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Lecture notes in computer science

Secure Two-Party Computation Is Practical

Benny Pinkas B, Thomas H. Schneider, Nigel Paul Smart, Stephen C. Williams

Published Jan 1, 2009• 720 citations
Publisher
DOI
10.1007/978-3-642-10366-7_15

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Introduced by Yao in early 1980s, secure computation is being one among the major area of research interest among cryptologists. In three decades of its growth, secure computation which can be called as two-party computation, or multiparty computation depending on the number of parties involved has experienced vast diversities. Research has been carried out by exploiting specific properties of functionalities and generic approach to achieve efficient practical secure computation protocols. This paper compares the above two approaches for secure two-party computation of AES-128.
Introduced by Yao in early 1980s, secure computation is being one among the major area of research interest among cryptologists. In three decades of its growth, secure computation which can be called as two-party computation, or multiparty computation depending on the number of parties involved has experienced vast diversities. Research has been carried out by exploiting specific properties of functionalities and generic approach to achieve efficient practical secure computation protocols. This paper considers the application secure two-party computation of AES-128 for comparison of the above two approaches.
Secure two-party computation enables two parties to evaluate a function cooperatively without revealing to either party anything beyond the function's output. The garbled-circuit technique, a generic approach to secure two-party computation for semi-honest participants, was developed by Yao in the 1980s, but has been viewed as being of limited practical significance due to its inefficiency. We demonstrate several techniques for improving the running time and memory requirements of the garbled-circuit technique, resulting in an implementation of generic secure two-party computation that is significantly faster than any previously reported while also scaling to arbitrarily large circuits. We validate our approach by demonstrating secure computation of circuits with over 109 gates at a rate of roughly 10 microseconds per garbled gate, and showing order-of-magnitude improvements over the best previous privacy-preserving protocols for computing Hamming distance, Levenshtein distance, Smith-Waterman genome alignment, and AES.