Thomas Yurek (University of Illinois at Urbana-Champaign), Licheng Luo (University of Illinois at Urbana-Champaign), Jaiden Fairoze (University of California, Berkeley), Aniket Kate (Purdue University), Andrew Miller (University of Illinois at Urbana-Champaign)

Despite significant recent progress toward making multi-party computation (MPC) practical, no existing MPC library offers complete robustness---meaning guaranteed output delivery, including in the offline phase---in a network that even has intermittent delays. Importantly, several theoretical MPC constructions already ensure robustness in this setting. We observe that the key reason for this gap between theory and practice is the absence of efficient verifiable/complete secret sharing (VSS/CSS) constructions; existing CSS protocols either require a) challenging broadcast channels in practice or b) introducing computation and communication overhead that is at least quadratic in the number of players.

This work presents hbACSS, a suite of optimal-resilience asynchronous complete secret sharing protocols that are (quasi)linear in both computation and communication overhead. Towards developing hbACSS, we develop hbPolyCommit, an efficient polynomial commitment scheme that is (quasi)linear (in the polynomial degree) in terms of computation and communication overhead without requiring a trusted setup. We implement our hbACSS protocols, extensively analyze their practicality, and observe that our protocols scale well with an increasing number of parties. In particular, we use hbACSS to generate MPC input masks: a useful primitive which had previously only been calculated nonrobustly in practice.

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COOPER: Testing the Binding Code of Scripting Languages with...

Peng Xu (TCA/SKLCS, Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences), Yanhao Wang (QI-ANXIN Technology Research Institute), Hong Hu (Pennsylvania State University), Purui Su (TCA/SKLCS, Institute of Software, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences)

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Megan Nyre-Yu (Sandia National Laboratories), Elizabeth S. Morris (Sandia National Laboratories), Blake Moss (Sandia National Laboratories), Charles Smutz (Sandia National Laboratories), Michael R. Smith (Sandia National Laboratories)

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The Taming of the Stack: Isolating Stack Data from...

Kaiming Huang (Penn State University), Yongzhe Huang (Penn State University), Mathias Payer (EPFL), Zhiyun Qian (UC Riverside), Jack Sampson (Penn State University), Gang Tan (Penn State University), Trent Jaeger (Penn State University)

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