61 results about "Chaotic encryption" patented technology

The invention discloses an intelligent abnormity early warning system for an industrial Internet of Things edge node, which comprises an edge sensing layer, an edge intelligent layer and a cloud edge collaboration layer, and is characterized in that the edge sensing layer is used for data acquisition and security preprocessing; the edge intelligent layer is used for intelligently analyzing the data transmitted by the edge sensing layer and constructing a dynamic space-time diagram neural network model and a dynamic edge knowledge graph; a digital twinning threshold engine is set, when the digital twinning threshold engine detects abnormity, reverse reasoning is carried out along the knowledge graph, and self-adaptive early warning is carried out; and the cloud edge collaboration layer is used for carrying out collaboration processing on early warning triggered by the digital twin threshold engine. According to the invention, the spatial-temporal features of the equipment group are learned through the set dynamic spatial-temporal diagram neural network; the digital twin threshold engine generates a dynamic threshold based on physical simulation and adapts to environment and load changes; the edge layer realizes lightweight real-time analysis; and a full-link embedded chaotic encryption and national cipher SM4 algorithm is adopted.

The invention relates to the technical field of data processing, and discloses a multi-terminal collaborative office data intelligent synchronization and privacy protection method, and the key points of the technical scheme are as follows: system initialization and node registration, intelligent data synchronization based on edge-federated learning, chaotic encryption and key negotiation, dynamic differential privacy protection, and block chain storage and lightweight consensus. An edge-block chain-cloud three-level architecture is adopted, federated learning, chaotic encryption, dynamic differential privacy and a DQN-Raft + consensus technology are integrated, and efficient intelligent synchronization and full-life-cycle privacy protection of multi-terminal office data are realized through full-process association of core parameters such as identity verification parameters, terminal weights and model errors. And meanwhile, the heterogeneous adaptation complexity of the system is reduced.

The invention relates to the technical field of electric digital data processing, and discloses an intelligent campus network security protection system. A network data acquisition module of the system continuously monitors data transmission flow of a smart campus network environment to obtain an original data packet; the chaotic encryption engine encrypts an original data packet by using a key stream based on dynamic chaotic mapping, wherein the key stream is generated by multi-chaotic system switching and a random parameter distribution mechanism; the security protocol processing module converts the encrypted data packet into a format conforming to a network security protocol standard and transmits the encrypted data packet; the data decryption unit decrypts the received encrypted data packet; the security threat analysis module identifies and estimates potential network attack behaviors according to the decrypted plaintext data; and the protection strategy controller generates and executes a network security protection instruction according to the threat analysis result. The system can effectively protect the network security of the smart campus, resist various network attacks, and ensure the security of data transmission and storage.

The invention discloses an information security data processing method based on biological characteristics and quantum enhancement, and belongs to the technical field of network and information security. Comprising the steps of collecting and preprocessing multi-dimensional biological characteristic data of a user; generating a dynamic correlation factor through weighted coupling calculation; a dynamic encryption key is generated through nonlinear coupling in combination with the quantum random number sequence; evaluating the environmental safety of the terminal by using a cognitive environmental credibility verification model; if the environment is credible, configuring a chaotic encryption parameter based on a dynamic key to encrypt target data and generate an integrity check code; and the receiving end generates a key through the same process and completes decryption and integrity verification. According to the method, the dynamic generation and'one-time pad 'of the secret key are realized, the secret key does not need to be stored, and a'biology-quantum-environment' three-in-one safety protection system is constructed by combining biological characteristic uniqueness, quantum randomness and environment credibility verification, so that the anti-cracking capability of data encryption and the adaptability of a terminal environment are effectively improved.

The invention discloses a medical image robust watermarking algorithm based on a re-parameterized high-efficiency attention network, and relates to the field of image data processing methods, and the algorithm comprises the steps: obtaining an original medical image; a pre-trained RepEA-Net model is used for extracting multi-scale deep features with good generalization performance from an original medical image, and then a mean perceptual hash algorithm is used for generating feature vectors. Obtaining an original watermark image; the watermark image is encrypted by using a Logistic chaotic encryption algorithm, the security of the watermark image is improved, and finally, the encrypted watermark image and the binary feature vector are subjected to XOR operation to generate the zero watermark. Through the innovative design of the re-parameterization efficient attention network, the contradiction among robustness, generalization and image integrity of a traditional medical image watermarking algorithm is broken through, and a solution with technical advancement and clinical practicability is provided for copyright protection and safe transmission of medical images in the medical Internet of Things.

The invention discloses an industry and trade enterprise security risk intelligent management system and method, and relates to the technical field of information security. The method comprises the following steps: firstly, obtaining a preprocessed industrial and trade enterprise original image, and segmenting to obtain a sub-original image set; updating a preset chaotic mapping parameter according to historical data to obtain an optimized parameter, and inputting the optimized parameter into mapping iteration to generate a chaotic sequence set; then, scrambling and diffusion control keys are extracted from the sequence according to a preset rule, and the two keys are used for performing data conversion and encryption on the target original sub-image to obtain an encrypted sub-image; and then, according to a preset rule, storing the sub-encrypted images in different physical positions, and finally, through a preset transmission path, transmitting a storage path and the two secret keys to a cloud end. According to the method, parameters are optimized according to historical data to improve the key suitability and security, the complexity and cracking resistance are enhanced through chaotic encryption, the leakage risk is reduced through sub-image scattered storage, and the whole-process security of enterprise production monitoring image data is comprehensively guaranteed.

The invention relates to a multifunctional intelligent communication method based on multi-modal emotion perception and dynamic encryption, and belongs to the crossing field of communication technology, artificial intelligence and information security. The method comprises the following steps: S1, extracting and fusing texts, voices and images input by a user through a multi-modal emotion recognition model in combination with historical emotion data and behavior modes in a knowledge base to analyze emotion features, and introducing an attention mechanism to perform multi-modal feature weighting to realize accurate classification of emotion types and intensities; based on a classification result, dynamically triggering a response strategy through an AI agent decision engine; and S2, through a content sensitivity analysis module, using a deep learning model to identify the sensitivity level of the chat content in real time, coordinating a plurality of encryption agents based on an MCP, dynamically adjusting the intensity of an encryption algorithm, generating a dynamic key by using a logistic chaotic encryption algorithm, constructing a multi-level key management system, and ensuring the security and efficiency of end-to-end communication.

The invention discloses a local data updating method and system in a local database, relates to the technical field of data management and security, and realizes user identity authentication by acquiring electrocardiogram and environment data through an edge computing node to generate a dynamic permission token. And then, the system verifies and authorizes a database updating request, and performs data fusion analysis by adopting federated learning and a deep neural network to ensure the security and accuracy of data updating. In the data updating process, the system uses chaotic encryption and a trusted execution environment to guarantee the confidentiality and integrity of data. And after updating, broadcasting an operation record through a block chain network, and performing auditing and rollback control by using zero-knowledge proof and a smart contract. And finally, ensuring the integrity and non-tampering property of data recovery by adopting a hash chain technology. Through multi-technology fusion, the security, reliability and efficiency of the data updating process are improved.

The invention discloses a watermark generation method and system based on artificial intelligence. The method comprises the following steps: extracting a depth characteristic spectrum of a to-be-protected model and generating a multi-scale topological code; segmenting the codes to generate a dynamic execution unit sequence, and marking decision nodes; constructing a nonlinear path containing random displacement, conditional branches, noise channels and virtual nodes; iteratively optimizing the watermark engine in stages; generating an irreversible identifier through a generative adversarial network, and fusing the dynamic sequence and the identifier to generate a confusion structure; and a watermark driving engine is generated through quantum noise compression, chaotic encryption and recursive iteration, and finally a deployable module is generated. The system comprises a feature extraction module, a path construction module, an iterative optimization module and the like. According to the method, through multi-level confusion, cross-domain fusion and active defense mechanisms, the reverse analysis resistance of watermarks is remarkably improved.

The embodiment of the invention provides a data processing method and device, a medium and a program product, and relates to the field of information security. The method comprises the following steps: processing original data through a Hash algorithm to generate first verification data; generating an encryption key through a key derivation algorithm, generating an encryption sequence through a chaotic system based on the encryption key, and combining the encryption sequence with the original data to obtain encrypted data; and decrypting the encrypted data and generating second verification data, and comparing the second verification data with the first verification data. Based on the method, multi-layer protection can be realized, and complex attacks can be resisted. When abnormal decryption is carried out, Hash verification, key derivation and chaotic encryption need to be cracked at the same time, so that the attack cost is remarkably improved, the encryption unpredictability is improved, and the accuracy of data integrity verification is ensured.

The application discloses a high-security-probability shaping method based on three-dimensional constellation joint shaping, applies a probability shaping (BCPU-PS) scheme based on a bit-level probability updating strategy to a three-dimensional constellation after geometric shaping, realizes probability shaping by modifying the probability distribution of bit positions of a sending end, and avoids coding and calculation complexity introduced by traditional probability shaping technology. The joint shaping technology improves the transmission rate of a signal and improves the bit error rate performance. In addition, in order to prevent the signal from being eavesdropped or tampered with during transmission, the scheme introduces a chaotic encryption technology, uses a key generated by a three-dimensional chaotic system to perform multi-layer encryption on bits, symbols and time domain subcarriers of the sending end, and thus realizes high security, large capacity and high rate signal transmission.

The invention discloses a high-dimensional chaotic key stream generation method and device based on closed-loop dynamic parameter control, a storage medium and a data chaotic encryption method. In the key stream generation method, multiple iterative mapping is performed on respective initial values through multi-stage one-dimensional chaotic mapping, and control parameters of next-stage one-dimensional chaotic mapping iteration are formed based on input of each stage of one-dimensional chaotic mapping through transformation operation. And forming a control parameter of the first-stage one-dimensional chaotic mapping iteration based on the input of the last-stage one-dimensional chaotic mapping. The device and the storage medium are used for implementing the key stream generation method. In the data chaotic encryption method, a high-dimensional chaotic key stream is generated based on the high-dimensional chaotic key stream generation method, a key is obtained based on the high-dimensional chaotic key stream, and the key and a plaintext are subjected to XOR operation to obtain chaotic encryption data. According to the method, the high-dimensional chaotic key stream under any-dimensional chaotic mapping can be constructed, the chaotic performance is remarkably improved, and the hardware cost is low.

The application discloses a kind of non-coherent optical phase disturbance encryption method, device, storage medium and equipment, belong to optical communication technical field, method includes: obtaining first plaintext image and second plaintext image;Chaotic encryption is obtained by the first plaintext image by chaos system, and the key of chaotic encryption process is saved to the second plaintext image;The gray value of the first ciphertext image is mapped into pseudo-random phase map;The second plaintext image is encrypted by non-coherent image encryption as the phase map in the non-coherent image encryption process of pure phase disturbance, and the second ciphertext image is obtained;The application can improve transmission security.

The invention discloses a female endocrine metabolism intelligent monitoring method, system, device and medium, a secondary encryption mode combining improved chaotic encryption and AES encryption is adopted, an adaptive parameter adjustment mechanism is introduced into the improved chaotic encryption, chaotic system parameters are dynamically adjusted according to data block characteristics, the key space is expanded, and the encryption efficiency is improved. The encryption complexity is enhanced; and AES encryption, HTTPS protocol transmission and a CRC verification mechanism are combined, so that the security and integrity of data transmission are greatly improved, and the problem of insufficient privacy protection in the prior art is solved.

The application provides an OFDM encrypted signal PAPR suppression method and system based on a self-encoder, which comprises the following steps: collecting a data sequence of an OFDM system, splitting a complex signal of the data sequence into a real part and an imaginary part to obtain an input sequence; inputting a chaotic neural network; allowing the chaotic neural network to perform chaotic encryption on the input sequence to obtain encrypted data; inputting the encrypted data into an encoder, allowing the encoder to extract features of the encrypted data and compress the features to a low latitude to obtain a low latitude result; inputting the low latitude result into a decoder to obtain a reconstruction result; performing inverse fast Fourier transform on the reconstruction result to obtain a time domain signal; converting the time domain signal into a frequency domain form for reconstruction to recover an original signal; and restoring the data sequence according to the original signal. The application has a significant improvement in reducing the performance of an encrypted OFDM signal, and the improvement is 10.7 dB compared with a non-suppression algorithm and 2.1 dB compared with an existing PRNet scheme.

This invention discloses a method for secure encryption of medical data, relating to the field of data encryption technology. The method includes implementing access control based on security levels, acquiring original medical images after authorization verification, stacking the images into a three-dimensional cube by channels, dynamically dividing them into blocks according to security levels, generating a chaotic encryption key based on the block information, and performing encryption operations on each three-dimensional block to obtain encrypted ciphertext. By destroying pixel correlation through channel stacking and segmentation, combined with differentiated keys generated by chaotic mapping, the key space and encryption efficiency are significantly improved, effectively resisting brute-force and statistical attacks. Permutation and substitution operations enhance the randomness of the ciphertext, ensuring encryption adapts to security levels and operates in a closed loop, guaranteeing controllable access permissions, improving the targeting and security of medical image encryption, and enabling flexible access for authorized users while ensuring efficient data encryption.

The invention discloses a secure coherent optical fiber communication encryption method based on digital fingerprints and chaotic encryption. The secure coherent optical fiber communication encryption method comprises the following steps: synchronously generating a chaotic key sequence and a digital fingerprint sequence with uniqueness by using the same chaotic source; then, digital fingerprints are embedded into encrypted data streams in a physical layer in a modulation format dynamic switching mode, and digital fingerprint embedding mapping and hybrid modulation are completed; and finally, fingerprint extraction is carried out at a receiving end by calculating the constellation coset rate value of each time slot group symbol sequence, a complete digital fingerprint sequence is reformed, the reformed digital fingerprint sequence is demodulated and decrypted after being subjected to identity verification, plaintext data is recovered, and the data is sent to the receiving end. And finally realizing the integration of confidentiality protection of communication data and strong identity authentication of the communication entity.

The invention provides a chaotic encryption and control method for an aircraft instruction, and relates to the technical field of information security, and the method comprises the steps: receiving plaintext data of an aircraft control instruction, respectively injecting the plaintext data into state equations of a plurality of chaotic systems, and generating a plurality of paths of key streams; performing internal permutation operation on the multiple paths of key streams by using predefined permutation vectors respectively, and performing external interleaving operation on the multiple paths of key streams subjected to internal permutation by using an interleaving sequence specified by predefined interleaving vectors so as to combine and generate a path of composite key stream; encrypting the plaintext data by using the composite key stream to obtain a ciphertext instruction, and sending the ciphertext instruction to an aircraft control end; and at the control end, decrypting the ciphertext instruction based on a preset permutation vector and an interleaving vector, restoring the plaintext data, and generating an aircraft control signal through an output feedback control algorithm according to the decrypted plaintext data.

The invention discloses a data encryption method based on a multi-stage dynamic iteration mechanism, and solves the problem that hidden dangers are brought to system security due to the fact that secret key information is repeatedly transmitted in pseudo noise information in the existing chaotic encryption technology. According to the method, encryption information in a 16 QAM modulation format and a key sequence in a QPSK modulation format are superposed into 64QAM signals for transmission by adopting different powers, encryption dimensions and a chaos model are embedded into small-power QPSK signals at the same time, and a multi-stage dynamic iteration mechanism is combined, so that more dynamic and flexible key information updating is realized, the safety performance of a system is improved, and the method is suitable for large-scale popularization and application. And potential safety hazards caused by a fixed encryption mode and encrypted information are avoided.

The application discloses a network attack event traceability processing method and device based on chaotic watermarking, equipment and medium, relates to the technical field of industrial internet of things safety, including, calculating the uncertainty index of the behavior of the real-time data based device, and judging the potential attack behavior, generating the attack judgment symbol and the abnormal conduction path; according to the attack judgment symbol and the abnormal conduction path, embedding chaotic encryption watermarking in the control instruction sent to the executor, obtaining the control instruction stream carrying the watermarking; the executor responds to the control instruction stream carrying the watermarking to complete the operation, while monitoring the deviation value of the execution result and the expected physical behavior, generating the execution deviation value and the watermarking feedback data; generating the attack source coordinate information based on the execution deviation value and the watermarking feedback data, and generating the attack path atlas, and pushing the traceability report; the application divides the sensor real-time data into independent data sequence groups, solving the deficiency of the existing method in real-time aspect.

The application discloses a low-resolution real-time key information detection and protection method, which comprises the following steps: acquiring an image by using a network camera; using ShuffleNetV2 as a backbone network to extract sampling, using a Ge-Fusion FPN module for multi-scale feature fusion, and using an FCOS target detection head; simultaneously using a data distillation and a high-resolution pre-training method to improve the detection accuracy of a model under low resolution; and simultaneously using a chaotic encryption scheme to encrypt a detected key information region and fuse the key information region into an original image. The technical scheme of the application can improve the target detection speed and accuracy under low resolution, can be applied to the field of intelligent security and protection, and can improve the privacy performance of the network camera. The application improves the security by introducing a chaotic encryption method to protect the key information of the detected image in real time.

The invention provides a transmission data processing method and device, electronic equipment, a storage medium and a product, relates to the technical field of wireless communication, and aims to avoid collapse in the process of encrypting constellation points by encrypting depth control parameters and acquiring a preprocessed first chaotic sequence, thereby improving the encryption accuracy of the constellation points. And when encryption protection is carried out on the transmission data, the performance of the transmission data can be effectively improved. Constellation points are subjected to cohesion encryption and rotation encryption according to the first chaos sequence, the second chaos sequence and the third chaos sequence, the chaos encryption algorithm and the digital signal processing technology are combined, ultra-bandwidth large-capacity transmission data can be subjected to transparent encryption, the safety of the transmission data is protected from the bottom layer, and the transmission efficiency is improved. Therefore, dual optimization of transmission performance and data encryption is realized.

The application relates to an array storage decoding method and system based on chaotic encryption and a nonvolatile memory. The method comprises the following steps: inputting an instruction address to a Gray code counter through an IO port; generating a Gray code sequence through the Gray code counter; generating plaintext by a decoder according to the Gray code sequence; generating a secret key by an encrypter according to the input of the IO port and through a chaotic generator; adding the secret key to the plaintext by the encrypter through encryption operation based on the Gray code to generate ciphertext; and inputting the ciphertext into a storage unit. The application optimizes the circuit structure, improves the decoder and encryption, simplifies the structure, reduces the energy consumption, and optimizes the anti-interference performance.

The invention discloses a chaotic sequence generation method and system based on cosine index discrete memristors and a data chaotic encryption method.In the chaotic sequence generation method, two cosine index discrete memristors are connected in parallel to form a chaotic mapping system, and outputs of the two cosine index discrete memristors are linearly scaled and then added to obtain a chaotic value; the chaotic value of each iteration is obtained through multiple iterative calculations, the chaotic values of each iteration are arranged in sequence to obtain a chaotic sequence, and the system is used for realizing the chaotic generation method. And performing operation on the obtained chaos sequence and plaintext data to realize chaos encryption of the plaintext data. The chaos sequence generated by the method has good pseudo-randomness, so that the security is improved when the chaos sequence is used for data encryption.

The application discloses a kind of superchaotic decision encryption method, device and storage medium of AGV control system based on generalized quasi-linear observer synchronization, AGV control system includes host computer, lower computer and communication module, and host computer and lower computer establish communication by communication module, this method includes: the speed control signal of AGV dolly is injected into Lorenz chaotic system by host computer, and generalized chaotic encryption system is constructed by Lorenz chaotic system through augmentation transformation;Generalized chaotic encryption system is received, and quasi-linear observer is constructed according to generalized chaotic encryption system;Based on quasi-linear observer solution, the effective solution of quasi-linear observer is obtained, and the encryption synchronization and transmission of the decision information of superchaotic system are realized.The method provided by the application converts the encryption decryption process of decision information into the synchronization process of the chaotic system of upper and lower computers once, without separately designing encryption decryption algorithm, with the advantages of being relatively efficient and easy to implement.

The application discloses a communication-efficient privacy-preserving personalized federated learning method. The application studies a personalized federated learning based on feature fusion mutual learning, which can realize communication-efficient personalized learning by interactive training of shared models, private models and fusion models on the client. Specifically, only the shared model is shared with the global model to reduce communication cost, while the private model can be personalized, and the fusion model can adaptively fuse local knowledge and global knowledge at different stages. Secondly, in order to further reduce the communication cost and enhance the privacy of the gradient, the application designs a privacy protection method based on gradient compression. The method can well realize privacy protection and lightweight compression by constructing a chaotic encryption circulant measurement matrix. In addition, the application also proposes an adaptive iterative hard threshold algorithm based on sparsity to improve flexibility and reconstruction performance.

The invention discloses an image encryption and restoration method for a bimodal isomorphic dynamics system in a scene with high real-time requirements. The method comprises the following steps: firstly, constructing a nonlinear system, adjusting parameters under the same structure to obtain a four-dimensional chaotic system for encryption and decryption and a stochastic resonance system for noise reduction, and carrying out characteristic analysis on the two systems; and then, a chaotic encryption and decryption algorithm is researched, the algorithm firstly uses a high-randomness chaotic sequence to perform random point scrambling on an original image, then performs diffusion encryption in combination with a Latin matrix, and decryption is an inverse process of encryption, so that high-security encryption and decryption of the image are realized. And finally, a repair algorithm after large-area damage of the image is researched, the algorithm firstly utilizes a stochastic resonance system to carry out noise reduction processing on the damaged image, and then feature information is clearer through integral repair. Experiments verify that the encryption algorithm has good communication confidentiality, and the restoration algorithm can effectively restore the feature information of the image under the condition that the image is seriously damaged.

The application proposes a wavelet domain statistical feature-based invisible watermark embedding method, which selects the high-frequency subband in the wavelet domain as the embedding area, ensures invisibility, and improves the robustness of the watermark to conventional attacks such as compression and noise. An adaptive embedding weight mechanism based on the eigenvalues of the covariance matrix can dynamically adjust the embedding strength of different texture regions, enhance the robustness of smooth regions, and suppress distortion in edge regions. A deep neural network is used to generate nonlinear perturbations and combined with chaotic encryption preprocessing to break the predictability of linear statistical rules, which has good application prospects.

The invention relates to the technical field of information management and control, and discloses an electromechanical equipment information management and control method based on a BIM technology, and the method comprises the following steps: S1, deploying a multi-modal energy collection module to form a self-powered sensor network, achieving the continuous collection of equipment data, and providing an original data source; s2, a dynamic protection system is constructed according to the data collected in the S1 to provide a safe data environment, safe encryption and transmission of full-life-cycle information of the equipment are achieved, and the dynamic protection system integrates a BIM model and a chaotic encryption mechanism. According to the invention, the sampling mode of the sensor is automatically switched according to the voltage of the super capacitor, the device data can be effectively acquired in different energy states, complex wiring is not needed, the influence of power supply interruption is avoided, the continuous acquisition of the device data is realized, and the stability and reliability of data acquisition are improved.

The invention discloses a talkback chaotic encryption method and system based on effective voice data, and relates to the technical field of talkback encryption, and the method comprises the steps: carrying out the encryption of voice data through employing a first layer encryption model, and generating first encrypted information; then, splitting and recombining the first encrypted information by using a second-layer encryption model to obtain second encrypted information; randomly noising the second encrypted information to form encrypted pseudo noise information, and transmitting the encrypted pseudo noise information as an interaction signal between interphones; determining a waveform section of the encrypted pseudo noise information by using a preset pseudo noise positioning template, and converting the waveform section into second encrypted information again; and decrypting and converting the second encrypted information by using the second encryption model to obtain the first encrypted information, and decrypting and converting the first encrypted information by using the first encryption model to recover the original voice data. According to the invention, through multilayer chaotic encryption and pseudo noise disguise, the security and timeliness of talkback voice data interaction are optimized.