Abstract: A dealer receives a first addend function and a second addend function. A function client provides first validation parameters, each first validation parameter corresponding to a coefficient of the first addend function and a corresponding coefficient of the second addend function. The sum of the first addend function and the second addend function equals the polynomial function. The dealer generates a function share for each share party based on a sampling of first random polynomials and second random polynomials and generates second validation parameters for each share party based on the function shares. The dealer transmits the second validation parameters to the share parties and transmits each function share to a corresponding share party. Each function share is verifiable by the corresponding share party based on the second validation parameters and a signed concatenation of the first validation parameters.

Abstract: Described are methods for protecting biometric templates using secret sharing in such a way that authentication can be performed without reconstruction of the biometric template. This can help protect against the security and privacy risks of storing biometric templates. Accordingly, the described methods use k-out-of-n secret sharing to distribute the template to some a number of parties, and when a user wishes to authenticate, k shares of a newly generated input template (produced from input biometrics) may be distributed by additive secret sharing to k parties. Each party computes a parameter based on its share of the biometric template and the input template without receiving any information about the other shares. The parameters are combined in a way that produces a Hamming distance, which may be compared to an authentication threshold to determine authenticity of the input.

Abstract: Disclosed are methods for electronic device authentication in which distinguishing physical characteristics of electronic devices are converted into unique identification strings (UIDs) that can be used like fingerprints to verify device authenticity. Such methods may be used for tamper detection, for example in combatting warranty fraud. UIDs may be generated from physical characteristics that are unique to a given device, such as imperfections on the device exterior or unique aspects of a circuit board. Images of the device in selected areas or at selected angles may be captured and provided to an algorithm that converts the physical characteristics of the physical device into a UID, for example making use of a fuzzy extractor. When a device is presented for authentication, images of the device may be similarly converted into a verification string that can be checked against the UID.

Abstract: A dealer receives a first addend function and a second addend function. A function client provides first validation parameters, each first validation parameter corresponding to a coefficient of the first addend function and a corresponding coefficient of the second addend function. The sum of the first addend function and the second addend function equals the polynomial function. The dealer generates a function share for each share party based on a sampling of first random polynomials and second random polynomials and generates second validation parameters for each share party based on the function shares. The dealer transmits the second validation parameters to the share parties and transmits each function share to a corresponding share party. Each function share is verifiable by the corresponding share party based on the second validation parameters and a signed concatenation of the first validation parameters.

Abstract: A third party cryptographically determines a private set difference between a data set of a first party and a data set of a second party. The third party cryptographically generates a key pair including a private key and a public key, provides the public key to the first party and the second party, receives an encrypted result from the second party, wherein the encrypted result is computed prior to receipt by the third party using homomorphic operations performed using the public key, the data set of the first party, and the data set of the second party, decrypts the encrypted result using the private key to yield an intermediate data set, and determines the private set difference between the first data set and the second data set based on the intermediate data set.

Abstract: A method computes, by a third party, a private set intersection of datasets of multiple input parties, wherein each dataset includes one or more data elements. The computer-processor-implemented method includes: obtaining one or more share polynomials for each dataset of the multiple input parties, the one or more share polynomials for a dataset of an input party being encoded from shares of zero for the input party, each share of zero corresponding to a data element of the dataset of the input party; determining an intersection polynomial based on the one or more share polynomials; and determining the private set intersection of the datasets to include data elements of the datasets of the multiple input parties for which the intersection polynomial of the multiple input parties solves to zero.

Abstract: A third party cryptographically determines a private set difference between a data set of a first party and a data set of a second party. The third party cryptographically generates a key pair including a private key and a public key, provides the public key to the first party and the second party, receives an encrypted result from the second party, wherein the encrypted result is computed prior to receipt by the third party using homomorphic operations performed using the public key, the data set of the first party, and the data set of the second party, decrypts the encrypted result using the private key to yield an intermediate data set, and determines the private set difference between the first data set and the second data set based on the intermediate data set.

Abstract: A secret sharing scheme with yes and no shares and having a hidden access structure. The secret sharing scheme may include share generation in which yes shares and no shares are generated for, and distributed to, each party in the secret sharing scheme. In turn, upon an attempt to reconstruct the secret, participants in the reconstruction each provide a share, which is unknown to be a yes share or a no share to the other participants. The secret is only reconstructable if the shares used in the reconstruction include yes shares of a minimal authorized subset of the parties. However, prior to secret reconstruction, the access structure remains hidden and the participants in a reconstruction are unaware of the character of the shares provided by other participants in the reconstruction attempt.

Abstract: Cryptographic sharing of a cryptographic secret among multiple parties provides a share of the cryptographic secret is generated for each party. Multiple threshold access structure tokens are generated for each party of the multiple parties. The threshold access structure tokens are generated for a party from one or more random token polynomials selected from a finite field based on the numbers of the multiple parties capable of attempting to reconstruct the cryptographic secret. The share of the cryptographic secret and the multiple threshold access structure tokens generated for each party are distributed to the corresponding party. At least a threshold number of the parties can reconstruct the cryptographic secret using the shares of the cryptographic secret and threshold access structure tokens corresponding to at least a threshold number of the parties attempting to reconstruct the cryptographic secret while less than the threshold number of parties cannot reconstruct the cryptographic secret.

Abstract: Polynomial function secret sharing provides for computation of reconstruction share results for a polynomial function on an input. An allocatable share of the polynomial function is received at a computing system of the share result computation systems. The allocatable share is generated from the polynomial function. Each of the allocatable shares is distributed to a unique share result computation system of the share result computation systems. Each allocatable share includes a share element for each coefficient in the polynomial function, wherein the share elements for a coefficient across the share result computation systems summing to the coefficient. A reconstruction share result is generated at the computing system by computing a dot product of the input and the allocatable share received by the computing system. A combination of the reconstruction share results generated by the share result computation systems yields a reconstructed result of the polynomial function on the input.

Abstract: Polynomial function secret sharing provides for computation of reconstruction share results for a polynomial function on an input. An allocatable share of the polynomial function is received at a computing system of the share result computation systems. The allocatable share is generated from the polynomial function. Each of the allocatable shares is distributed to a unique share result computation system of the share result computation systems. Each allocatable share includes a share element for each coefficient in the polynomial function, wherein the share elements for a coefficient across the share result computation systems summing to the coefficient. A reconstruction share result is generated at the computing system by computing a dot product of the input and the allocatable share received by the computing system. A combination of the reconstruction share results generated by the share result computation systems yields a reconstructed result of the polynomial function on the input.

Abstract: The disclosure provides systems and methods for a multi-party secret sharing protocol that includes determining device channel errors of a plurality of computing devices based on channel impulse response (CIR) of communication channels of the plurality of computing devices, training a linear regression model using the device channel errors to generate learning with error (LWE) secrets for each of the plurality of computing devices, generating a general access structure secret matrix using the LWE secrets from each of the plurality of computing devices, and distributing shares of the general access structure secret matrix to the plurality of computing devices based on a multi-party secret sharing protocol.

Abstract: A computing system cryptographically generates an intermediate message authentication code as a function of the message and a cryptographic key assigned to a first party. The computing system also generates a first instance of an aggregate message authentication code corresponding to the message by combining the intermediate message authentication code with one or more other intermediate message authentication codes of one or more second parties. Each code of the one or more other intermediate message authentication codes is cryptographically generated as a function of the message and individual cryptographic key assigned to each of the one or more second parties.

Abstract: A computing system determines a maximum field size for a field containing values of quantized versions of a weight matrix, an input data matrix, and a bias matrix and determines a weight upper bound of scaling factors for the weight matrix based on values of the weight matrix, an input data upper bound of scaling factors for the input data matrix based on values of the input data matrix, and a bias upper bound of scaling factors for the bias matrix based on values of the bias matrix. The computing system also sets a weight scaling factor of the weight matrix, an input data scaling factor of the input data matrix, and a bias scaling factor for the bias matrix in two different cases: when the sum is less than or equal to the bias upper bound and when the sum is greater than the bias upper bound.

Abstract: Evolving function secret sharing is performed on a given function by multiple share parties, A dealer selects a random vector for each share party corresponding to an arrival order. The dealer generates an array of function shares for each share party of the set, each array including a function share based on the random vector corresponding to the share party and one or more function shares cryptographically generated based on the random vector corresponding to each previously-arrived share party. The dealer distributes an array of the function shares to each share party, wherein a first function share result resulting from a computation of a first function share on given input data and at least a second function share result resulting from a computation of a second function share on the given input data are combinable to yield a result of the given function executed on the given input data.

Abstract: A private set intersection protocol in which a third party may determine intersections of a first set of a first party and a second set of a second party. The third party may not obtain any information regarding the first set or the second set other than the intersection result. The protocol may be communicatively efficient and computationally efficient to allow for secure private set intersection to be performed.

Abstract: A secret sharing scheme with yes and no shares and having a hidden access structure. The secret sharing scheme may include share generation in which yes shares and no shares are generated for, and distributed to, each party in the secret sharing scheme. In turn, upon an attempt to reconstruct the secret, participants in the reconstruction each provide a share, which is unknown to be a yes share or a no share to the other participants. The secret is only reconstructable if the shares used in the reconstruction include yes shares of a minimal authorized subset of the parties. However, prior to secret reconstruction, the access structure remains hidden and the participants in a reconstruction are unaware of the character of the shares provided by other participants in the reconstruction attempt.

Abstract: A secret sharing scheme with yes and no shares and having a hidden access structure. The secret sharing scheme may include share generation in which yes shares and no shares are generated for, and distributed to, each party in the secret sharing scheme. In turn, upon an attempt to reconstruct the secret, participants in the reconstruction each provide a share, which is unknown to be a yes share or a no share to the other participants. The secret is only reconstructable if the shares used in the reconstruction include yes shares of a minimal authorized subset of the parties. However, prior to secret reconstruction, the access structure remains hidden and the participants in a reconstruction are unaware of the character of the shares provided by other participants in the reconstruction attempt.

Abstract: A function is decomposed into a plurality of function shares. The function returns a Boolean result based on whether an input y satisfies a query on a data set. The function shares hide the function from non-collaborating entities that separately execute the function shares. Each of the functions shares are sent to one of a plurality of servers having a same data set. The function shares are executed on the data set at the servers to obtain a respective plurality of shares. A conditional disclosure of secrets operation is simulated on the shares and the input y. The conditional disclosure of secrets operation uses a secret known to at least one of the servers, and further uses a source of randomness shared between the servers. A Boolean value corresponding to the Boolean result is returned based on the conditional disclosure of secrets operation returning the secret.

Abstract: A function secret sharing (FSS) scheme that facilitates multiple evaluations of a secret function. The FSS scheme includes a function share based on a secret function and at least one key of a key-homomorphic pseudo random function (PRF). At least one key and a function share are provided to each party in the FSS scheme. In turn, each party may generate an output share comprising a function share output evaluated at a function input and a masking component generated based on the at least one key in relation to the key-homomorphic PRF. In turn, the output shares of each participating party may be combined to evaluate the secret function. The FSS scheme facilitates multiple evaluations of the secret function without leaking information regarding the secret function.