Abstract: An identity recognition method, an apparatus, a computer device, and a storage medium are provided. The method includes: obtaining a signal to be identified which includes a millimeter wave signal and an audio signal; performing living feature detection based on the millimeter wave signal and the audio signal, and acquiring a living millimeter wave signal and a living audio signal; performing feature fusion of the living millimeter wave signal and the living audio signal, and acquiring a fusion response diagram of a living voice signal; and performing identity recognition based on the fusion response diagram of the living voice signal.

Abstract: A method and an apparatus for privacy protection biometric authentication and an electronic device. The method comprises the following steps: constructing a corresponding a biological data template according to a biological information data set input by a user when registering; generating a pair of public key and private key by asymmetric cryptography technology; generating encrypted biological data by a secret sharing solution and OKVS technology according to the biological data template and the private key; sending the public key and the encrypted biological data to a server; recovering the private key by OKVS technology according to the biological data input by the user during authentication and the encrypted biological data; constructing a signature according to the recovered private key and the corresponding public key; sending the signature to the server, so that the server verifies the user according to the public key and the signature.

Abstract: The present invention discloses a method for designing an interference noise of speech based on the human speech structure, including the following steps: (1): obtaining a large amount of speech data containing different speakers and different speech contents, extracting voiceprint information, and then building an initial speech data set; (2): for each user, obtaining a small amount of speech data of the user, extracting voiceprint information, and then matching the most similar speech data in the initial speech data set; (3): performing data augmentation on the matched speech data; (4): segmenting the augmented speech data with a phoneme segmentation algorithm to form a vowel data set and a consonant data set; (5): constructing three noise sequences based on the vowel data set and the consonant data set, and performing superimposition to obtain an interference noise; and (6): continuously generating and playing randomly generated interference noise, and continuously injecting the interference noise into rec

Abstract: A batch private information retrieval method and apparatus, including: agreeing on a hash function, calculating a serial number index in an original database, retaining a result of each serial number index for each hash function, and obtaining a first hash bucket; filling an index of a batch query into a second hash bucket of a same length as the first hash bucket by the client, and encoding a filling result by using a constant weight code encoding manner; encrypting an obtained encoding result as a batch query request by the client; comparing the batch query request with the first hash bucket by the server to obtain a corresponding intermediate result, calculating correspondingly the intermediate result and the original database to obtain a corresponding query result ciphertext; and decrypting the query result ciphertext by the client, and thus simultaneously obtaining a query result of the batch query request.

Abstract: A batch private information retrieval method and apparatus, including: agreeing on a hash function, calculating a serial number index in an original database, retaining a result of each serial number index for each hash function, and obtaining a first hash bucket; filling an index of a batch query into a second hash bucket of a same length as the first hash bucket by the client, and encoding a filling result by using a constant weight code encoding manner; encrypting an obtained encoding result as a batch query request by the client; comparing the batch query request with the first hash bucket by the server to obtain a corresponding intermediate result, calculating correspondingly the intermediate result and the original database to obtain a corresponding query result ciphertext; and decrypting the query result ciphertext by the client, and thus simultaneously obtaining a query result of the batch query request.

Abstract: An information retrieval method and apparatus, a computer device, and a storage medium are provided. The method includes receiving a request ciphertext sent by a client, the request ciphertext including an encrypted first code, the first code being generated based on a request entry of the client and a preset encoding algorithm; performing distributed matching on a plurality of candidate codes based on the request ciphertext to determine a second code matching the request ciphertext, the candidate codes being generated based on index entries of a database and the preset encoding algorithm; and sending a request information ciphertext associated with the index entry corresponding to the second code to the client.

Abstract: The disclosure provides a multimodal speech recognition method and system, and a computer-readable storage medium. The method includes calculating a first logarithmic mel-frequency spectral coefficient and a second logarithmic mel-frequency spectral coefficient when a target millimeter-wave signal and a target audio signal both contain speech information corresponding to a target user; inputting the first and the second logarithmic mel-frequency spectral coefficient into a fusion network to determine a target fusion feature, where the fusion network includes at least a calibration module and a mapping module, the calibration module is configured to perform mutual feature calibration on the target audio/millimeter-wave signals, and the mapping module is configured to fuse a calibrated millimeter-wave feature and a calibrated audio feature; and inputting the target fusion feature into a semantic feature network to determine a speech recognition result corresponding to the target user.

Abstract: A multi-party privacy computing method and device based on semi-trusted hardware, wherein the method applied to semi-trusted hardware comprises the following steps: acquiring random number masks and random seeds of all user terminals; generating a garbled circuit seed according to the random seeds; generating a garbled circuit according to a predetermined circuit description and the garbled circuit seed, wherein the garbled circuit comprises garbled tables, wire labels and decoding information; sending the wire labels corresponding to the inputs of all user terminals to a user terminal corresponding to the semi-trusted hardware by using an oblivious transfer protocol; and sending the garbled table and the decoding information to the user terminal corresponding to the semi-trusted hardware, so that the user terminal can compute an output value according to the garbled tables, the decoding information and the wire label corresponding to the inputs of all user terminals.

Abstract: A network device determines a priority sequence of a plurality of features, where the priority sequence of the plurality of features is used for random access resource selection. The network device sends first indication information indicating the priority sequence of the plurality of features to a terminal device.

Abstract: A method and an apparatus for privacy protection biometric authentication and an electronic device. The method comprises the following steps: constructing a corresponding a biological data template according to a biological information data set input by a user when registering; generating a pair of public key and private key by asymmetric cryptography technology; generating encrypted biological data by a secret sharing solution and OKVS technology according to the biological data template and the private key; sending the public key and the encrypted biological data to a server; recovering the private key by OKVS technology according to the biological data input by the user during authentication and the encrypted biological data; constructing a signature according to the recovered private key and the corresponding public key; sending the signature to the server, so that the server verifies the user according to the public key and the signature.

Abstract: A multi-party privacy computing method and device based on semi-trusted hardware, wherein the method applied to semi-trusted hardware comprises the following steps: acquiring random number masks and random seeds of all user terminals; generating a garbled circuit seed according to the random seeds; generating a garbled circuit according to a predetermined circuit description and the garbled circuit seed, wherein the garbled circuit comprises garbled tables, wire labels and decoding information; sending the wire labels corresponding to the inputs of all user terminals to a user terminal corresponding to the semi-trusted hardware by using an oblivious transfer protocol; and sending the garbled table and the decoding information to the user terminal corresponding to the semi-trusted hardware, so that the user terminal can compute an output value according to the garbled tables, the decoding information and the wire label corresponding to the inputs of all user terminals.

Abstract: A method and a device for remote acquisition of correlated pseudo-random numbers based on semi-trusted hardware. When applied to semi-trusted hardware, the method comprises: acquiring a random seed of a sender and a selected number of a receiver; generating a plurality of first correlated pseudo-random numbers and first commitment seeds according to the random seed and a predetermined category of the correlated pseudo-random number; generating a first commitment value and a first open value by a commitment mechanism according to the first correlated pseudo-random numbers and the first commitment seeds; generating a Merkle proof according to the first commitment value and the selected number; sending the first correlated pseudo-random numbers, the first commitment value, the first open value and the Merkle proof corresponding to the selected number to the receiver.

Abstract: A method and a device for remote acquisition of correlated pseudo-random numbers based on semi-trusted hardware. When applied to semi-trusted hardware, the method comprises: acquiring a random seed of a sender and a selected number of a receiver; generating a plurality of first correlated pseudo-random numbers and first commitment seeds according to the random seed and a predetermined category of the correlated pseudo-random number; generating a first commitment value and a first open value by a commitment mechanism according to the first correlated pseudo-random numbers and the first commitment seeds; generating a Merkle proof according to the first commitment value and the selected number; sending the first correlated pseudo-random numbers, the first commitment value, the first open value and the Merkle proof corresponding to the selected number to the receiver.

Abstract: This invention discloses a method for discovering vulnerabilities of operating system access control based on model checking. In this method, security attribute and security specifications of operating system access control module are analyzed to construct the access control model. To discover vulnerabilities in the model, security analysis is performed for access control functionality with theorem proving techniques, and consistency of abstract machine specification and correctness and completeness of the components are verified with model checking tools. This method provides theoretical and technical support for studies in the field of operating system security.

Abstract: An efficient, secure and low-communication vertical federated learning method, includes: all participants select part of features of a held data feature set and a small number of samples of the selected features; the participants add noise satisfying differential privacy to part of samples of the selected features, and then send them to other participants together with data indexes of the selected samples; all participants take the received feature data as a label, take each missing feature as a learning task, and train each model with the feature data originally held in the same data index, respectively; all participants predict the data of the other samples with the trained model to complete the missing feature; the participants jointly train a model through horizontal federated learning. The present disclosure can protect data privacy and provide quantitative support for data privacy protection while efficiently training the model with horizontal federated learning.

Abstract: Disclosed is a database encryption method supporting composable SQL query, which mainly comprises the following steps: (1) a user encrypting and preprocessing data based on the encryption scheme provided by the present disclosure and uploading an encryption result and preprocessed data to a service provider; (2) setting and uploading a SQL query instructions: the user uploads the query instruction to the service provider according to actual needs, and uploads auxiliary parameters for the query instruction at the same time; (3) data query: the service provider performs SQL query according to the query instruction and auxiliary parameters received from the user, saves a calculation result, updates the data and returns a query result to the user.

Abstract: Disclosed is a database encryption method supporting composable SQL query, which mainly comprises the following steps: (1) a user encrypting and preprocessing data based on the encryption scheme provided by the present disclosure and uploading an encryption result and preprocessed data to a service provider; (2) setting and uploading a SQL query instructions: the user uploads the query instruction to the service provider according to actual needs, and uploads auxiliary parameters for the query instruction at the same time; (3) data query: the service provider performs SQL query according to the query instruction and auxiliary parameters received from the user, saves a calculation result, updates the data and returns a query result to the user.

Abstract: The disclosure provides a multimodal speech recognition method and system, and a computer-readable storage medium. The method includes calculating a first logarithmic mel-frequency spectral coefficient and a second logarithmic mel-frequency spectral coefficient when a target millimeter-wave signal and a target audio signal both contain speech information corresponding to a target user; inputting the first and the second logarithmic mel-frequency spectral coefficient into a fusion network to determine a target fusion feature, where the fusion network includes at least a calibration module and a mapping module, the calibration module is configured to perform mutual feature calibration on the target audio/millimeter-wave signals, and the mapping module is configured to fuse a calibrated millimeter-wave feature and a calibrated audio feature; and inputting the target fusion feature into a semantic feature network to determine a speech recognition result corresponding to the target user.

Abstract: Disclosed is a method and an apparatus a zero-knowledge proof and an electronic device. That method comprise the following steps: selecting a data processing relationship, and processing private data and public data to obtain a calculation result; respectively committing the private data and the calculation result according to a commitment parameter to obtain a first commitment value and a second commitment value, wherein the commitment parameter is generated by a trusted third party; generating a non-interactive zero-knowledge proof according to the data processing relationship; wherein the commitment parameter, the first commitment value and the second commitment value are used by a verifier to verify the non-interactive zero-knowledge proof. The present disclosure solves the technical problem that bilinear pairing cannot be used in the scenario where bilinear pairing cannot be used in related technologies.

Abstract: A method and an apparatus for acquiring semantic information, an electronic device and a storage medium are provided. The method includes: collecting an echo signal of vibrations of a throat; performing a Fourier transform on a waveform of each period of the echo signal to obtain a spectrogram of each period, wherein the spectrograms of M periods form a spectrogram set, the spectrogram set includes M spectrograms, and the spectrograms are arranged in sequence from first to last according to a return time sequence of the corresponding echo signal; extracting a characteristic waveform of the vibrations of the throat from the spectrogram set; segmenting the characteristic waveform to obtain characteristic segments containing the semantic information; and inputting the characteristic segments into a semantic acquisition model to acquire the semantic information.