Biblio

Filters: Author is Kumaresan, Ranjit  [Clear All Filters]
2017-10-03
Kumaresan, Ranjit, Bentov, Iddo.  2016.  Amortizing Secure Computation with Penalties. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :418–429.

Motivated by the impossibility of achieving fairness in secure computation [Cleve, STOC 1986], recent works study a model of fairness in which an adversarial party that aborts on receiving output is forced to pay a mutually predefined monetary penalty to every other party that did not receive the output. These works show how to design protocols for secure computation with penalties that guarantees that either fairness is guaranteed or that each honest party obtains a monetary penalty from the adversary. Protocols for this task are typically designed in an hybrid model where parties have access to a "claim-or-refund" transaction functionality denote FCR*. In this work, we obtain improvements on the efficiency of these constructions by amortizing the cost over multiple executions of secure computation with penalties. More precisely, for computational security parameter λ, we design a protocol that implements l = poly\vphantom\\(λ) instances of secure computation with penalties where the total number of calls to FCR* is independent of l.

2017-07-24
Kumaresan, Ranjit, Vaikuntanathan, Vinod, Vasudevan, Prashant Nalini.  2016.  Improvements to Secure Computation with Penalties. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :406–417.

Motivated by the impossibility of achieving fairness in secure computation [Cleve, STOC 1986], recent works study a model of fairness in which an adversarial party that aborts on receiving output is forced to pay a mutually predefined monetary penalty to every other party that did not receive the output. These works show how to design protocols for secure computation with penalties that tolerate an arbitrary number of corruptions. In this work, we improve the efficiency of protocols for secure computation with penalties in a hybrid model where parties have access to the "claim-or-refund" transaction functionality. Our first improvement is for the ladder protocol of Bentov and Kumaresan (Crypto 2014) where we improve the dependence of the script complexity of the protocol (which corresponds to miner verification load and also space on the blockchain) on the number of parties from quadratic to linear (and in particular, is completely independent of the underlying function). Our second improvement is for the see-saw protocol of Kumaresan et al. (CCS 2015) where we reduce the total number of claim-or-refund transactions and also the script complexity from quadratic to linear in the number of parties. We also present a 'dual-mode' protocol that offers different guarantees depending on the number of corrupt parties: (1) when s

2017-10-03
Kumaresan, Ranjit, Vaikuntanathan, Vinod, Vasudevan, Prashant Nalini.  2016.  Improvements to Secure Computation with Penalties. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :406–417.

Motivated by the impossibility of achieving fairness in secure computation [Cleve, STOC 1986], recent works study a model of fairness in which an adversarial party that aborts on receiving output is forced to pay a mutually predefined monetary penalty to every other party that did not receive the output. These works show how to design protocols for secure computation with penalties that tolerate an arbitrary number of corruptions. In this work, we improve the efficiency of protocols for secure computation with penalties in a hybrid model where parties have access to the "claim-or-refund" transaction functionality. Our first improvement is for the ladder protocol of Bentov and Kumaresan (Crypto 2014) where we improve the dependence of the script complexity of the protocol (which corresponds to miner verification load and also space on the blockchain) on the number of parties from quadratic to linear (and in particular, is completely independent of the underlying function). Our second improvement is for the see-saw protocol of Kumaresan et al. (CCS 2015) where we reduce the total number of claim-or-refund transactions and also the script complexity from quadratic to linear in the number of parties.