91 results about "Channel analysis" patented technology

The invention discloses an intelligent interaction system based on a large language model and a knowledge graph, and relates to the technical field of artificial intelligence and intelligent interaction. According to the system, data processed by a data acquisition and preprocessing module is stored in a local knowledge warehouse in a three-layer nested structure; the multi-modal semantic understanding module constructs a knowledge system in which a triple knowledge graph and a vector database are complementary by optimizing a BERT model and performing dual-channel analysis; the intelligent interaction module realizes natural language interaction and business task automatic triggering based on an RAG technology and a dialogue memory mechanism; the information change identification and analysis module generates a personnel change risk report and performs early warning; and the summary report automatic generation module outputs a structured report. According to the method, the problems of data splitting, complex interaction and slow response in traditional enterprise management are solved, the functions of system intelligent question answering, personnel change risk analysis, structured report automatic generation and the like are realized, and the management efficiency and the information consistency are improved.

The invention relates to the technical field of video analysis, in particular to an AI-based video analysis and management system, which comprises a channel evaluation module, a track extraction module, a cross-source fusion module, a content screening module and a scheduling generation module. In the method, key frame optimization is realized by combining frame activity index evaluation in an object identification process, track continuity breakpoint repair is realized based on a displacement sequence and a direction change trend in a track extraction process, and track matching fusion is realized through region and direction cross mapping in cross-channel analysis. Effective channels are identified based on track keeping features in content screening, and a structured identification directory is constructed in combination with label mapping in a scheduling process, so that target identification and track splicing among different channels have a full-process dynamic completion and consistency verification mechanism, the cross-video-source target identification precision and stability can be effectively improved, and the target identification efficiency is improved. And thus, more efficient content screening and structured recognition can be realized in a multi-source video environment.

The invention relates to the technical field of building information model optimization, in particular to a large-volume BIM model optimization system based on intelligent loading, which comprises a model analysis unit, a function identification unit, a simplified execution unit and a model recombination unit, and is characterized in that the model analysis unit reads an IFC file and separates component data; the function identification unit outputs a decoration component (first class) set, a non-bearing structure (second class) set and a bearing component (third class) set through geometric and semantic dual-channel analysis, the simplified execution unit performs edge folding on the first class, performs vertex clustering on the second class and skips simplification on the third class, and the model recombination unit binds metadata and constructs a dynamic octree index. The problems that a traditional simplification strategy is single and core information is lost are solved, the model loading efficiency and application precision are improved, and the method is suitable for complex building scenes.

The invention relates to the technical field of remote monitoring, in particular to a multi-source data acquisition monitoring robot based on the Internet of Things, which comprises a morpheme trigger recognition module, a task compression judgment module, a resource tilt execution module, a difference channel analysis module and a path state injection module. According to the method, dynamic switching of voice interaction states is realized through morpheme response distance and silence zone recognition, priority allocation of task resources is completed in combination with a task delay labeling mechanism, an auxiliary path is released through linkage of node states and communication port fields, resource scheduling flexibility is improved, fluctuation trend and structural offset are fused in abnormal recognition, and abnormal recognition accuracy is improved. And in path control, label field double write-in and state register linkage is adopted, a closed-loop mapping relation between a task path and a control state is constructed, and the accuracy and synchronization consistency of path regulation and control are improved.

The application discloses a computing system configured to measure a step response of a channel in an electronic device, determine a feedback voltage added to the channel by a decision feedback equalizer in response to detecting inter-symbol interference in a received symbol, and predict signal integrity of the channel based at least in part on the step response of the channel and the feedback voltage. The computing system may utilize the predicted signal integrity to determine a probability that a feedback voltage added to the channel by the decision feedback equalizer is wrong, and determine a signal integrity of the channel based at least in part on the step response of the channel, the feedback voltage, and a probability that the feedback voltage added to the channel by the decision feedback equalizer is wrong.

A computerized method comprising: tracking user behavior data of users each using a respective mobile device within a channel; detecting a demand surge in the channel based on channel analysis data for the channel, wherein the channel analysis data for the channel are based channel events for the channel; and generating one or more first incentives for one or more first users of the users based on the demand surge and incentive metrics, wherein the one or more first incentives are configured to change user behavior of the one or more first users. Other embodiments are disclosed herein.

The invention discloses an optical signal channel structure analysis system based on a new generation of mobile communication networking, which belongs to the field of optical communication data, and comprises the following steps: a data acquisition module receives an OTN (Optical Transport Network) signal and an SDH (Synchronous Digital Hierarchy) signal; the OTN channel analysis module carries out channel structure analysis on the accessed OTN signal and carries out OTN demultiplexing and de-encapsulation mapping processing to obtain OTN channel structure information; the SDH channel analysis module is used for carrying out channel structure analysis on the accessed SDH signal and normalizing the SDH signal into SDH channel structure information; the channel structure issuing configuration module carries out regular conversion on the OTN channel structure information and the SDH channel structure information obtained through analysis, and issues the information to the ZYNQ control chip; the channel structure reporting module reports and pushes the channel structure information of the whole port to the rear-end signal processing module; and the automatic polling module performs an automatic real-time polling mechanism on the accessed OTN signal and SDH signal. The system provided by the invention can effectively realize the characteristic of integrated input and output of channelized equipment.

The invention relates to a high-security hidden communication system, and belongs to the technical field of information security. According to the system, the mark feature and the structural feature of encrypted data are eliminated through a strong encryption technology, the key feature of the encrypted data is eliminated, the key security is ensured, the ciphertext security is improved, and the risk problem brought by side channel analysis to the data encryption security is solved; a double-layer covert channel is realized through a multimedia steganography technology and a flow simulation technology, the concealment of communication behaviors is greatly enhanced, and the problem of insufficient concealment of a single-layer covert channel is solved; the hidden communication technology with both concealment and anonymity is realized by combining the hidden channel with the anonymous network, and the problems that the anonymous network has obvious traffic characteristics and network boundary nodes are easy to expose are solved.

The application relates to the technical field of wireless communication and vehicle-mounted multimedia interaction, in particular to a vehicle-mounted video backhaul and multi-mode audio interaction system, which comprises the following modules: a service shunting module, which is used for determining the priority label of audio stream data according to an identification result; a channel analysis module, which is used for evaluating the channel capacity and interference level of current time-frequency resources; a power domain allocation module, which is used for dynamically calculating a power allocation coefficient and dividing the total transmission power of a vehicle-mounted communication terminal into a first power level and a second power level; a superposition coding module, which is used for generating a multi-layer superposition signal; and a transmission control module, which is used for directly transmitting the multi-layer superposition signal to a base station side through a radio frequency unit in a scheduling-free transmission mode without sending a scheduling request signaling, so that the competition and conflict of high-definition video backhaul and key voice interaction for limited time-frequency resources in vehicle-mounted wireless communication are effectively solved, and efficient concurrency of heterogeneous services is realized.

The present application relates to a kind of password algorithm artificial intelligence side channel analysis method based on dimension reduction and clustering, belong to information security cryptography field.First, the energy trace obtained is analyzed, to determine the area of the energy trace in which the execution of the decryption process is related to secret information operation.Analyze the energy trace of the key operation part, use the method based on sliding window gradient value to divide each operation, obtain energy trace segment.Combined with the implementation of cryptographic algorithm, the energy trace segment is analyzed, and the operation type is identified.Use principal component analysis on energy trace segment for dimension reduction, take the component corresponding to the expected dimension as the principal component of each operation.Combined with the characteristics of energy trace segment, the cluster number obtained by clustering is estimated.Use clustering algorithm to cluster the energy trace segment after dimension reduction, analyze the clustering result to determine the operation type represented by each cluster, obtain the operation type corresponding to the energy trace segment, finally obtain the secret index sequence, realize the efficient analysis of the side channel of cryptographic algorithm.

The present application relates to pathological analysis technical field, specifically to a kind of pathological section intelligent analysis method and system based on deep learning, including the following steps: based on tissue section image, utilize multi-channel analysis tissue structure and dye distribution, adjust collection parameter and optimize image definition and cell structure performance, combine spatial distribution and gray layering relationship, automatically distinguish mutation area and structure boundary, output demarcation structure positioning mark.The present application is through collection sequence optimization, parameter dynamic adjustment and spatial distribution automatic discrimination, microstructure change, dye distribution and cell arrangement relationship are mapped as structure response index, realizes the efficient linkage of collection parameter and tissue characteristics, supports the synchronous identification of spatial mutation, dye layering and demarcation relationship in complex section, greatly improves the objectivity and coherence of area identification, structure annotation and demarcation positioning, avoids feature omission, enhances the integrity of data processing link and the practical depth of medical image analysis.

The invention provides an automatic control system and method for an AES circuit. The system comprises an upper computer and a lower computer. The upper computer comprises an AES data generation logic module and a serial port communication logic module; the AES data generation logic module generates AES circuit input data; the serial port communication logic module sends the AES circuit input data added with the tag bit to a lower computer; the lower computer comprises an AES circuit, a serial port communication circuit and a data processing circuit; the serial port communication circuit converts input data of the AES circuit into parallel data; the data processing circuit analyzes the input data through the state machine and controls the channel analysis device to collect the power consumption of the lower computer during encryption and decryption; and the AES circuit implements encryption and decryption by using the analyzed data. The AES circuit is automatically called by designing upper / lower computer communication logic, automatic acquisition of the test channel analysis device is realized by controlling a flag bit signal during encryption and decryption, and the time for manual encryption and decryption and manual acquisition is saved.

Systems and methods are disclosed for physical side-channel monitoring of a software program. In one embodiment, a method performed by a server for enabling program- specific side channel analysis (SCA) comprises receiving, from an orchestrator, an instruction to execute a first software program, executing the first software program on at least one processor core of at least one processor at the server, and sending measurement data for the first software program to a SCA monitor. The measurement data for the first software program comprises, for each processor core for each processor on which the first software program is executed at the server, for each time period during which the first software program was executed on the processor core, one or more physical side-channel measurements related to the processor core made during the time period during which the first software program was executed by the processor core.

The invention relates to the technical field of side channel analysis, and particularly provides a side channel analysis method and system based on bit decoupling and a medium, and the method comprises the steps: obtaining power consumption data during encryption, calculating an intermediate value, and carrying out the multi-label decoupling; extracting multi-scale features from the preprocessed energy traces, performing weighted fusion, and outputting global shared features; mapping the global shared features into initial bit features through linear projection, calculating a dependency relationship between the bit features by using an attention mechanism, and generating interactive bit features; the fusion proportion is dynamically adjusted through gating parameters, fusion features are input into a multi-label classifier, the posterior probability of each bit is obtained, and a loss function is adopted for training; and inputting a to-be-measured energy trace into the trained neural network model, outputting a prediction probability, and selecting a target key by calculating the confidence coefficient of the candidate key through traversal. According to the method, the quantity of required energy traces is greatly reduced, and meanwhile, the attack success rate in a low signal-to-noise ratio environment is remarkably improved.

The invention relates to the technical field of integrated circuit chips, and discloses an integrated circuit chip power consumption information side channel analysis method, which comprises the following steps of: acquiring original power consumption data in chip operation, setting an initial format consisting of a timestamp and an amplitude field, and associating the data with the format through an interface protocol; performing initial processing such as noise filtering and amplitude calibration on the original data, extracting characteristic parameters such as peak amplitude, fluctuation frequency and duration, dividing data types according to a characteristic parameter range corresponding to a chip model, and performing classified storage; establishing a standard mode database, and calling a corresponding standard mode according to operating environment information such as working voltage and environment temperature; comparing the preprocessed data with a standard mode, and marking abnormal data points; and finally, counting an abnormal proportion and transmitting the abnormal proportion to a monitoring terminal, rechecking abnormal data points according to a fixed proportion, and outputting an analysis conclusion according to a rechecking result. The method has good practicability and application value.

The invention provides a side channel analysis method based on frequency domain loss auto-encoder data enhancement, which comprises the following steps of: adding a frequency domain loss item to a reconstruction loss part of a vector quantization variational auto-encoder loss function, and synchronously utilizing frequency domain and time domain information to improve the loss function of an auto-encoder; constructing an auto-encoder model based on the improved loss function, and training the improved auto-encoder model by using original data; performing data enhancement by using the trained model to generate a new energy trace; and finally, performing side channel analysis by using the newly generated energy trace. The method can better help the model to learn the periodic structure and frequency characteristics of the energy trace, thereby generating more real energy trace data, expanding the scale of a data set for side channel analysis, improving the generalization ability of a deep learning side channel analysis model, and improving the effect of side channel analysis.

The invention provides a side channel data generation method and system, electronic equipment and a storage medium, according to the side channel data generation method provided by the invention, a multi-view generative adversarial network architecture is introduced into the field of side channel analysis for the first time, and through parallel acquisition and joint modeling of multi-source side channel trajectory data, the multi-view generative adversarial network architecture is introduced into the field of side channel analysis. And constructing a multi-view data set containing multi-dimensional features, and generating simulation data with real leakage features by using a confrontation mechanism of a generator and a discriminator. And a multi-view consistency adversarial training mechanism is provided, and the practicability and reliability of the generated data are remarkably improved through a dual optimization target and a dual discrimination mechanism.

The invention relates to a block cipher side channel analysis method based on experience accumulation and three-dimensional decision, and belongs to the technical field of cipher security analysis and side channel analysis. Aiming at the problems of large search space, low information utilization rate, computing power waste and the like in the traditional correlation coefficient energy analysis, the method provides an analysis framework combining a dynamic hierarchical screening mechanism and a cross validation strategy. The method comprises the following steps: randomly initializing each byte of a key to generate a candidate set; constructing a three-dimensional decision-making structure comprising a data layer, a statistical layer and a decision-making layer so as to record and analyze correlation coefficient distribution; screening conditions are automatically tightened through dynamic threshold attenuation, and the search range is gradually reduced; and adopting a multi-stage single-byte perturbation and cross validation strategy to carry out iterative optimization and ranking on each byte candidate value, and finally selecting an optimal key combination to carry out verification. According to the method, the success rate, robustness and convergence speed of side channel analysis are effectively improved, and the method is suitable for key recovery of block cipher.

Methods and circuits provide mitigation against ransomware attacks by sampling one or more physical characteristics of a semiconductor device while a ransomware attack is underway. Based on the samples taken during the ransomware attack, the key used in the ransomware attack can be extracted by performing side channel analysis.

This invention relates to the field of computer technology and provides an algorithm for analyzing the complexity of EEG signals based on multi-domain fusion. The method includes: data preprocessing to acquire multi-band, multi-channel EEG signals; single-scale single-channel analysis at the single-scale level, performing single-scale single-channel analysis on the multi-band, multi-channel EEG signals and outputting multi-band fuzzy entropy; multi-scale single-channel analysis at the multi-scale level, performing multi-scale single-channel analysis on the multi-band, multi-channel EEG signals and outputting a multi-scale fuzzy entropy vector; and multi-scale multi-channel analysis at the multi-scale level, performing multi-scale multi-channel analysis on the multi-band, multi-channel EEG signals and outputting multi-channel multi-scale fuzzy entropy. This invention, through multi-band decomposition combined with multi-scale multi-channel analysis, can comprehensively capture the dynamic variation characteristics of EEG signals across different frequency bands, scales, and channels, effectively solving the problem of incomplete information extraction in traditional methods and improving the ability to characterize the dynamic characteristics and complexity of EEG signals.

A secure hash-based message authentication code (HMAC) deterministic random bit generator (DRBG) architecture is provided. In one embodiment, a circuit may include: an HMAC DRBG circuit including a counter configured to incremented based on a clock state and provide a counter output; and an HMAC function circuit coupled to the HMAC DRBG circuit, the HMAC function circuit comprising a first hash circuit and a second hash circuit, the HMAC function circuit configured to implement an HMAC function using the first and second hash circuits and a counter output, the HMAC function circuit is configured to divide the key into a first share and a second share based on the counter output, and provide the first share to the first hash circuit and the second share to the second hash circuit.

The invention provides a side channel analysis method based on a convolutional auto-encoder and a parallel analysis model, and the method comprises the steps: collecting an initial trajectory curve of a target device, the initial trajectory curve being an unknown attack trajectory curve, and the target device being a to-be-attacked device containing a secret key; the initial trajectory curve is input into a preset convolution auto-encoder, a target trajectory curve is obtained, and the target trajectory curve and the initial trajectory curve both comprise the same key features; inputting the target trajectory curve into a pre-trained second network model, and inputting the initial trajectory curve into a pre-trained first network model to respectively obtain a second attack result and a first attack result; based on a preset fusion algorithm, fusing the second attack result and the first attack result to obtain a key of the target device; wherein the second network model is a model obtained by utilizing a self-defined loss function and based on the guidance training of the first network model.

The application discloses a side channel analysis method and system of a matrix restriction regularization adaptive optimization, wherein the method steps comprise: obtaining a plurality of side channel trace data and recombining and dividing; pre-processing the divided side channel trace data to obtain processed data; constructing a side channel analysis model, classifying and identifying the processed data to obtain the probability of a predicted label value of each side channel trace data; optimizing the side channel analysis model based on the obtained probability of the predicted label value of the side channel trace data to obtain a final model; and completing side channel analysis by using the final model. The application improves the model training stability and generalization ability by adaptive learning rate and regularization term, avoids overfitting, and accelerates the convergence speed, especially when the data is limited or the model is complex.

The embodiment of the invention provides a data processing method and a task platform. The data processing method comprises the following steps: acquiring a ligand to be screened and a target protein conformation; determining at least one binding channel corresponding to the target protein conformation; calculating channel energy information of each combination channel corresponding to the ligand to be screened, and obtaining channel attribute information corresponding to each combination channel; determining a combination weight corresponding to each combination channel according to the channel energy information and the channel attribute information of each combination channel; and selecting a target binding channel corresponding to the to-be-screened ligand and the target protein conformation according to each binding weight. According to the method, an index for measuring the binding difficulty degree of the protein and the ligand is obtained by utilizing the results of channel analysis and energy analysis through a probability statistics method. And false sun conditions can be effectively screened and filtered.

A memory encryption system and method are disclosed, which rotates encryption keys to robustly resist side-channel analysis (SCA)-based attacks on the communication path between the encryption engine and external memory components within a trust boundary. A key data structure has multiple keys used to encrypt multiple blocks of memory in the external memory. The memory block encrypted using the oldest key in the key data structure is identified. Encrypted data is read from the identified memory block. The encrypted data from the identified memory block is decrypted. The data is then re-encrypted using a newly selected key (more recent than the oldest key) and rewritten to the identified memory block.

The invention relates to the technical field of wireless communication and vehicle-mounted multimedia interaction, in particular to a vehicle-mounted station video return and multi-mode audio interaction system, which comprises a service shunting module used for determining a priority label of audio stream data according to an identification result; the channel analysis module is used for evaluating the channel capacity and the interference level of the current time-frequency resource; the power domain distribution module is used for dynamically calculating a power distribution coefficient and dividing the total transmitting power of the vehicle-mounted communication terminal into a first power level and a second power level; the superposition coding module is used for generating multiple layers of superposition signals; the transmission control module is used for directly transmitting the multi-layer superposed signal to a base station side through a radio frequency unit in a scheduling-free transmission mode under the condition that a scheduling request signaling does not need to be sent; according to the method, the competition conflict of high-definition video return and key voice interaction on limited time-frequency resources in vehicle-mounted wireless communication is effectively solved, and efficient concurrency of heterogeneous services is realized.

The application relates to an artificial intelligence side channel analysis method and device based on cross-device incremental learning, applied to the field of information security password technology, and comprising the following steps: collecting side information when multiple modeling devices running symmetric password algorithms perform secret information related operations, then constructing a key leakage model, taking the Hamming weight of a secret intermediate value corresponding to each piece of side information as a label to construct a data set, using a memory sample playback strategy to sequentially train multiple data sets, obtaining a final neural network model for predicting corresponding secret intermediate value information according to side information, finally using the trained model to predict the intermediate value information to calculate the key, and completing key recovery; the final model trained by the scheme has stronger generalization ability and robustness when facing new target devices, effectively solves the bottleneck problem of cross-device side channel analysis, reduces the influence of device changes on the performance of the cross-device modeling type password side channel analysis method, and realizes efficient recovery of the key.

The invention relates to the technical field of sodium aluminate solution analysis, and provides a sodium aluminate solution on-line analysis system and method.The sodium aluminate solution on-line analysis system comprises an on-line sampling module used for automatically collecting a sodium aluminate solution sample from a production pipeline and conducting pretreatment on the sodium aluminate solution sample, and filtering suspended particles and conducting automatic dilution according to the concentration range; the multi-channel analysis module integrates a near infrared spectrum analysis unit, a potentiometric titration analysis unit and a conductivity / TOC sensor unit and is used for synchronously detecting the contents of aluminum oxide, total alkali, caustic alkali and carbon alkali in the sodium aluminate solution; and the intelligent control module is based on a PLC (Programmable Logic Controller) or an industrial computer and is used for controlling an analysis process and optimizing detection parameters. Through synchronous operation of the multi-channel module, the traditional manual detection period of 2-6 hours is greatly shortened to 20-40 minutes, and the real-time performance is improved by matching with the full-process automatic design of automatic sampling, filtering and diluting; meanwhile, due to cooperative application of technologies such as near infrared spectrum and potentiometric titration, the detection precision reaches + / -0.5%.

The invention relates to the technical field of biomedical engineering, and discloses an electromyographic signal simulation display method and system, and the method comprises the steps: carrying out the channel analysis and synchronous verification of a mixed signal sequence, and constructing a shunt signal which retains the time sequence correlation; extracting envelope features of the signals and performing trend fitting correction to generate initial intensity distribution; constructing an interference distribution diagram based on cross-correlation analysis, and determining an intensity correction value by using adaptive filtering and residual analysis; carrying out reverse reconstruction on the signal in combination with a tissue impedance model, and restoring real muscle activity distribution; and finally, mapping the distribution data to a visual model, and generating a muscle activity image through interpolation and sharpening processing. According to the method, the problem of low visual image accuracy in the prior art can be solved.

The application discloses a nuclear reactor core sub-channel analysis method based on a two-fluid model, comprising the following steps: 1, establishing a fluid domain calculation grid according to the structure of a nuclear reactor core or an assembly; 2, establishing a control equation set and a fuel rod heat conduction model for continuous gas-liquid phases and discrete droplet phases respectively; 3, considering flow heat exchange, resistance pressure drop and turbulent flow mixing and other physical phenomena in the core, implanting corresponding constitutive models; 4, discretizing the control equation based on a second-order discrete format to obtain a discrete equation set; 5, dividing parallel tasks and parallel regions through an MPI parallel strategy to form a large coefficient matrix of a pressure equation; and 6, solving the discrete equation set and the large coefficient matrix through a pressure coupling semi-implicit algorithm and a stable double-conjugate gradient method. Through the method, key physical parameter distribution of a pressurized water reactor can be more accurately and reasonably calculated, thereby providing technical guidance for reactor safety analysis and engineering design.