Automatically optimizing secure computation
Proceedings of the 18th ACM conference on Computer and communications security
Demo: secure computation in JavaScript
Proceedings of the 18th ACM conference on Computer and communications security
Expression rewriting for optimizing secure computation
Proceedings of the third ACM conference on Data and application security and privacy
An information-flow type-system for mixed protocol secure computation
Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security
PICCO: a general-purpose compiler for private distributed computation
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Efficient secure computation optimization
Proceedings of the First ACM workshop on Language support for privacy-enhancing technologies
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Secure Computation (SC) enables secure distributed computation of arbitrary functions of private inputs. It has many useful applications, e.g. benchmarking or auctions. Several general protocols for SC have been proposed and recently been implemented in a number of compilers and frameworks. These compilers or frameworks implement one general SC protocol and then require the programmer to implement the function he wants the protocol to compute. Performance remains a challenge for this approach and it has been realized early on that special protocols for important problems can deliver superior performance. In this paper we propose a new intermediate language (L1) for optimizing SC compilers which enables efficient implementation of special protocols potentially mixing several general SC protocols. We show by three case studies--one for computation of the median, one for weighted average, one for division--that special protocols and mixed-protocol implementations in our language L1 can lead to superior performance. Moreover, we show that only a combined view on algorithm \emph{and} cryptographic protocol can discover SCs with best run-time performance.