using a blockchain-based fast broadcast channel as the SMPC network, reducing communication complexity and execution delay, and (ii) utilizing pipelining on SMPC for the first time, improving resources utilization and, therefore, reducing the execution time. Second, we proposed approaches on robustness and management. On the robustness side, we leveraged the blockchain-based approach as the basis for a failure-recovery protocol that parties can follow in the face of network errors and node failures, thus increasing resilience. On the management side, we propose an SMPC framework that automatizes the secure connection setup between data source clients and, initially unknown, SMPC servers and delivers verified results without leaking any input or output. The evaluation results on cloud deployments show that the proposed approaches significantly improve efficiency, robustness, and management over existing approaches.

Identifier

FIDC011104

ORCID

0000-0002-5000-1912

Comments

This manuscript contains information that has been reviewed and approved for public release through the Public Affairs (PA) release process. The approved PA release numbers for chapters 4, 6, and 7 are AFRL-2023-2164, AFRL-2022-5506, and AFRL-2024-0647, respectively.

Previously Published In

Bautista, O., Akkaya, K., and Homsi, S., (2023). ReplayMPC: A Fast Failure Recovery Protocol for Secure Multiparty Computation Applications using Blockchain. Proceedings of the IEEE International Conference on Smart Computing (SMARTCOMP), 124-132.

Bautista, O., Manshaei, M., Hernandez, R., Akkaya, K., Homsi, S. and Uluagac, S., (2023). MPC-ABC: Blockchain-based Network Communication for Efficiently Secure Multiparty Computation. Journal of Network and Systems Management, Vol. 31.

Bautista, O. and Akkaya, K., (2023). MPC-as-a-Service: A Customizable Management Protocol for Running Multi-party Computation on IoT Devices. Proceedings of the 3rd IEEE/IFIP International Workshop and Internet of Things Management, 1-6.

Bautista, O. and Akkaya, K., (2022). Network-Efficient Pipelining-Based Secure Multiparty Computation for Machine Learning Applications. Proceedings of the IEEE 47th Conference on Local Computer Networks, 205-213.

Bautista, O., Akkaya, K., and Homsi, S., (2021). Outsourcing Secure MPC to Untrusted Cloud Environments with Correctness Verification. Proceedings of the IEEE 46th Conference on Local Computer Networks, 178-184.

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

Recommended Citation

Bautista Chia, Oscar G., "Efficient and Practical Secure Multiparty Computation in Zero-Trusted Environments" (2023). FIU Electronic Theses and Dissertations. 5339.
https://digitalcommons.fiu.edu/etd/5339