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.

A method includes receiving, on a computer-implemented system and from user, an identification of data and an identification of an algorithm and, based on a user interaction with the computer-implemented system comprising a one-click interaction or a two-click interaction. Without further user input, the method includes dividing the data into a data first subset and a data second subset, dividing the algorithm (or a Boolean logic gate representation of the algorithm) into an algorithm first subset and an algorithm second subset, running, on the computer-implemented system at a first location, the data first subset with the algorithm first subset to yield a first partial result, running, on the computer-implemented system at a second location separate from the first location, the data second subset with the algorithm second subset to yield a second partial result and outputting a combined result based on the first partial result and the second partial result.

A bit-decomposition secure computation apparatus uses r1, r2, and r3 satisfying w=r1+r2+r3 mod 2{circumflex over ()}n as share information of (2, 3) threshold type RSS (Replicated Secret Sharing) stored in a share value storage apparatus, and includes an addition sharing part that sums two values out of the share information by modulo 2{circumflex over ()}n arithmetic and distributes the sum using (2, 3) type RSS; and a full adder secure computation part that adds the value generated by the addition sharing part by distributing the sum of the two values to share information of one remaining value other than the two values used by the addition sharing part for each digit by using secure computation of a full adder.

Data is efficiently read from and written in a sequence without an access position being revealed. A secure reading and writing apparatus (1) receives a read command or a write command as input, and, when the read command is input, outputs a secret text [a[x]] which is an x-th element of a secret text sequence [a], and, when the write command is input, adds the secret text [a[x]] which is the x-th element of the secret text sequence [a], to a secret text [d]. A secure reading part (12) reads the secret text [a[x]] which is the x-th element from the secret text sequence [a]. A buffer addition part (13) adds a secret text [c] of an unreflected value c to the secret text [a[x]].

A buffer appending part (14) appends a secret text [x] and the secret text [d] to a write buffer [b]. When the number of elements of the write buffer [b] exceeds a predetermined value, a secure writing part (15) adds a value indicated with a secret text vector [b.sub.1] to an access position of the secret text sequence [a] which is indicated with a secret text vector [b.sub.0].

A garbled circuit and two garbled inputs are received by a server from each pair of a plurality of clients. The garbled circuit encodes a comparison function and the garbled inputs encode a respective data value from each of the clients in each pair. Thereafter, the server evaluates the garbled circuits using the corresponding garbled inputs to result in a plurality of comparison bits. The server can then sort the datasets in an ascending or descending order by using the comparison bits to compute the rank of each data value. Using the sorted datasets, the server determines a median value for the datasets and transmits data characterizing the median value to each of the clients.

A server receives a corresponding data value encrypted using a common threshold public key from each of a plurality of clients. The server distributes the received data values to the clients for evaluating comparison of values. The server receives the encrypted comparison results from each of the clients in response to the distribution of the received encrypted data values. The comparison results are encrypted using the common key. The server homomorphically determines a ciphertext encrypting the rank of each client's data value using the comparison results. Further, the server can compute a ciphertext encrypting the median of the datasets. Thereafter, the server can initiate a threshold decryption to generate a final result.

This application describes systems and methods for using a garbled circuit and a physical unclonable function (PUF) value to authenticate a device. During enrollment, the device and at least one computer collaboratively construct multiple garbled circuits corresponding to bits of an enrollment PUF value generated by PUF circuitry coupled to the device. During authentication, the device and at least one computer evaluate the multiple garbled circuits using an authentication PUF value. Using the results of this evaluation, the at least one computer compares the enrollment PUF value with the authentication PUF value and determines a distance between them. The at least one computer may authenticate the device when the calculated distance is less than a threshold value.

A biometric matching process is disclosed. The biometric matching process may be used to obtain access to a resource managed by an access device using only biometric information. In some embodiments, a biometric template is stored in relation to a user device and/or account information, and is obscured. Upon receiving a request for access to a resource from an access device, the system may identify a number of user devices in proximity to the access device. Biometric templates associated with each of those user devices may be compared to a biometric template received from the access device. Upon identifying a match, the system may provide the access device with account information stored in relation to the matched biometric template. The access device may then complete a transaction using the provided account information and grant access to the requested resource.

Described is a system for jointly generating a random value amongst a set of servers for secure data sharing. The set of servers initiates a randomness generation protocol where each server in the set of servers selects a randomly generated polynomial and broadcasts a cryptographic hash function of the randomly generated polynomial. Each server sends its value of the cryptographic hash function of the randomly generated polynomial to the set of servers. The randomness generation protocol is used in a multi-party computation protocol to ensure a set of data is securely shared electronically amongst the set of servers via a secure, authenticated broadcast channel.

An assigned share which is a proper subset of a subshare set with a plurality of subshares as elements, and meta information indicating values according to the elements of the subshare set or indicating that the elements are concealed values are stored. When a value according to a provided corresponding value according to a subset of the assigned share is not obtained from the meta information, a provided value according to the provided corresponding value obtained from the subset of the assigned share is outputted. When a value according to an acquired corresponding value according to a subset of an external assigned share, which is a proper subset of the subshare set, is not obtained from the meta information, input of an acquired value according to the acquired corresponding value is accepted. When the acquired value is inputted, a secret share value is obtained at least using the acquired value.