Concretely Efficient MPC Protocols for Real-world Applications

Yubo Zeng, Kang Yang, Dengguo Feng +1 more

Nariyasu Heseri, Koji Nuida

Carmit Hazay, Emmanuela Orsini, Peter Schöll +1 more

Ashish Choudhury, Arpita Patra

Nishat Koti, Varsha Bhat Kukkala, Arpita Patra +1 more

Secure multiparty computation (MPC) is increasingly being used to address privacy issues in various applications. The recent work of Alon et al. (CRYPTO'20) identified the shortcomings of traditional MPC and defined a Friends-and-Foes (FaF) security notion to address the same. We showcase the need for FaF security in real-world applications such as dark pools. This subsequently necessitates designing concretely efficient FaF-secure protocols. Towards this, keeping efficiency at the center stage, we design ring-based FaF-secure MPC protocols in the small-party honest-majority setting. Specifically, we provide (1,1)-FaF secure 5 party computation protocols (5PC) that consider one malicious and one semi-honest corruption and constitutes the optimal setting for attaining honest-majority. At the heart of it lies the multiplication protocol that requires a single round of communication with 8 ring elements (amortized). To facilitate having FaF-secure variants for several applications, we design a variety of building blocks optimized for our FaF setting. The practicality of the designed (1,1)-FaF secure 5PC framework is showcased by benchmarking dark pools. In the process, we also improve the efficiency and security of the dark pool protocols over the existing traditionally secure ones. This improvement is witnessed as a gain of up to 62x in throughput compared to the existing ones. Finally, to demonstrate the versatility of our framework, we also benchmark popular deep neural networks.

Alessandra Scafuro, Tanner Verber

The server-aided model for multiparty computation (MPC) was introduced to capture a real-world scenario where clients wish to off-load the heavy computation of MPC protocols to dedicated servers. A rich body of work has studied various trade-offs between security guarantees (e.g., semi-honest vs malicious), trust assumptions (e.g., the threshold on corrupted servers), and efficiency. However, all existing works make the assumption that all clients must agree on employing the same servers, and accept the same corruption threshold. In this paper, we challenge this assumption and introduce a new paradigm for server-aided MPC, where each client can choose their own set of servers and their own threshold of corrupted servers. In this new model, the privacy of each client is guaranteed as long as their own threshold is satisfied, regardless of the other servers/clients. We call this paradigm per-party private server-aided MPC to highlight both a security and efficiency guarantee: (1) per-party privacy, which means that each party gets their own privacy guarantees that depend on their own choice of the servers; (2) per-party complexity, which means that each party only needs to communicate with their chosen servers. Our primary contribution is a new theoretical framework for server-aided MPC. We provide two protocols to show feasibility, but leave it as a future work to investigate protocols that focus on concrete efficiency.