Systems and methods for configuring a reduced instruction set computer processor architecture to execute fully homomorphic encryption (FHE) logic gates as a streaming topology. The method includes parsing sequential FHE logic gate code, transforming the FHE logic gate code into a set of code modules that each have in input and an output that is a function of the input and which do not pass control to other functions, creating a node wrapper around each code module, configuring at least one of the primary processing cores to implement the logic element equivalents of each element in a manner which operates in a streaming mode wherein data streams out of corresponding arithmetic logic units into the main memory and other ones of the plurality arithmetic logic units.

Secure data analytics is provided via a process that identifies sensitive data fields of an initial dataset and mappings between the sensitive data fields and other data fields of the dataset, where analytics processing is to be performed on the initial dataset, then, based on an expectation of data fields, of the initial data set, to be used in performance of the analytics processing and on the identified sensitive data fields, selects and applies a masking method to the initial dataset to mask the sensitive data fields and produce a masked dataset, provides the masked dataset to an analytics provider with a request for the analytics processing, and receives, in response, a generated analytics function, generated based on the masked dataset, that is configured to perform the analytics processing, and invokes the generated analytics function against the initial dataset to perform the analytics processing on the initial dataset.

Systems and methods for digital circuit emulation with homomorphic encryption include: receiving, by a hardware design tool chain, a customization file containing a predetermined set of one or more cells; converting, by the hardware design tool chain, a first digital circuit representation in a set of hardware design language (HDL) files into a second digital circuit representation based on the predetermined set of cells in the customization file; receiving, by an encrypted circuit emulator, a set of encrypted inputs; and executing, by the encrypted circuit emulator, the second digital circuit representation using the set of encrypted inputs to generate a set of encrypted outputs.

In one embodiment, a set of feature vectors can be derived from any biometric data, and then using a deep neural network (“DNN”) on those one-way homomorphic encryptions (i.e., each biometrics' feature vector) an authentication system can determine matches or execute searches on encrypted data. Each biometrics' feature vector can then be stored and/or used in conjunction with respective classifications, for use in subsequent comparisons without fear of compromising the original biometric data. In various embodiments, the original biometric data is discarded responsive to generating the encrypted values. In another embodiment, the homomorphic encryption enables computations and comparisons on cypher text without decryption of the encrypted feature vectors. Security of such privacy enable biometrics can be increased by implementing an assurance factor (e.g., liveness) to establish a submitted biometric has not been spoofed or faked.

Embodiments described herein enable data associated with a large plurality of users to be analyzed without compromising the privacy of the user data. In one embodiment, a user can opt-in to allow analysis of clear text of the user's emails. An analysis process can then be performed in which an analysis service receives clear text of an email of a client device; processes the clear text of the email into one or more tokens having one or more tags; enriches one or more tokens in the processed email using data associated with a user of the client device and the one or more tags; and processes the clear text and one or more enriched tokens to generate a data set of one or more feature vectors.

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.

A method and a system of selective encryption of a test dataset is disclosed. In an embodiment, the method may include determining a relevancy grade associated with each of a plurality of datapoints within a test dataset by comparing the test dataset with a common heat map, wherein the common heat map is generated using a plurality of training datasets. The method may further include calculating, based on the relevancy grade, an encryption level associated with each of the plurality of datapoints. The method may further include selectively encrypting at least one datapoint from the plurality of datapoints based on the encryption level associated with each of the plurality of datapoints. The at least one data point is rendered to a user after being decrypted.

A method for recognizing and/or identifying a user (9) with a chip (C) in an electronic identity object storing a digital identity (24), the method comprising steps of: —establishing a wireless or electrical connection between the electronic identity object (C) and a verification terminal (T); —verifying, in the electronic identity object, if the verification terminal is authorized to communicate with the electronic identity object (C), and in response of a positive verification sharing a secret (K): using the shared secret (K) for establishing an encrypted symmetric data link (5) between the electronic identity object and the verification terminal (T); transmitting, through the encrypted data link (5), said digital identity (24) stored in the electronic identity object to the verification terminal (T); and verifying in the verification terminal (T) the authenticity of said digital identity (24).

Systems and methods are provided for receiving input data to be processed by an encrypted neural network (NN) model, and encrypting the input data using a fully homomorphic encryption (FHE) public key associated with the encrypted NN model to generate encrypted input data. The systems and methods further provided for processing the encrypted input data to generate an encrypted inference output, using the encrypted NN model by, for each layer of a plurality of layers of the encrypted NN model, computing an encrypted weighted sum using encrypted parameters and a previous encrypted layer, the encrypted parameters comprising at least an encrypted weight and an encrypted bias, approximating an activation function for the level into a polynomial, and computing the approximated activation function on the encrypted weighted sum to generate an encrypted layer. The generated encrypted inference output is sent to a server system for decryption.

A homomorphic encryption processing device includes the processing circuitry is configured to generate ciphertext operation level information based on field information. The field information represents a technology field to which homomorphic encryption processing is applied. The ciphertext operation level information represents a maximum number of multiplication operations between homomorphic ciphertexts without a bootstrapping process. The processing circuitry is further configured to select and output a homomorphic encryption parameter based on the ciphertext operation level information. The processing circuitry is further configured to perform one of a homomorphic encryption, a homomorphic decryption and a homomorphic operation, based on the homomorphic encryption parameter. The homomorphic encryption processing device may adaptively generate a homomorphic encryption parameter according to a ciphertext operation level information determined based on a field information, and may perform a homomorphic encryption, a homomorphic decryption and a homomorphic operation based on the homomorphic encryption parameter.