107 results about "Chaotic encryption" patented technology

The invention relates to the technical field of network information security, in particular to a novel network information security method and system, and the method comprises the following steps: injecting a dynamic variation engine into the bottom layer of a network protocol stack, and generating a variation protocol fingerprint; generating an equipment identity label with space-time dynamic property; selecting a protocol encapsulation channel based on chaotic encryption or a disguised transmission channel based on bait data injection, wherein the protocol encapsulation channel encrypts or obfuscates an original protocol; a self-adaptive bait generator is embedded in the camouflage transmission channel; extracting attack fingerprints; and inputting the attack fingerprint into the antagonistic defense strategy generator, and synchronously updating the distortion parameter of the dynamic variation engine. According to the invention, the distortion parameter of the dynamic variation engine and the adaptive adjustment mechanism based on the attack fingerprint ensure that the defense strategy always dynamically confronts the attack behavior, and the robustness of the protocol layer protection is improved.

The invention belongs to the technical field of intelligent information, and particularly discloses a government affair security management intelligent system which comprises a data acquisition and integration module, a security situation awareness module and a core security management engine. Multiple innovative algorithms such as multi-source data fusion and deep transfer learning are adopted, and the functions of security threat prediction, personnel behavior supervision, emergency response decision optimization and the like are achieved. The invention also covers embodiments such as threat tracing based on the knowledge graph and the graph neural network, quantum key distribution, data transmission security of chaotic encryption and the like. All the modules cooperate with algorithms, safety of government affair system information, personnel, networks and the like is guaranteed in an all-around mode, safety management efficiency and emergency handling capacity are effectively improved, and safety risks are reduced.

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 discloses an independent double-single-side-band direct detection system based on geometric shaping and digital chaotic encryption, and belongs to the field of terahertz communication. According to the detection system, an external cavity laser ECL of a sending end generates continuous optical carriers, the continuous optical carriers are input into an I / Q modulator, a TX-DSP module generates two independent vector radio frequency signals of GS-QPSK and GS-NQAM through geometric shaping and a three-dimensional multi-vortex chaos system technology, the I / Q modulator is driven to modulate the input optical carriers, and the optical carriers are transmitted to a receiver. After being amplified, the terahertz signals are input into a one-way carrier photoelectric detector for frequency beating to obtain independent double-sideband terahertz signals, the independent double-sideband terahertz signals are input into a frequency mixer of a receiving end for frequency mixing with generated local oscillation signals, down-conversion of the signals is achieved, and fundamental frequency signals are obtained; and then the data are input to an RX-DSP module, normalization, down-sampling, signal separation, de-mapping, symbol-level and bit-level decryption and other operations are carried out, and finally two paths of original data are obtained to solve the bit error rate. According to the invention, the system communication capacity is improved, and the security of independent double-sideband signal transmission is improved.

According to the invisible watermark embedding method based on the wavelet domain statistical characteristics, the high-frequency sub-band in the wavelet domain is selected as the embedding area, and the robustness of the watermark to conventional attacks such as compression and noise is improved while invisibility is guaranteed. Based on a self-adaptive embedding weight mechanism of a covariance matrix eigenvalue, the embedding strength of different texture regions can be dynamically adjusted, the robustness is enhanced by a smooth region, and distortion is suppressed by an edge region. Nonlinear disturbance is generated by adopting a deep neural network and chaotic encryption preprocessing is combined, so that the predictability of a linear statistical rule is broken, and the method has a relatively good application prospect.

The invention discloses a multi-dimensional assembly line batch encryption method for a cloud control system, which comprises the following steps of: performing chaos encryption on pipeline row and column shuffling on large code words and subcarrier mapping, and encrypting control data generated by a cloud server side by using encryption keys marked as X, Y and Z, the encrypted control data is transmitted to the client through a set number of subcarriers, and the client decrypts the encrypted control data to control the controlled object, so that the security and low bit error rate of the data transmission process in the cloud control system are effectively ensured.

The invention relates to the field of Internet of Things equipment security upgrading, and discloses an intelligent washing machine embedded software online upgrading method and system, and the method comprises the following steps: 1, a server side stores an encrypted upgrading program file and calculates a verification value, issues the verification value in a wireless manner at a set time, generates an equipment uniqueness voucher based on a physical unclonable function, and sends the equipment uniqueness voucher to the server side; establishing equipment identity binding; 2, dynamically calculating a network coding parameter based on the equipment uniqueness voucher according to a real-time channel quality parameter; and 3, based on the network coding parameters, carrying out dynamic block network coding transmission on the upgrade data, and generating an encrypted upgrade data packet by adopting chaotic encryption in the transmission process. According to the invention, an end-to-end security authentication system is realized by binding the unique voucher of the equipment and establishing an encrypted transmission channel. According to the scheme, the unauthorized access and firmware tampering are effectively prevented by utilizing the dual guarantee of hardware features and a cryptographic algorithm.

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 provides a signal encryption and decryption method and system based on a fractional order memristor neural network, relates to the technical field of digital signal processing, and aims to solve the problems that the decryption accuracy and stability are influenced due to the adoption of finite time synchronization in the existing signal encryption and decryption technology, and the encryption efficiency is low due to the adoption of integer order to limit the signal encryption security. According to the method, a chaotic signal is acquired through a fractional order memristor neural network model, encryption and decryption are realized by combining random signal preprocessing and chaotic encryption strategies based on predefined time synchronization characteristics of the model, and a random signal and a plaintext signal before synchronization form a mask signal at a sending end according to preset adjustable synchronization time; encrypting the mask signal by using a chaos sequence; at a receiving end, decoding is carried out according to preset synchronization time; therefore, the accuracy and the high efficiency of decryption are ensured. The problems in the prior art are solved, efficient and safe signal encryption and decryption are achieved, and reliable guarantee is provided for communication safety.

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 relates to the technical field of visible light communication (VLC), particularly discloses a multi-band CAP digital chaotic encryption method and system in a band-limited visible light communication system, and designs three encryption modes of chaotic constellation mapping, chaotic index selection and chaotic PWC coding. According to the chaotic constellation mapping, the positions of constellation points in the corresponding original constellation set are adjusted according to the constellation bits, and a new chaotic constellation set is obtained; the chaotic index selection is used for scrambling a corresponding relation between two distinguishable constellation modes and two encrypted chaotic constellation sets; and performing sub-band sequence chaotic encryption on m sub-bands obtained after block creation by chaotic PWC coding, disorganizing the sequence of the m sub-bands, and then performing PWC coding. Three encryption modes are designed, when confidential information is located in the coverage range of the VLC system, useful information in the system can be prevented from being eavesdropped by unauthorized malicious users, and therefore the information transmission safety is enhanced.

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 provides an unmanned aerial vehicle path tracking control method based on chaotic encryption and disturbance observation, and belongs to the technical field of unmanned aerial vehicle control, data encryption and interference resistance. Comprising the steps that measurement data of an aircraft is encrypted through a key stream, and the key stream is obtained through Logistic map chaotic nesting encryption, chaotic system switching and random key stream coefficient distribution; transmitting the ciphertext measurement data to a controller of the aircraft for decryption based on the communication interface; generating a control instruction according to the decrypted measurement data; a chaos encryption algorithm and a disturbance observer control strategy are combined, and the dual requirements of the VTOL-FW for measurement data secure transmission and anti-disturbance control in a dynamic flight scene are met.

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 robust federated learning method and system based on chaotic encryption and dual-server enabling, and belongs to the technical field of data security. The method is provided for solving the problems that an existing federated learning privacy protection method is generally high in calculation overhead, and an existing method for protecting federated learning privacy by using chaotic encryption does not support edge nodes to encrypt by using different initial values. According to the technical key points, edge nodes are allowed to encrypt local model parameters by using different initial values, the characteristic of mutual offset exists between ciphertexts, and a result in a plaintext form can be obtained after aggregation; secondly, constructing a dual-server detection mode, and performing layered detection on a local model; and finally, providing a reputation sub-mechanism, performing reputation evaluation on the edge nodes according to a detection result, filtering Byzantine edge nodes, and aggregating local model parameters of honest edge nodes. Security analysis shows that the method can effectively prevent privacy leakage of edge nodes; experimental results show that under Byzantine attack, the test accuracy of the method is averagely 18.33% higher than that of a baseline scheme, and compared with homomorphic encryption methods such as CKKS and BFV, the time overhead is at least reduced by 69.8%, and privacy protection and Byzantine robustness can be efficiently considered. The method is suitable for fault diagnosis of the rolling bearing.

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 present invention discloses a chaotic block encryption method, system and medium based on random selection of a model, which belongs to the field of information security technology and is used to solve the technical problems that the existing chaotic encryption algorithm is easily cracked and maliciously attacked when used alone, and relies on the internal characteristics of nonlinear functions, does not expand the secret key space, and has limited improvement on the security of the secret key. The method includes: based on a preset chaotic system, constructing a chaotic system model library; the chaotic system model library contains several chaotic subsystems; based on binary coding, generating a secret key initial field for the original image; according to the secret key initial field, selecting a corresponding target chaotic subsystem in the chaotic system model library; encrypting the original image through the target chaotic subsystem to obtain an encrypted image. The present invention designs a row-level image chaotic encryption algorithm to improve the image encryption speed. It also increases the secret key length, expands the secret key space, and increases the security of the secret key.

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 invention relates to the technical field of image processing, in particular to an image chaotic encryption method and system based on a magnetic control memristor, and the method comprises the steps: obtaining a to-be-processed image; constructing a fractional order variable parameter hyper-chaos model through a magnetic control memristor; features of an image to be processed are used as initial parameters of the fractional order variable parameter hyper-chaos model, and a multi-dimensional key stream is dynamically generated through the fractional order variable parameter hyper-chaos model; performing preprocessing operation and blocking operation on the to-be-processed image; based on the multi-dimensional key stream, performing dual scrambling on the to-be-processed image after block processing to generate a scrambled image; performing dynamic diffusion and nonlinear confusion on the scrambled image through a fractional order difference feedback mechanism to generate a one-dimensional ciphertext vector; and remodeling the one-dimensional ciphertext vector to generate an encrypted image. According to the method, the security of the key stream can be remarkably improved, and a solid physical layer guarantee is provided for image encryption.

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 present invention discloses a secure communication method and system based on chaotic prediction and interleaving coding in a reserve pool. The chaotic encryption module includes a light source output by a first continuous wave laser (CW), which is modulated by a parallel quadrature modulator (IQM) to convert the signal output by an arbitrary waveform generator (AWG) for transmission. The signal is pseudo-randomly interleaved and encoded. The transmitted signal is loaded onto a chaotic carrier through a first optical coupler (FC) to achieve chaotic hiding. The chaotic optical carrier is then transmitted through an information transmission module. The chaotic optical carrier is predicted in advance by the reserve pool in the chaotic decryption module and modulated onto the continuous optical carrier output by a second continuous wave laser (CW) through a Mach-Zehnder modulator (MZM). The signal is then decrypted by a 90° mixer to initially restore the original transmitted signal. Finally, the resulting signal is processed by a local oscillator (LO) and a coherent receiver, and digital information processing (DSP) is performed to compensate, recover, and decrypt the digital signal, thereby realizing chaotic secure coherent optical communication.

The invention discloses a chaos watermark-based network attack event traceability processing method and device and a medium, and relates to the technical field of industrial Internet of Things security, and the method comprises the steps: calculating an uncertainty index of a device behavior based on real-time data, judging a potential attack behavior, and generating an attack judgment mark and an abnormal conduction path; according to the attack judgment mark and the abnormal conduction path, a chaotic encryption watermark is embedded in a control instruction sent to an actuator, and a control instruction stream carrying the watermark is obtained; the actuator responds to the control instruction stream carrying the watermark to complete operation, monitors a deviation value between an execution result and an expected physical behavior, and generates an execution deviation value and watermark feedback data; attack source coordinate information is generated based on the execution deviation value and the watermark feedback data, an attack path map is generated, and a traceability report is pushed; according to the method, the sensor real-time data is divided into the independent data sequence groups, so that the defect of the existing method in the aspect of real-time performance is overcome.

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 invention discloses an intelligent internet-of-things medical garbage sorting and recycling system, and relates to the technical field of garbage sorting and recycling. The garbage collection module monitors a garbage can through a high-precision sensor, and data are transmitted through quantum encryption LoRa. Data transmission is combined with an LPWAN and a satellite link, and chaos encryption is used; deep reinforcement learning analysis is used for central control, a scheme is generated according to a GIS and traffic, garbage transportation depends on a multi-sensor AGV, intelligent obstacle avoidance, automatic charging and intelligent sorting can be achieved through a Raman spectrum and a flexible mechanical arm, and a block chain and a quantum watermarking technology are used for monitoring and tracing. Efficient collection through the intelligent garbage can, accurate transportation through the AGV, intelligent sorting through the spectrum and the mechanical arm, sterilization through the advanced disinfection technology and whole-course tracing through the block chain are achieved; the medical waste treatment efficiency is comprehensively improved, the pollution risk is reduced, and the safety and sanitation of the medical environment are guaranteed.

The present invention discloses an independent dual-single-sideband direct detection system based on geometric shaping and digital chaos encryption, which belongs to the field of terahertz communication. In the detection system, the external cavity laser ECL at the transmitting end generates a continuous optical carrier, which is input to the I / Q modulator. The TX-DSP module uses geometric shaping and three-dimensional multi-vortex chaotic system technology to generate two independent vector radio frequency signals of GS-QPSK and GS-NQAM, drives the I / Q modulator to modulate the input optical carrier, and after amplification, inputs it to a single-row carrier photodetector for beat frequency to obtain an independent double-sideband terahertz signal, which is input to the mixer at the receiving end for mixing with the generated local oscillator signal to achieve signal down-conversion and obtain a baseband signal; then it is input to the RX-DSP module for normalization, down-sampling, signal separation, demapping, symbol-level and bit-level decryption, and finally obtains two channels of original data to calculate the bit error rate. The present invention improves the communication capacity of the system and improves the security of independent double-sideband signal transmission.