TY - GEN
T1 - Leviosa
T2 - 26th ACM SIGSAC Conference on Computer and Communications Security, CCS 2019
AU - Hazay, Carmit
AU - Marcedone, Antonio
AU - Ishai, Yuval
AU - Venkitasubramaniam, Muthuramakrishnan
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/11/6
Y1 - 2019/11/6
N2 - We study the problem of secure two-party computation of arithmetic circuits in the presence of active (“malicious”) parties. This problem is motivated by privacy-preserving numerical computations, such as ones arising in the context of machine learning training and classification, as well as in threshold cryptographic schemes. In this work, we design, optimize, and implement an actively secure protocol for secure two-party arithmetic computation. A distinctive feature of our protocol is that it can make a fully modular black-box use of any passively secure implementation of oblivious linear function evaluation (OLE). OLE is a commonly used primitive for secure arithmetic computation, analogously to the role of oblivious transfer in secure computation for Boolean circuits. For typical (large but not-too-narrow) circuits, our protocol requires roughly 4 invocations of passively secure OLE per multiplication gate. This significantly improves over the recent TinyOLE protocol (Döttling et al., ACM CCS 2017), which requires 22 invocations of actively secure OLE in general, or 44 invocations of a specific code-based passively secure OLE. Our protocol follows the high level approach of the IPS compiler (Ishai et al., CRYPTO 2008, TCC 2009), optimizing it in several ways. In particular, we adapt optimization ideas that were used in the context of the practical zero-knowledge argument system Ligero (Ames et al., ACM CCS 2017) to the more general setting of secure computation, and explore the possibility of boosting efficiency by employing a “leaky” passively secure OLE protocol. The latter is motivated by recent (passively secure) lattice-based OLE implementations in which allowing such leakage enables better efficiency. We showcase the performance of our protocol by applying its implementation to several useful instances of secure arithmetic computation. On “wide” circuits, such as ones computing a fixed function on many different inputs, our protocol is 5x faster and transmits 4x less data than the state-of-the-art Overdrive (Keller et al., Eurocrypt 2018). Our benchmarks include a general passive-to-active OLE compiler, authenticated generation of “Beaver triples”, and a system for securely outsourcing neural network classification. The latter is the first actively secure implementation of its kind, strengthening the passive security provided by recent related works (Mohassel and Zhang, IEEE S&P 2017; Juvekar et al., USENIX 2018).
AB - We study the problem of secure two-party computation of arithmetic circuits in the presence of active (“malicious”) parties. This problem is motivated by privacy-preserving numerical computations, such as ones arising in the context of machine learning training and classification, as well as in threshold cryptographic schemes. In this work, we design, optimize, and implement an actively secure protocol for secure two-party arithmetic computation. A distinctive feature of our protocol is that it can make a fully modular black-box use of any passively secure implementation of oblivious linear function evaluation (OLE). OLE is a commonly used primitive for secure arithmetic computation, analogously to the role of oblivious transfer in secure computation for Boolean circuits. For typical (large but not-too-narrow) circuits, our protocol requires roughly 4 invocations of passively secure OLE per multiplication gate. This significantly improves over the recent TinyOLE protocol (Döttling et al., ACM CCS 2017), which requires 22 invocations of actively secure OLE in general, or 44 invocations of a specific code-based passively secure OLE. Our protocol follows the high level approach of the IPS compiler (Ishai et al., CRYPTO 2008, TCC 2009), optimizing it in several ways. In particular, we adapt optimization ideas that were used in the context of the practical zero-knowledge argument system Ligero (Ames et al., ACM CCS 2017) to the more general setting of secure computation, and explore the possibility of boosting efficiency by employing a “leaky” passively secure OLE protocol. The latter is motivated by recent (passively secure) lattice-based OLE implementations in which allowing such leakage enables better efficiency. We showcase the performance of our protocol by applying its implementation to several useful instances of secure arithmetic computation. On “wide” circuits, such as ones computing a fixed function on many different inputs, our protocol is 5x faster and transmits 4x less data than the state-of-the-art Overdrive (Keller et al., Eurocrypt 2018). Our benchmarks include a general passive-to-active OLE compiler, authenticated generation of “Beaver triples”, and a system for securely outsourcing neural network classification. The latter is the first actively secure implementation of its kind, strengthening the passive security provided by recent related works (Mohassel and Zhang, IEEE S&P 2017; Juvekar et al., USENIX 2018).
KW - MPC-in-the-Head
KW - Oblivious Linear Evaluation (OLE)
KW - Secure Arithmetic Two-Party Computation
UR - http://www.scopus.com/inward/record.url?scp=85075950768&partnerID=8YFLogxK
U2 - 10.1145/3319535.3354258
DO - 10.1145/3319535.3354258
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AN - SCOPUS:85075950768
T3 - Proceedings of the ACM Conference on Computer and Communications Security
SP - 327
EP - 344
BT - CCS 2019 - Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security
Y2 - 11 November 2019 through 15 November 2019
ER -