本发明提供一种基于椭圆曲线的乘法三元组生成方法、装置、设备及介质，该方法适用于第一参与节点，包括：选取随机非负整数x(1)和y(1)，对x(1)进行基于椭圆曲线的同态加密处理得到第一密文，将第一密文发送至预先选取有随机非负整数x(2)和y(2)的另一参与节点，以使另一参与节点将y(2)与所述第一密文进行同态数乘运算后再与预先选取的第二随机数r(2)相加，得到第一随机化结果后返回至所述第一参与节点；对所述第一随机化结果进行基于椭圆曲线的同态解密处理，得到第一解密结果，而后根据第一解密结果计算第一乘积z(1)，并根据第一乘积生成第一三元组(x(1),y(1),z(1))。本发明能够在椭圆曲线密码体系上生成乘法三元组，并且不会浪费乘法三元组的取值空间。

基于椭圆曲线的乘法三元组生成方法、装置、设备及介质

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to generate a pair of synthetic stereo images and a corresponding synthetic depth map with an image synthesis engine wherein the synthetic stereo images correspond to real stereo images acquired by a stereo camera and the synthetic depth map is a three-dimensional (3D) map corresponding to a 3D scene viewed by the stereo camera and process each image of the pair of synthetic stereo images pair independently using a generative adversarial network (GAN) to generate a fake image, wherein the fake image corresponds to one of the synthetic stereo images. The instructions can further include instructions to process a stereo pair of fake images to form a fake depth map, compare the fake depth map to the synthetic depth map using a Siamese one-shot neural network, train a deep neural network to determine an object using one or more of the fake images generated by the GAN, and operate a vehicle based on the object.

Vehicle image verification

Methods, systems and computer program products for data analytics. An information ecosystem comprises a plurality of participants and a plurality of data sets associated with the participants. An event initiates performance of a computation over different obfuscated data sets to determine an obfuscated computational result. An integrity value pertaining to constituent data of the different obfuscated data sets and, correspondingly, an integrity value pertaining to the computational result itself, is quantified by checking if the earlier offered data set or any constituents thereof are consistent with one or more aspects of later retrieved data. Certain variations of methods, systems and computer program products are used for verifying data accuracy in privacy-preserving computations that are performed in a health ecosystem where the data sets pertain to health information associated with the participants. When the integrity value is below a threshold, the data is deemed to include falsified or inaccurate data.

Verifying data accuracy in privacy-preserving computations

Methods, systems and computer program products for data analytics. Multiple components are interconnected to carry out operations for said data analytics. A method commences upon establishing a connection with a user device that is associated with a user. The user operates the user device to produce a plurality of datasets that correspond to a plurality of differing data regimes. The plurality of datasets from the different data regimes are analyzed to determine spatial and temporal correlations between the datasets. The quality score is in turn based on the determined spatial and temporal correlations. To improve the quality score, specific action requests are sent to the user device. The specific action requests are based on a comparison between the quality score and a quality score threshold. To protect against spoofing, capture time windows of respective datasets selected from the differing data regimes are analyzed to verify the provenance of the datasets.

Measuring and increasing the quality of user-provided information

Methods, systems, and computer program products for health data management. A user obtains a biomaterial collection kit that provides a unique identifier that is matched to a biomaterial specimen container. The identity of any user is not associated with any unit of the biomaterial kit. The user retains their unique identifier and mails their biomaterial (e.g., hair, saliva, etc.) anonymously to a lab. The lab analyzes the biomaterial sample to produce anonymous analysis results. The lab broadly publishes the anonymous analysis results to a publicly-accessible network location (e.g., the Internet). At will, users access the publicly-accessible repository to initiate compute operations on the published entries. If a particular user's identifier matches a published entry (e.g., if the entry can be decrypted using that particular user's unique identifier), then that user can gain access to that published entry while being unable to match to or decrypt any other user's published entries.

Deniable digital health diagnoses

Methods, systems and computer program products for health data protection. Embodiments commence upon receiving a data access request message from a participant in a health ecosystem. The data access request message comprises an indication of one or more health data sets that are held by or at least potentially of interest to the participant. System components are configured to receive the message and to identify the participant. Based on parameter values corresponding to a data protection policy of the participant, a data protection scheme is generated. The scheme includes parameter values derived from the data protection policy. The parameter values of the scheme are used to generate a variation of the health data set that is formed by applying one or more data anonymization, data obfuscation or other data protection techniques to the health data set. A balance among the parameters is calculated so as to achieve a desired outcome.

Dynamic data protection

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Verifying data accuracy in privacy-preserving computations

Measuring and increasing the quality of user-provided information

Deniable digital health diagnoses

Dynamic data protection