TASTY: Tool for Automating Secure Two-partY computations. Secure two-party computation allows two untrusting parties to jointly compute an arbitrary function on their respective private inputs while revealing no information beyond the outcome. Existing cryptographic compilers can automatically generate secure computation protocols from high-level specifications, but are often limited in their use and efficiency of generated protocols as they are based on either garbled circuits or (additively) homomorphic encryption only. In this paper we present TASTY, a novel tool for automating, i.e., describing, generating, executing, benchmarking, and comparing, efficient secure two-party computation protocols. TASTY is a new compiler that can generate protocols based on homomorphic encryption and efficient garbled circuits as well as combinations of both, which often yields the most efficient protocols available today. The user provides a high-level description of the computations to be performed on encrypted data in a domain-specific language. This is automatically transformed into a protocol. TASTY provides most recent techniques and optimizations for practical secure two-party computation with low online latency. Moreover, it allows to efficiently evaluate circuits generated by the well-known Fairplay compiler. We use TASTY to compare protocols for secure multiplication based on homomorphic encryption with those based on garbled circuits and highly efficient Karatsuba multiplication. Further, we show how TASTY improves the online latency for securely evaluating the AES functionality by an order of magnitude compared to previous software implementations. TASTY allows to automatically generate efficient secure protocols for many privacy-preserving applications where we consider the use cases for private set intersection and face recognition protocols.

This software is also peer reviewed by journal TOMS.

References in zbMATH (referenced in 11 articles )

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  1. Applebaum, Benny: Garbling XOR gates “for free” in the standard model (2016)
  2. Dagdelen, Özgür; Mohassel, Payman; Venturi, Daniele: Rate-limited secure function evaluation (2016)
  3. Frederiksen, Tore Kasper; Jakobsen, Thomas P.; Nielsen, Jesper Buus: Faster maliciously secure two-party computation using the GPU (2014)
  4. Kerschbaum, Florian; Schneider, Thomas; Schröpfer, Axel: Automatic protocol selection in secure two-party computations (2014)
  5. Frederiksen, Tore Kasper; Jakobsen, Thomas Pelle; Nielsen, Jesper Buus; Nordholt, Peter Sebastian; Orlandi, Claudio: MiniLEGO: efficient secure two-party computation from general assumptions (2013)
  6. Huang, Yan; Katz, Jonathan; Evans, David: Efficient secure two-party computation using symmetric cut-and-choose (2013)
  7. Damgård, Ivan; Keller, Marcel; Larraia, Enrique; Miles, Christian; Smart, Nigel P.: Implementing AES via an actively/covertly secure dishonest-majority MPC protocol (2012)
  8. Mohassel, Payman; Niksefat, Salman; Sadeghian, Saeed; Sadeghiyan, Babak: An efficient protocol for oblivious DFA evaluation and applications (2012)
  9. Nielsen, Jesper Buus; Nordholt, Peter Sebastian; Orlandi, Claudio; Burra, Sai Sheshank: A new approach to practical active-secure two-party computation (2012)
  10. Ateniese, Giuseppe; De Cristofaro, Emiliano; Tsudik, Gene: (If) size matters: size-hiding private set intersection (2011)
  11. Katz, Jonathan; Malka, Lior: Constant-round private function evaluation with linear complexity (2011)