Abstract: A secure and trusted three-party device fingerprint authentication method is disclosed. The method includes the following steps: S1. authentication preparation stage: dividing subjects involved in fingerprint authentication into a device party U, a service party P and a storage party V, uploading and verifying an execution program of a trusted execution environment TEE; S2. authentication initialization stage: establishing the trusted execution environment TEE by the service party P, and establishing a security channel between the trusted execution environment TEE, the device party U and the storage party V; and S3. device fingerprint authentication stage: uploading a fingerprint and a fingerprint library to the trusted execution environment TEE through the security channel by the device party U and the storage party V, respectively, after completing a device fingerprint authentication, obtaining an authentication result through the security channel.

Abstract: A secure and trusted three-party device fingerprint authentication method is disclosed. The method includes the following steps: S1. authentication preparation stage: dividing subjects involved in fingerprint authentication into a device party U, a service party P and a storage party V, uploading and verifying an execution program of a trusted execution environment TEE; S2. authentication initialization stage: establishing the trusted execution environment TEE by the service party P, and establishing a security channel between the trusted execution environment TEE, the device party U and the storage party V; and S3. device fingerprint authentication stage: uploading a fingerprint and a fingerprint library to the trusted execution environment TEE through the security channel by the device party U and the storage party V, respectively, after completing a device fingerprint authentication, obtaining an authentication result through the security channel.

Abstract: A multi-terminal collaborative dynamic security analysis method and system for distributed power supply are provided. The method includes building a physical-cyber network topology model for a distributed power supply control system; updating cyber domain security risk probabilities and physical domain security risk probabilities of other units, to achieve a dynamic physical-cyber security risk network topology map; searching a target attack path according to different attack entrances and attack intensities; and taking the target attack path as guidance, to implement a damage degree assessment.

Abstract: A camera with a privacy protection function and a camera privacy protection method therefor are provided, which relates to the field of image privacy protection. The camera includes an image acquisition module, a parameter storage module, an access control module, and an image post-processing module. An objective of the privacy protection method of the camera is to enable an image shot by the camera to naturally have a privacy protection capability to resist sniffing of a malicious third party to personal privacy, which includes, but is not limited to, face recognition. A system deeply participates in a generation process of an image from a plurality of levels, which can affect various procedures including image signal processing, image color adjustment, and an image encoding process, and provide a platform for the development and application of underlying privacy protection algorithms.

Abstract: A method for detecting diaper wetness based on a ratio signal technology comprises: sending a frequency-modulated continuous wave signal to a diaper through a radar device to obtain a transmission signal ST(t) and a return signal SR(t); detecting a static environment factor and a dynamic environment factor, and obtaining continuous radar snapshots; eliminating interference of environmental factors by using a filtering template based on the continuous radar snapshots and object respiration; obtaining an outline of the diaper by using wavelet synchronous compression transformation, and dividing into a training sample set and a testing sample set; and inputting the training sample set and the test sample set into a heuristic mobility network for training until a loss function is converged, obtaining the trained heuristic mobility network, and obtaining diaper wetness of the test sample set.

Abstract: The present invention relates to the technical field of central processing units (CPUs), and in particular to a fault-tolerant system with multi-core CPUs capable of being dynamically configured. The multi-core CPUs are three reconfigurable CPUs, the fault-tolerant system with multi-core CPUs is statically configured to be in a normal fault-tolerant mode, a reliable fault-tolerant mode or a performance mode by means of configuration of the three CPUs and then is switched between the normal fault-tolerant mode, the reliable fault-tolerant mode and the performance mode according to a mode switching command of a mode switching register, and finally, the three CPUs are correspondingly configured according to the mode to be switched.

Abstract: A cross-chain transaction method based on hash locking and a sidechain technology is provided. The cross-chain transaction method comprises the following steps: establishing a hash-locking-based atomic exchange data transmission mechanism for a first terminal and a second terminal; establishing a cross-chain data transfer mechanism based on an SPV pegging mode; and realizing, by the first terminal and the second terminal, a hash-locking-based atomic exchange data transmission under a supervision state of the SPV pegging mode. The cross-chain transaction method, by utilizing the sidechain technology, solves the defect of the hash locking technology that only asset exchange can be realized but asset transfer cannot be realized, and thus the cross-chain asset transfer can be realized by utilizing the hash locking technology without additionally adding a sidechain or a relay chain.

Abstract: A covert channel construction method in a blockchain network includes: sharing, by a first terminal and a second terminal, a secret key and transaction information, and generating a blockchain network address by using the secret key and a standard public key address generation algorithm, wherein the transaction information comprises a permutation mapping table and an information capacity of a single transaction; sending, by the first terminal, information by using an information hiding method, and performing simultaneously, by the first terminal and the second terminal, transaction recording; and monitoring, by the first terminal and the second terminal, whether an account transaction of the blockchain network address exists in a blockchain, if yes, extracting, by the second terminal, the information by using an information extraction method, and after extracting the information, replying to the information by using the information hiding method, thereby enabling communication parties to safely transmit infor

Abstract: A covert channel construction method in a blockchain network includes: sharing, by a first terminal and a second terminal, a secret key and transaction information, and generating a blockchain network address by using the secret key and a standard public key address generation algorithm, wherein the transaction information comprises a permutation mapping table and an information capacity of a single transaction; sending, by the first terminal, information by using an information hiding method, and performing simultaneously, by the first terminal and the second terminal, transaction recording; and monitoring, by the first terminal and the second terminal, whether an account transaction of the blockchain network address exists in a blockchain, if yes, extracting, by the second terminal, the information by using an information extraction method, and after extracting the information, replying to the information by using the information hiding method, thereby enabling communication parties to safely transmit infor

Abstract: The present disclosure discloses a machine learning-based method for defending a voice assistant from being controlled by an inaudible command, including following steps: 1) collecting data of positive and negative samples, 2) performing data segmentation on data of the positive and negative samples; 3) selecting and normalizing sample features; 4) selecting a classifier to be trained and generate a detection model for a malicious voice command; 5) detecting a voice command to be detected by the detection model. The present disclosure selects an original feature selection method, and for smart devices of different types, it is necessary to obtain normal voice commands and malicious voice commands by means of a smart device of this type, and use them as the positive and negative samples to train a specific classifier for the device. Such a customized approach can well solve a problem that detection and defense between devices cannot work.

Abstract: The disclosure discloses a method and a system for generating image adversarial examples based on an acoustic wave. The method includes: acquiring an image containing a target object or a target scene; generating simulated image examples for the acquired image, wherein the simulated image examples have adversarial effects on a deep learning algorithm in a target machine vision system; optimizing the generated simulated image examples to obtain an optimal adversarial example and corresponding adversarial parameters; and injecting the adversarial parameters into an inertial sensor of the target machine vision system in a manner of an acoustic wave, such that the adversarial parameters are used as sensor readings that will cause an image stabilization module in the target machine vision system to operate to generate particular blurry patterns in a generated real-world image so as to generate an image adversarial example in a physical world.

Abstract: The present disclosure discloses a machine learning-based method for defending a voice assistant from being controlled by an inaudible command, including following steps: 1) collecting data of positive and negative samples, 2) performing data segmentation on data of the positive and negative samples; 3) selecting and normalizing sample features; 4) selecting a classifier to be trained and generate a detection model for a malicious voice command; 5) detecting a voice command to be detected by the detection model. The present disclosure selects an original feature selection method, and for smart devices of different types, it is necessary to obtain normal voice commands and malicious voice commands by means of a smart device of this type, and use them as the positive and negative samples to train a specific classifier for the device. Such a customized approach can well solve a problem that detection and defense between devices cannot work.

Abstract: Systems and methods for calibrating a web inspection system.

Abstract: Systems and methods for calibrating a web inspection system.

Abstract: Systems and methods for calibrating a web inspection system.

Abstract: Techniques are described for estimating the propagation velocity through a surface acoustic wave sensor. In particular, techniques which measure and exploit a proper segment of phase frequency response of the surface acoustic wave sensor are described for use as a basis of bacterial detection by the sensor. As described, use of velocity estimation based on a proper segment of phase frequency response has advantages over conventional techniques that use phase shift as the basis for detection.

Abstract: Systems and methods for calibrating a web inspection system.

Abstract: Techniques are described for estimating the propagation velocity through a surface acoustic wave sensor. In particular, techniques which measure and exploit a proper segment of phase frequency response of the surface acoustic wave sensor are described for use as a basis of bacterial detection by the sensor. As described, use of velocity estimation based on a proper segment of phase frequency response has advantages over conventional techniques that use phase shift as the basis for detection.

Abstract: An imaging device for sequentially imaging a portion of a continuously moving web to provide a digital data stream which is then analyzed by a single computer without the used of dedicated signal processing hardware. Techniques for operating on the data stream from an imaging device are disclosed, particularly including operations based on blob information stored in terms of starting position and segment run lengths in a crossweb direction. These allow definitions of blobs to be accumulated in a line-by-line fashion, and allow classes of defects commonly found in continuous web manufacturing to be identified with far less computing power than was previously required. In particular, in the challenging application of inspecting flexible circuits, data rates in excess of 10 mega-pixels/second are achieved and successfully processed.

Abstract: An imaging device for sequentially imaging a portion of a continuously moving web to provide a digital data stream which is then analyzed by a single computer without the used of dedicated signal processing hardware. Techniques for operating on the data stream from an imaging device are disclosed, particularly including operations based on blob information stored in terms of starting position and segment run lengths in a crossweb direction. These allow definitions of blobs to be accumulated in a line-by-line fashion, and allow classes of defects commonly found in continuous web manufacturing to be identified with far less computing power than was previously required. In particular, in the challenging application of inspecting flexible circuits, data rates in excess of 10 mega-pixels/second are achieved and successfully processed.