112 results about "Hidden data" patented technology

The invention discloses a government affair data sharing system based on a data security law risk control mode, and relates to the technical field of data management. According to the method, full-process closed-loop management from data classification and grading, differential desensitization, law and regulation compliance review, access authority precise control to behavior trajectory real-time analysis and risk trend prediction is realized, and the risk trend prediction is realized by introducing key technologies such as a context sensitive desensitization algorithm, legal knowledge graph reasoning, behavior portraits, semantic trajectory similarity scoring and risk rise rate monitoring. The method effectively improves the recognition and response capability of the hidden data re-recognition risk, and achieves the safe, controllable, compliant and ordered intelligent risk control management of government affair data in the sharing process.

The invention relates to the technical field of privacy protection, and discloses a privacy data anonymization protection method, which comprises the following steps: carrying out data desensitization processing on original privacy data to obtain desensitized privacy data, carrying out differential privacy noise addition processing on the desensitized privacy data to obtain noise-added privacy data, and carrying out differential privacy noise addition processing on the noise-added privacy data to obtain the privacy data. Adding dynamic noise to the desensitized privacy data by adopting a Laplace mechanism to obtain privacy data with a differential privacy protection characteristic; carrying out confusion on the privacy data attributes after noise addition to obtain confused privacy data; and performing data fuzzy processing on the confused privacy data obtained by querying the query statement, limiting the accuracy of the query result, performing pseudo data generation on the privacy data of which the privacy data items of the query result are less than the specified threshold, and returning the query result and the generated pseudo data as the query result together, thereby avoiding the leakage of the differential privacy data.

The invention provides a model sensitive data detection method which comprises the following steps: loading a model file of a to-be-detected model, determining a frame type of the model file, obtaining model graph structure data corresponding to the model file, and obtaining a model parameter set corresponding to the model file from the model graph structure data; performing sensitive data detection on the model parameters in the model parameter set to obtain a first detection result; when the first detection result represents that the model parameter set does not contain sensitive data, abnormal hidden data detection is carried out on a weight parameter and an offset parameter corresponding to the to-be-detected model in the model parameter set, and a second detection result is obtained; and when the second detection result represents that the model parameter set does not contain abnormal hidden data, performing safe operation detection on the to-be-detected model in the isolation environment to obtain an operation detection result, so as to realize multi-level sensitive data detection, ensure the comprehensiveness and depth of detection, and improve the detection efficiency and detection precision of sensitive data detection.

The invention relates to the field of intelligent fault diagnosis, and particularly discloses an intelligent fault diagnosis method for a buried pipeline cathode protection system, which comprises the following steps of: capturing a data mode hidden in multiple dimensions by fusing information (time characteristics) of test pile parameters changing along with time and position topology and spatial correlation (spatial correlation) among test piles; therefore, the identification capability of the difference between similar representation fault types is effectively improved. The space-time collaborative analysis mode provides a solid foundation for realizing intelligent fault diagnosis with high confidence, high precision and high robustness, and is an important technical path for promoting intelligent operation and maintenance management of the buried pipeline cathode protection system.

First data is received which encapsulates second data in a hidden compartment. Thereafter, a password is received by a password encoder which uses such password to generate a key. The first data and the key are combined to generate the second data (i.e., the hidden data). The second data is then provided to a consuming application or process. Related apparatus, systems, techniques and articles are also described.

The subject technology provides techniques for enabling hidden database objects, which in an example are utilized for testing and verifying new database objects against existing workloads. Hidden database objects are a mechanism for bridging that gap by running user workloads on user data in advance of exposing the feature to users. This mechanism allows placing a database object as a hidden object nested beneath a user's visible object (e.g., table, column, view, and the like). Hidden database objects can be used to verify the functionality, parity, performance, and correctness of new unreleased features.

For semantic data leak prevention, one or more semantic interpretations of an input text are obtained with a generative pre-trained transformer, GPT, configured for interpreting the input text with reference to a target context, and it is determined whether the input text comprises a hidden data leakage by checking the semantic interpretations of the input text with a data leak prevention, DLP, system configured for detecting a data leakage based on a collection of words and phrases of interest. As a result, enabled is a prevention of hidden data leaks when a sensitive information is hidden within a text, for example, by using advanced language techniques.

The invention relates to an image steganography method. The method comprises the following steps: carrying out content analysis on an original image serving as a carrier; generating a self-adaptive embedding strategy according to an analysis result, and encoding the embedding strategy into a compact binary format; embedding to-be-embedded data into different areas and channels of the original image in a layered manner according to an embedding strategy to obtain an embedded image; the embedded data is extracted from the embedded image by decoding the embedding policy and mapping reconstruction. According to the method, a region self-adaptive embedding strategy is formulated, the embedding capacity is maximized on the premise of keeping the visual quality of the original image, and the hidden data detection risk is reduced.

A method is described herein. The method generally includes receiving stream parameters that defines an array, wherein the stream parameters include a first null element count and a second null element count. The method generally includes forming a stream of vectors for the multidimensional array responsive to the stream parameters. The stream of vectors generally includes a vector of null elements at a beginning of the stream of vectors based on the first null element count. The stream of vectors generally includes a null element at a beginning of each vector of the stream of vectors based on the second null element count. The stream of vectors generally includes a set of data distributed across a subset of the stream of vectors. The method generally includes providing the stream of vectors.

The invention discloses a compiling optimization device and method supporting Page Attention and a medium, and belongs to the field of compiling optimization devices.The device comprises a multi-core AI accelerator, and each calculation core comprises a tensor component, a vector component, a DMA component and an IMM component; the compiling optimization device is optimized through the following modules: (a) a KV Cache management module, which is used for storing page table items corresponding to different KV Cache blocks according to a batch sequence and generating standardized page table items; (b) a DMA control module which supports a linear reading and remapping mode, carries discrete KV Cache blocks from an external memory to an on-chip weight buffer area in a segmented manner according to an index table, and hides data loading delay by adopting a double-buffer technology; and (c) a multi-batch reasoning scheduling module which dynamically allocates computing resources according to the data scale in a code stage. According to the invention, through deep cooperation of a hardware architecture and functional logic, the problems of low KV Cache management efficiency, complex multi-batch dynamic scheduling and insufficient computing resource utilization rate on an ASIC platform are solved.

In one embodiment, a method includes receiving a first request to access one or more resources in the first network layer. The method may include acquiring first identity information of a first user account specified in the first request. The method may include performing multi-factor authentication of the first user account using the first identity information. In response to authenticating the first user account using the first identity information, the method may include acquiring multiple shares of pre-configured first hidden data from a distributed ledger in the first network layer. The method may include determining a first password from the multiple shares of pre-configured first hidden data and, using the first password, authenticating the first user account to access the one or more resources in the first network layer.

The invention relates to a distributed hidden data submission method based on a block chain, and belongs to the technical field of data security. In order to guarantee the security of a data submission process, a session key updating method based on a block chain and Diffie-Hellman key exchange is provided, symmetric cryptography, a hash function and a digital signature technology are used, a special data message construction method is provided, and each communication participant periodically scans the change of the block chain and pulls a new block to the local. According to the invention, the demand of establishing a secure network communication channel by handshake between a receiving party and a transmitting party is eliminated fundamentally, and the adverse effect of DDos network attack is reduced; the integrity and the consistency of the datagram are ensured; the data anti-repudiation, anti-tampering and anti-forgery characteristics are provided; and key distribution and storage with low maintenance cost are realized.

The invention relates to a hidden data center intelligent identification method based on multi-scale time sequence feature fusion. The method comprises the following steps: S1, obtaining time sequence data of a to-be-detected area and preprocessing the time sequence data; s2, based on the preprocessed time sequence tensor, an initial graph structure is established on the layers of an entity and an observation point, an edge weight is calibrated and sparsified through a data-driven adaptive graph learning mechanism, multiple time delay path sets between node pairs are learned, and optimized dynamic adjacency and time delay weights are obtained; s3, constructing a hidden data center intelligent identification model in combination with an ST-GNN model; s4, training the hidden data center intelligent identification model to obtain a trained hidden data center intelligent identification model; s5, acquiring a real-time detection probability and a confidence interval according to the real-time data stream; and S6, selecting an initial alarm threshold value through the cost sensitive curve, carrying out adaptive fine tuning, and obtaining a final alarm list according to the real-time detection probability. The method effectively improves the intelligent recognition efficiency of the hidden data center.

The invention discloses a computer interface safety device capable of preventing computer data from being stolen, which comprises a computer shell, a plurality of mounting grooves are formed in the side wall of the computer shell, an electric telescopic rod is fixedly connected to the inner bottom side wall of each mounting groove, the output end of each electric telescopic rod is fixedly connected with a moving plate, and the moving plate is fixedly connected with the computer shell. The movable plate is slidably connected into the mounting groove, a data interface is fixedly connected to the side wall of the movable plate, four pressure sensors are mounted on the peripheral side walls of the movable plate respectively, and a temperature sensor and a humidity sensor are mounted on the side wall of the data interface. According to the invention, not only is the telescopic hidden data interface designed to prevent the data interface from being exposed outside and being communicated with a computer by an outsider through the interface to steal data, but also the damage risk assessment coefficient FX is set, so that when the data interface has a damage risk, the data interface can be timely and actively retracted to prevent the data interface from being damaged.

The invention discloses a time sequence electroencephalogram data quality detection and restoration method and a time sequence electroencephalogram data quality detection and restoration system, and belongs to the technical field of industrial internet. According to the method, the problems that the electroencephalogram data is lost, the electroencephalogram data quality is poor and the electroencephalogram data storage efficiency is low are solved. According to the method, by calculating the integrity index of the electroencephalogram data, the hidden data value missing condition can be detected, then the data filling operation is guided according to the missing detection result, and the original electroencephalogram data characteristics can be recovered. Effectiveness indexes are established on the basis of effectiveness, change speed and acceleration of values, quantitative evaluation standards can be provided for reasonability of electroencephalogram data values so as to detect whether data points are reasonable and have sudden changes or abnormities or not, a data restoration method is further selected according to detection results, data stability is enhanced, data continuity is improved, and the accuracy of data restoration is improved. The electroencephalogram data quality is improved, and subsequent data analysis is facilitated. The method can be applied to electroencephalogram data quality detection and restoration.

The embodiment of the invention provides a page analysis method and device, electronic equipment, a storage medium and a program product, and the page analysis method comprises the steps that a burying point processing request for a target page is received, and the burying point processing request comprises page data of the target page; inputting the page data into a pre-trained page analysis model to obtain buried point processing data of the target page, the buried point processing data including buried point identifiers and operation information corresponding to target elements in the target page, the buried point identifiers being used for representing operation types for the target elements, and the operation information being used for representing operation types for the target elements; the operation information is used for representing operation content for the target element; and based on the operation type and the operation content, performing burying point configuration on the page data. According to the method, the page analysis request is automatically processed, the pre-trained model is utilized to analyze the page data and generate the burying point data, and the corresponding burying point identifier and information are added to each element in the page, so that the workload of manual configuration is reduced, and the burying point deployment speed is increased.

A server determines an array [[addr]] indicating a storage destination of each piece of data, generates an array of concealed values, and connects the generated array to the array [[addr]] to determine an array [[addr′]]. The server generates a sort permutation [[σ1]] for the array, applies the sort permutation [[σ1]] to the array [[addr′]], and converts the array [[addr′]] into an array with a sequence composed of first Z elements set to [[i]] followed by αi elements set to [[B]]. The server generates a sort permutation [[σ2]] for the converted array [[addr′]], generates dummy data, imparts the generated dummy data to the concealed data sequence, applies the sort permutations [[σ1]] and [[σ2]] to the data array imparted with the dummy data, and generates, as a secret hash table, a data sequence obtained by deleting the last N pieces of data from the sorted data array.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products for concealing a subscription identifier. The subscription identifier may be padded with a random number of characters. The padding may use characters not usable for the subscription identifier. The padded subscription identifier may be encrypted and output, possibly with an indication of the padding method used and, in an embodiment, an indication of the number of padding characters. The subscription identifier may be a user identifier, e.g., in a 5G network in which a wireless transmit / receive unit can conceal its identifier.

The present invention discloses a video information hiding method, system, device, and medium based on inter-block pairing. The method comprises: obtaining encoded H.264 video data and obtaining coefficients of all 4×4 luminance blocks in the H.264 video data; sorting all 4×4 luminance blocks according to the absolute values ​​of their DC coefficients; pairing the AC coefficients from the second to the last digit in adjacent luminance blocks to obtain coefficient pairs; shifting the luminance blocks accordingly based on the coefficient pairs, the data to be embedded, and a two-dimensional histogram transfer map; and placing the embedded 4×4 luminance blocks into the encoded H.264 video data in their original order. The present invention uses inter-block pairing to modify the luminance blocks in the video data according to the embedded data, thereby embedding hidden data and effectively reducing the impact on video quality and the increase in video file size. The present invention can be widely applied in the field of multimedia information security technology.

This application provides an image processing method and an electronic device, relating to the field of terminal technology. The technical solution provided by this application can effectively avoid the problem of image detail loss and reduced image quality caused by encoding processing of transmitted images during image transmission. The method can be applied to a first device, and includes: in response to a trigger operation to send an original image, acquiring a first image, the first image including hidden data, the hidden data being used to identify the storage path information of the original image in a first cloud server; and sending the first image.

The present invention provides a method for hiding and extracting secure text compatible with multiple types of image carriers. The hiding method includes: obtaining a digital image to get its corresponding pixel value matrix I; performing image block division on I; determining the encoding type and embedding mode of the text to be embedded, and generating an encoding type identification field and an embedding mode identification field; calculating the embedding capacity under this encoding type and this embedding mode; encoding the text to be embedded, calculating the length of the encoded text and generating a text length identification field; generating hidden data; allocating the hidden data to the corresponding image blocks; for the image blocks that need to embed the hidden data, modifying the image blocks according to the original pixel mean of the image blocks and the hidden data to be embedded therein to obtain new image blocks; repeating the above until all the image blocks that need to embed the hidden data are modified, and at this time storing all the image blocks in the original image format to obtain an image containing hidden data.

Provided is a data analysis system, a data analysis device, a data analysis method, and a computer program. The data analysis system includes: a first data conversion device configured to conceal first data on a first product manufactured in a first manufacturing system and output the first data as first concealed data; and a data analysis device configured to select an element of the first concealed data that affects second data on a second product manufactured using the first product by evaluating a degree of influence between the first concealed data and the second data.

The application provides a holographic image anti-counterfeiting pattern laser processing method, a storage medium and a product, a polarization angle sequence is determined through spectrum processing, a neural network is used to optimize microstructure arrangement, an encoding matrix is generated, hidden data is integrated to improve information dimension, then simulation calculation and iterative updating are used to enhance the anti-counterfeiting effect of the encoding matrix, resistance characteristics are extracted and robustness is verified, finally, material surface writing is guided to form a holographic image anti-counterfeiting pattern, and finally, a multi-dimensional verification protocol is combined to ensure the stability of the polarization response in different environments. The application significantly improves the cracking resistance and environmental adaptability of the anti-counterfeiting pattern through the deep combination of the polarization angle and the microstructure optimization.

The present disclosure relates to hiding data trends in a machine-to-machine (M2M) system. A method for operating a first device in a machine-to-machine (M2M) system may include: performing a registration procedure for a second device; receiving real data generated by the second device; obtaining fake data of an identical type as the real data; and storing the real data and the fake data in a same resource.

The application belongs to the field of medical prediction, and discloses an information mining method for heterogeneous time series data, comprising: acquiring electronic medical record data and constructing a hypergraph, analyzing and calculating the hypergraph to obtain embedding representation data, weighting the embedding representation data based on an attention mechanism to obtain embedding sequence data, constructing a sequence learning model and performing hidden state access to obtain hidden representation data and weight data thereof, weighting the embedding sequence data to obtain embedding sequence hidden data; training the sequence learning model through time training parameter data, weighting the embedding sequence hidden data through the trained sequence learning model to obtain time dimension hidden data, constructing a full connection network to analyze the time dimension hidden data to obtain medical event prediction data. The technical scheme disclosed by the application can learn complex information in the time dimension by using time step information, and can obtain accurate medical event prediction results.

The invention discloses a federal learning method for hiding data source information based on group signature, smart contract and distributed file system, and relates to the technical field of computer cryptography. According to the method, the smart contract is utilized to manage each group member, each group member completes model training by utilizing local data to obtain model parameters, the model parameters are encrypted by utilizing a group signature function and then uploaded to the DFS to obtain a DFS address, and then encryption and group signature are performed on the encrypted key and the DFS address through the smart contract, so that the group signature of the encrypted key and the DFS address is realized. And the central server obtains a DFS address and a secret key through decryption, downloads encrypted model parameters from the DFS, obtains model parameters uploaded by each group member through decryption by using the secret key, and obtains an improved global model after aggregation updating by using the model parameters. The privacy of the data provider is effectively protected, so that the data source information of the two parties in the federal learning process is protected.

The invention discloses a tamper-proof electronic scale monitoring method and system based on an electronic lead seal and a gravity sensor, and relates to the technical field of equipment tamper-proof, and the method comprises the steps: basic monitoring: an electronic lead seal module detects the opening and closing state of an electronic scale housing in real time and outputs a state signal; the gravity sensor module acquires weighing data and space state parameters of the electronic scale in real time and outputs acquisition signals, and the operation log module synchronously records weighing operation information; through cooperative operation of electronic lead sealing monitoring, gravity sensing detection and time sequence data analysis, the electronic lead sealing module can be used for monitoring the opening and closing state of the electronic scale shell, and weighing data and space state parameters can be collected through the gravity sensor module; and meanwhile, abnormity identification is carried out by combining a weighing data fluctuation model and a weighing interval model constructed by a time sequence analysis module, so that physical tampering and hidden data tampering behaviors of the electronic scale can be identified at the same time.

The invention discloses a deniable storage method and system with multi-snapshot security. The method comprises the following steps: generating system public parameters according to security parameters; inputting a password of a secure deletion system to initialize the first master key; inputting a password of the hidden storage system to initialize a second master key; the disk state of the PPRF is stored through a tree structure, and a first key tree is generated; encrypting and storing encryption keys of all files to generate a first file key table; constructing a storage space of the deniable storage system; writing / updating, reading and deleting the public file; and writing, updating and deleting the hidden data. According to the method, normal file change in the snapshot period has multi-snapshot security; the hidden space and the public space can be freely switched, and compared with an existing deniable storage system with multi-snapshot safety, the capacity can be increased by 50 times at most; and the hidden space is completely encrypted by using the master key in the TPM module, so that a powerful guarantee is provided for the security of the hidden space.

The embodiments of the present invention disclose a method, device, equipment and medium for reporting buried point data, the method comprising: when generating a service request, reading buried point data from a buried point data file, generating data to be transmitted according to the service request and the buried point data; determining the service interface corresponding to the service request, and calling the service interface to send the data to be transmitted to the server. The method provided by the embodiments of the present invention reports buried point data by calling the service interface when sending a service request, thereby realizing the reporting of buried point data without going through a special buried point reporting interface, speeding up the response speed, and reducing the amount of data reported for a single buried point data report by dispersing the buried point data to different service interfaces for uploading, saving the network bandwidth occupied by a single buried point data report, speeding up the reception speed of the service request data returned by the server, and improving the performance of the client.

The present invention relates to a method for encoding accessible and hidden data in the form of a machine-readable visual code. The visual code comprises a number X of graphic units UG(1), …UG(X) respectively positioned at positions P(1), …P(X) of the visual code, each graphic unit UG(i) having a graphic value VG(i). The method comprises: obtaining the values ​​v(1), …v(X) obtained by encoding the accessible data using a first type of encoding; determining ⌊X.λ⌋ positions P(a1), P(a2)….P(a⌊X.λ⌋) from among the positions P(1), …P(X); and encoding the hidden data into a number ⌊X.λ⌋ of values ​​v'(1), …v'(⌊X.λ⌋) obtained using a second type of encoding. encoding; Obtaining the visual code in which: VG(i) is representative of v(i) if P(i) is not one of the positions P(a1), P(a2)….P(a⌊ X.λ ⌋), VG(i) is representative of v'(j) if P(i) is the position P(aj). Figure for the abbreviation: Fig. 5