Computer-implemented systems and methods are disclosed herein for use within secure multi-party computation. A system and method are used for storing an operation preference and a cryptographic preference. A data set is stored based on the operation preference and the cryptographic preference. A determination is made that processing the query involves performing an allowable operation on the data set based on the operation preference.

Methods, systems, and devices for homomorphic encryption. In one implementation, the methods include inputting first data into a recurrent artificial neural network, identifying patterns of activity in the recurrent artificial neural network that are responsive to the input of the secure data, storing second data representing whether the identified patterns of activity comports with topological patterns, and statistically analyzing the second data to draw conclusions about the first data.

Various embodiments include a first node for providing a function to a second node for evaluation, the first node configured to form a first plurality of garbled circuits for the function, each circuit being formed from a circuit representing the function and a respective set of wire keys and including one or more logic operations, one or more input wires for inputting data into the circuit and one or more output wires for outputting the result of the function, wherein each respective set of wire keys comprises a respective subset of wire keys for each input wire and each output wire, each subset of wire keys comprising a plurality of wire keys, each wire key in the plurality being associated with a possible value for the wire; and publish a first list of the first plurality of garbled circuits for the function for access by a plurality of second nodes.

A share [x].sub.i of plaintext x in accordance with Shamir's secret sharing scheme is expressed by N shares [x.sub.0].sub.i, . . . , [x.sub.N−1].sub.i, and each share generating device A.sub.i obtains a function value r.sub.i=P.sub.m(i(−))(s.sub.i) of a seed s.sub.i, obtains a first calculated value ζ.sub.i=λ(i, i(−))[x.sub.i(−)].sub.i+r.sub.i using a Lagrange coefficient λ(i, i(−)), a share [x.sub.i(−)].sub.i, and the function value r.sub.i, and outputs the first calculated value ζ.sub.i to a share generating device A.sub.i(−). Each share generating device A.sub.i accepts a second calculated value ζ.sub.i(+), obtains a third calculated value z.sub.i=λ(i, i(+))[x.sub.i].sub.i+ζ.sub.i(+) using a Lagrange coefficient λ(i, i(+)), a share [x.sub.i].sub.i, and the second calculated value ζ.sub.i(+), and obtains information containing the seed s.sub.i and the third calculated value z.sub.i as a share SS.sub.i of the plaintext x in secret sharing and outputs the share SS.sub.i.

Some embodiments are directed to a computation device configured for batch-wise multiparty verification of a computation which has been performed multiple times. The computations being multiparty computations that are cryptographically shared between the computation device and multiple other computation devices. The computation device is configured to perform the computation a further time to obtain a randomizing computation on a randomizing set of values.

A computer node comprising multiple software modules may receive a cryptographic key from a hardware security module. The computer node may use the cryptographic key to produce two key portions, which are distributed to two software modules. These software modules and an optional additional software module may use the key portions in order to encrypt an initial message. The key portions and their locations in memory are periodically updated in order to provide improved cryptographic security.

A system and method for securing application programming interface (API) requests using multi-party digital signatures. The method includes generating, by a first system, at least one first secret share of a plurality of secret shares based on an API secret, wherein the plurality of secret shares includes the at least one first secret share and at least one second secret share, wherein the at least one second secret share is generated by at least one second system; and signing, by the first system, an API request using the at least one first secret share, wherein the API request is further signed by the at least one second system using the at least one second secret share, wherein the API request is signed without revealing any of the at least one first secret share to the at least one second system and without revealing any of the at least one second secret share to the first system.

Provided is a data distribution method for a data distribution system which includes a device and a plurality of authentication servers. The data distribution method includes: receiving, by a first authentication server included in the plurality of authentication servers, transaction data including encrypted history information which is history information of the device encrypted using a secure computation method which enables computation without decrypting the encrypted history information; recording, by the first authentication server, the transaction data in a distributed ledger in synchronization with the plurality of authentication servers excluding the first authentication server, when a validity of the transaction data received from the device is verified by the first authentication server; and performing, by the first authentication server, secure computation on the encrypted history information included in the transaction data, the secure computation being computation processing performed without decrypting the encrypted history information.

Described are a system and method for secure n-party computation. The method includes communicating a first input of an n-party computation to a trusted execution environment (TEE). The method also includes receiving, from the TEE, at least one encrypted output of the n-party computation using the first input and at least one second input of at least one other computing device, and using at least one public key of the at least one other computing device. The method further includes posting the at least one encrypted output on at least one blockchain accessible by the at least one other computing device. The method further includes, in response to posting the at least one encrypted output, receiving at least one proof of publication. The method further includes communicating the at least one proof of publication to the TEE and receiving the function output of the n-party computation.

A parameter estimation device for executing a parameter estimation of a cox proportional hazard model by secure computation comprises: a data storage unit that stores a database having, with respect to each object to be observed, a record including a point of time at which an event was observed, a feature amount of an object to be observed at the point of time, and a state of the object to be observed at the point of time; a calculation unit that, by reading a vector comprising points of time from the database, and sorting the vector, generates a replacement table and a flag indicating a boundary between the points of time, by using the replacement table and the flag, totalizer the feature amounts at the respective points of time while concealing values at the points of time, and performs the parameter estimation on the basis of a result of the totalization; and an output unit that outputs a parameter estimated by the calculation unit.