A method, system, medium and device for optimizing communication security based on a two-dimensional code

Abstract

A communication security optimization method, system, medium, and device based on QR codes includes: establishing a communication security optimization model based on QR codes; modeling a problem based on the established communication security optimization model by constraining the signal-to-noise ratio, power, and IRS reflection coefficient of authorized user Bob and passive eavesdropper Eve; indirectly solving the established problem model by transforming the problem to obtain the beamforming at the passive eavesdropper Eve's receiver and the beamforming vector and signal of authorized user Bob; and analyzing the average bit error rate of Bob and Eve based on the beamforming at the passive eavesdropper Eve's receiver and the beamforming vector and signal of authorized user Bob to verify the reliability of secure communication.

Description

Technical Field

[0001] This invention belongs to the field of communication security technology, and specifically relates to a communication security optimization method, system, medium and device based on QR codes. Background Technology

[0002] Security is one of the most critical issues in Internet of Things (IoT) networks. Traditional wireless communication is protected by encryption methods embedded in the network layer, which typically require high complexity. This can be unaffordable for many low-cost IoT devices. As an alternative, Physical Layer Security (PLS) technology can also achieve secure communication. PLS is based on leveraging the differences in the physical channels of authorized users, designing beamforming, interference, and artificial noise to widen the signal-to-noise ratio (SNR) or signal-to-noise ratio (SINR) gap between authorized users. With lower complexity than encryption, PLS has significant potential for protecting the communications of low-cost IoT devices.

[0003] PLS technology can enhance the security of backscatter communication (BackCom), frequently used in low-power IoT devices. BackCom is a passive communication technology that allows devices to transmit information by modulating and reflecting incoming signals from an external radio frequency (RF) source. In recent years, intelligent reflectors (IRS) have evolved into a type of backscattering device. Modulation schemes in the infrared spectrum, such as phase-shift keying (PSK) and quadrature amplitude modulation, are also available. IRS-BackCom is used for cognitive radio and offloading computational data. PLS also offers advantages over IRS-BackCom.

[0004] Quick Response (QR) codes, or RF QR codes (RF2C), as a new derivative of IRS-BackCom, can be used to achieve passive communication in low- to medium-cost, low-power IoT devices. The key idea of ​​QR codes is to map information in the form of a QR code onto an adjustable or non-adjustable information metasurface. Once an electromagnetic (EM) wave illuminates the metasurface, the information in the QR code is modulated onto the input signal. The information is propagated through signal reflection. IRS is a well-developed metasurface, making its integration with QR codes a good choice. However, QR code communication has been widely applied in various fields. During information exchange using QR codes, it is easily eavesdropped by third parties, leading to information leakage. Therefore, the security of QR codes based on novel low-power IRS as a newly proposed communication paradigm has not yet been thoroughly investigated. Summary of the Invention

[0005] The purpose of this invention is to provide a communication security optimization method, system, medium, and device based on QR codes to solve the above-mentioned problems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A QR code-based communication security optimization method includes:

[0008] A communication security optimization model for QR codes is established, which includes a smart reflective surface IRS, an authorized user Bob equipped with a transmitting antenna and a receiving antenna, and a passive eavesdropper Eve equipped with a receiving antenna.

[0009] Based on the established communication security optimization model, the problem is modeled by constraining the signal-to-noise ratio, power, and IRS reflection coefficient of authorized user Bob and passive eavesdropper Eve.

[0010] The established problem model is transformed and solved indirectly to obtain the beamforming at the passive eavesdropper Eve's receiver, as well as the beamforming vector and signal of the authorized user Bob;

[0011] Based on the beamforming at the passive eavesdropper Eve's receiver, and the beamforming vector and signal of the authorized user Bob, the average bit error rate of Bob and Eve is analyzed to verify the reliability of secure communication.

[0012] Furthermore, in the model: the secret information is mapped onto the elements of the complex reflection coefficient of the smart reflective surface IRS, forming a microwave QR code. Bob sends a radio frequency signal to the IRS to obtain the QR code; under the reflection of infrared light, the information of the QR code is modulated onto the radio frequency signal, which Bob can receive and Eve can eavesdrop on.

[0013] Furthermore, the Bob-IRS, IRS-Bob, Bob-Eve, and IRS-Eve links are respectively Quasi-static flat fading, and the channel state information of the transmitted signal at Bob's location is completely known; when Bob transmits electromagnetic waves to the IRS in a time slot, the signals received by Bob and Eve are respectively:

[0014]

[0015] in, The signal is transmitted by Bob; It is the reflection coefficient matrix at the IRS; and The white Gaussian random vectors at Bob and Eve are respectively and express; for The reflection coefficient vector at the IRS further represents the signals received by Bob and Eve as follows:

[0016]

[0017] in, Information vector

[0018] Normalized receive beamforming is used on the outputs of Bob and Eve, respectively. and The outputs for Bob and Eve are as follows:

[0019]

[0020] Bob's SNR and Eve's SINR are respectively:

[0021]

[0022] Further, problem modeling:

[0023] Eve's SINR is minimized by optimizing the transmission signal design and Bob's receive beamforming vector, under the conditions of Bob's transmit power and the minimum allowable signal-to-noise ratio:

[0024]

[0025] in For Bob's transmit power budget, The threshold value is .

[0026] Furthermore, beamforming is performed at the Eve receiver:

[0027] Between Bob and Eve in the system , and The information does not affect each other; as a passive eavesdropper, Eve's optimal strategy is based on the assumption that the information used does not affect each other. and Maximize without security protection Maximize time In mathematics Bob can estimate this by solving the following optimization problem:

[0028]

[0029] The optimization problem P1 is solved using semidefinite relaxation SDR, yielding a rank-1 solution; definition use and The optimization problem P1 is equivalently represented as:

[0030]

[0031] let ,in The optimization problem P2 can be rewritten as:

[0032]

[0033] Ignoring the rank-1 constraint C11, the optimization problem P3 is rewritten as:

[0034]

[0035] The optimization problem P4 is convex, and the optimal solution to the optimization problem P4 is obtained. We then use its largest eigenvector to calculate the suboptimal solution to the optimization problem P1. .

[0036] Furthermore, the problem substitutes optimizing the beamforming vector and signal of parameter Bob:

[0037] In the optimization problem P0, choose As an estimate of Eve's received beamforming vector; then, for the variables and Alternating optimization is performed in two steps.

[0038] Step 1): Optimization

[0039] Given The optimization problem P0 is simplified to:

[0040]

[0041] The optimization problem P5 is solved using SDR (Self-Depth Analysis) and then the solution with rank 1 is restored. definition , The optimization problem P5 is equivalently expressed as:

[0042]

[0043] make make The optimization problem P6 is rewritten as follows:

[0044]

[0045] Ignoring the rank-1 constraint C20, the optimization problem P7 is rewritten as:

[0046]

[0047] The optimization problem P8 is convex and can be solved using existing CVX tools; the optimal solution to the optimization problem P4 is obtained. By finding its largest eigenvector, we obtain the optimal or suboptimal solution to the optimization problem P5. ;

[0048] Step 2): Optimization

[0049] when pass When optimization increases, There is a larger feasible region for constraint C1; given x, the optimization problem (P0) simplifies to:

[0050]

[0051] Due to constraint C3, maximizing the objective function P9 is equivalent to:

[0052]

[0053] The Hermitian matrix was derived using spectral decomposition.

[0054] Rewritten as in It is a product of A diagonal matrix composed of eigenvalues; Definition

[0055] The optimization problem on page 9 is restated as follows:

[0056]

[0057] For the optimization problem P10, the optimal objective value is equal to... The largest eigenvalue; to obtain the optimal yes The largest eigenvector.

[0058] Further analysis of Bob and Eve's average bit error rate (ABEP):

[0059] Use size The signal constellation diagram is represented as follows: The expression for the average symbol error probability ASEP is for The element's IRS is:

[0060]

[0061] in for The estimated vector, based on which a closed-form expression for the corresponding average bit error rate can be obtained, in Bob and Eve's... The ABEPs of the BPSK of the element's IRS are as follows:

[0062]

[0063] in, yes of Elements by and composition; yes of Elements by and Composition; the probability of QPSK in the first IRS element of Bob and Eve is approximately:

[0064]

[0065] when hour, The ABEPs of the IRS of an element are approximately:

[0066]

[0067] Numerical simulations were performed to evaluate the security and confidentiality performance of the IRS-based QR code transmission system.

[0068] Furthermore, a QR code-based communication security optimization system includes:

[0069] The model building module is used to build a communication security optimization model for QR codes. The model includes building a smart reflector IRS, an authorized user Bob equipped with a transmitting antenna and a receiving antenna, and a passive eavesdropper Eve equipped with a receiving antenna.

[0070] The problem modeling module is used to model problems based on the established communication security optimization model by applying signal-to-noise ratio constraints, power constraints, and IRS reflection coefficient constraints to authorized user Bob and passive eavesdropper Eve.

[0071] The problem-solving module is used to indirectly solve the established problem model by transforming it into a solution, and obtains the beamforming at the passive eavesdropper Eve's receiver, as well as the beamforming vector and signal of the authorized user Bob.

[0072] The analysis and verification module is used to analyze the average bit error rate of Bob and Eve based on the beamforming at the passive eavesdropper's receiver and the beamforming vector and signal of the authorized user Bob, thereby verifying the reliability of secure communication.

[0073] Furthermore, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of a QR code-based communication security optimization method.

[0074] Furthermore, a computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of a QR code-based communication security optimization method.

[0075] Compared with the prior art, the present invention has the following technical effects:

[0076] This invention presents a new communication security optimization method based on QR codes. It proposes a novel communication method different from traditional QR code communication, utilizing a low-power intelligent reflective surface (IRS) and QR code communication, while considering the overall communication security of the authorized user Bob and the passive eavesdropper Eve. Furthermore, the secret information is mapped onto elements of the complex reflection coefficient of the intelligent reflective surface IRS, forming a microwave QR code. Bob sends a radio frequency signal to the IRS to obtain the QR code; under infrared reflection, the information of the QR code is modulated onto the radio frequency signal, which Bob can receive, and Eve can eavesdrop on the establishment of the complete secure communication process.

[0077] Furthermore, the Bob-IRS, IRS-Bob, Bob-Eve, and IRS-Eve links are configured as follows: and After quasi-static flat fading, and with the channel state information of the transmitted signal at Bob fully known, signal system modeling and signal-to-noise ratio analysis are performed, which can then be used to describe secure communication problems.

[0078] Furthermore, by optimizing the transmission signal design and Bob's receiving beamforming vector, and setting up a problem model for minimizing Eve's SINR under the conditions of Bob's transmit power and the minimum allowable signal-to-noise ratio, the problem of QR code secure communication is mathematically expressed.

[0079] Furthermore, since the known problems are difficult to solve directly, the beamforming settings at the Eve receiver are configured to indirectly solve the problem and obtain the suboptimal beamforming at Eve.

[0080] Furthermore, known problems are difficult to solve directly, so we choose... As an estimate of Eve's received beamforming vector; then for the variables and Optimization is performed to obtain a solution to the problem.

[0081] Furthermore, the average bit error rate (ABEP) of Bob and Eve is analyzed to evaluate the security and reliability of the QR code secure communication problem proposed in this system.

[0082] In summary, this invention solves the problem of secure QR code communication through system modeling, communication modeling, mathematical expression, problem optimization, and alternative solutions, and analyzes the average bit error rate of the results. This verifies the reliability of the QR code secure communication solution presented in this patent, and proposes a novel, low-power, secure, and reliable solution for the field of secure QR code communication. For QR code communication, which is widely applicable to various fields, and addressing the issue of information leakage due to eavesdropping by third parties during information exchange, this invention provides a secure, stable, and reliable communication system. Attached Figure Description

[0083] Figure 1 A schematic diagram of a QR code-based communication security optimization method and system;

[0084] Figure 2 For Eve's SINR and Bob's transmission power;

[0085] Figure 3 Here are Eve's average bit error rate (ABEP) and Bob's transmission power;

[0086] Figure 4 The probability of Eve's recognition versus Bob's transmission power

[0087] Figure 5 For Bob's signal-to-noise ratio and Bob's transmission power

[0088] Figure 6 Bob's average bit error rate (ABEP) and Bob's transmission power

[0089] Figure 7 Bob's recognition probability and Bob's transmission power

[0090] Figure 8 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0091] The present invention will be further described below with reference to the accompanying drawings:

[0092] Figure 1 This describes a secure transmission system for QR codes based on an IRS, including an IRS (Alise) as the information source and a device equipped with... Transmitting antenna and The authorized user (Bob) of the receiving antenna, and a device equipped with The passive eavesdropper (Eve) of the receiving antenna. In this system, confidential information is mapped onto elements of the complex reflection coefficient of the smart reflector IRS, designed to form a microwave QR code. To obtain the QR code, Bob sends a radio frequency signal to the IRS. The information from the QR code is modulated onto the radio frequency signal by the reflection of infrared light, which Bob can receive, and Eve can eavesdrop on.

[0093] The assumed channels Bob-Alice, Alice-Bob, Bob-Eve, and Alice-Eve links are respectively After quasi-static flat fading, and with full availability of channel state information (CSI) for designing the transmitted signal at Bob's location. Another assumption is that self-interference with Bob can be completely eliminated. When Bob transmits electromagnetic waves to the IRS in a time slot, the signals received by Bob and Eve are respectively:

[0094]

[0095] in This is the signal transmitted by Bob. It is the reflection coefficient matrix at the IRS. and These are white Gaussian random vectors at Bob and Eve, respectively. and It means. Let Indicates using The reflection coefficient vector at the IRS further represents the signals received by Bob and Eve as follows:

[0096]

[0097] In the system under consideration, It represents an information vector, rather than a passive beamformer.

[0098] Normalized receive beamforming is used on the outputs of Bob and Eve, respectively. and The outputs for Bob and Eve are as follows:

[0099]

[0100] Therefore, Bob's SNR and Eve's SINR are respectively:

[0101]

[0102] Problem definition:

[0103] To improve the security of Alice's QR code propagation, Eve's SINR is minimized under the conditions of Bob's transmit power and the minimum allowable signal-to-noise ratio by optimizing the transmission signal design and Bob's receive beamforming vector.

[0104]

[0105] in For Bob's transmit power budget, The threshold value is .

[0106] Eve minimizes SINR

[0107] Due to optimization variables and Due to coupling, the non-convex optimization problem (P0) is difficult to solve directly. Variables It is also included in the objective function. To handle the optimization problem (P0), estimation is required first. Based on this, an alternative optimization method can be used to minimize... After solving the optimization problem (P0), a computational complexity analysis was performed.

[0108] A. Beamforming at Eve receiver:

[0109] Between Bob and Eve in the system , and The information does not affect each other. As a passive eavesdropper, Eve's optimal strategy is based on the assumption that... and Maximize without security protection Maximize time In mathematics Bob can estimate this by solving the following optimization problem:

[0110]

[0111] The optimization problem (P1) can be solved using semidefinite relaxation (SDR), yielding a rank-1 solution. Definition use and The optimization problem (P1) is equivalently represented as:

[0112]

[0113] let in The optimization problem (P2) is rewritten as:

[0114]

[0115] Ignoring the rank-1 constraint C11, the optimization problem (P3) is rewritten as:

[0116]

[0117] The optimization problem (P4) is convex and can be easily solved using existing CVX tools. Once the optimal solution to the optimization problem (P4) is obtained... We then use its largest eigenvector to compute the suboptimal solution to the optimization problem (P1). .

[0118] B. Alternative Optimization

[0119] In the optimization problem (P0), choose As an estimate of Eve's received beamforming vector. Then, for the variables and Alternating optimization is performed in two steps.

[0120] Step 1): Optimization

[0121] Given The optimization problem (P0) is simplified to:

[0122]

[0123] The optimization problem (P5) can be solved using SDR, and then the solution with rank 1 can be restored. definition , The optimization problem (P5) is equivalently expressed as:

[0124]

[0125] make make The optimization problem (P6) can be rewritten as follows:

[0126]

[0127] Ignoring the rank-1 constraint C20, the optimization problem (P7) is rewritten as:

[0128]

[0129] The optimization problem (P8) is convex and easily solved using existing CVX tools. Once the optimal solution to the optimization problem (P4) is obtained... By finding its largest eigenvector, the optimal or suboptimal solution to the optimization problem (P5) can be obtained. .

[0130] Step 2): Optimization

[0131] From the optimization problem (P0), it is found that by optimizing... To reduce This is because when

[0132] pass When optimization increases, There is a larger feasible region for constraint C1. Given x, the optimization problem (P0) simplifies to:

[0133]

[0134] Due to constraint C3, maximizing the objective function (P9) is equivalent to:

[0135]

[0136] The Hermitian matrix was derived using spectral decomposition.

[0137] Can be rewritten as in It is a product of A diagonal matrix composed of the eigenvalues. Definition

[0138] The optimization problem (P9) is restated as follows:

[0139]

[0140] For the optimization problem (P10), the optimal objective value is equal to The largest eigenvalue. This can yield the optimal... yes The largest eigenvector.

[0141] Computational complexity analysis

[0142] The optimization problem (P0) can be solved by optimization of (P4) and substitution optimization of (P8) and (P10), where the computational complexity of optimization problems (P4) and (P8) is much higher than that of (P10). According to the interior-point method (IPM), the computational complexities of optimization problems (P4) and (P8) are respectively:

[0143]

[0144] in, This indicates the precision of the alternating iterations until convergence. and Furthermore, the computational complexity of the rank-1 optimization problem is very small compared to optimization problems (P4) and (P8). Therefore, the total computational complexity (P0) of the optimization problem is approximately:

[0145]

[0146] in It represents the number of iterations for alternating optimization.

[0147] Bob and Eve's Average Bit Error Rate (ABEP) Analysis:

[0148] Based on the design of Bob's transmitted signal and the received beamforming vectors of Bob and Eve in the previous section, the average bit error rate of the phase shift keying (PSK) for Bob and Eve in the considered secure transmission system will be calculated. A value of [missing value] will be used. The signal constellation diagram is represented as follows: The expression for the average symbol error probability (ASEP) is for The element's IRS is:

[0149]

[0150] in for The estimated vector, based on which a closed-form expression for the corresponding average bit error rate can be obtained, in Bob and Eve's... The ABEPs of the BPSK of the element's IRS are as follows:

[0151]

[0152] in, yes of Elements by and composition; yes of Elements by and Composition; the probability of QPSK in the first IRS element of Bob and Eve is approximately:

[0153]

[0154] when hour, The approximate ABEPs of the element's IRS are:

[0155]

[0156] Numerical simulations were conducted to evaluate the security and confidentiality performance of an IRS-based QR code transmission system. In the simulations, the channel was assumed to be... and Following a Rician distribution, assuming its path distance is... Loss by This indicates that Bob and Eve are experiencing noise. and .

[0157] All are set to be the same as the square of the path loss. =50m.

[0158] In the legend, "secure" represents the optimized scheme proposed for the system under consideration; "insecure" and "active" represent two corresponding parts. "Insecure" represents the optimized scheme without considering eavesdropping issues. In "active," the IRS uses active transmission instead of passive reflection, and Bob does not radiate electromagnetic waves. The legends PSK, Theo, and Simu represent the modulation scheme, theoretical results, and simulation results of PSK, respectively.

[0159] Please see Figure 2 and Figure 5 This describes how Bob's transmit power affects Eve's SINR and Bob's SNR, and the number of IRS elements. =19; Bob's The number of transmitting antennas is 16 or 8; the number of receiving antennas for Bob and Eve is... =19, =19; Distance from Bob to Alice =50 m, the distance from Bob to Eve =90m, from Alice to Eve ;

[0160] Set threshold Set the Ricin factor =0.5. The distance between Bob and Eve is set to 90 meters for the purpose of maintaining confidentiality in the event of minimal interference from Bob on Eve.

[0161] Please see Figure 2 and Figure 5 Both the secure and insecure schemes achieved a high level of confidentiality. The secure scheme offered better confidentiality compared to the insecure scheme, but had a lower signal-to-noise ratio at Bob. In the active scheme, security was not guaranteed. These results indicate that the system itself possesses good confidentiality performance.

[0162] Please see Figure 3 and Figure 6 The text describes how Bob's transmission power affects Eve's and Bob's algorithms, including the algorithms themselves. Except for 16, most simulation parameters are the same as the above settings. It can be seen that the theoretical results of BPSK, QPSK and 16-PSK schemes are almost consistent with the simulation results, while the theoretical results of 8-PSK scheme do not match at low SINR / SNR. This is because the approximations of (1) and (2) are not good enough at low SINR / SNR, especially for 8-PSK scheme.

[0163] Please see Figure 4 and Figure 7 This demonstrates how Bob's transmission power affects the recognition probability of Eve and Bob, where the number of QR modules n = 38 × 38; and the number of BPSK receiving antennas for Bob and Eve is... Number of receive antennas in 16-PSK and The IRS is composed of 38 or 19 elements, chosen from materials used in its fabrication. It can be seen that increasing Bob's transmission power and the Rician factor improves Bob's recognition probability. Furthermore, Eve's recognition probability is almost zero, verifying that the considered system provides good confidentiality when propagating QR codes.

[0164] Communication security based on IRS QR codes. Based on the established model, the confidentiality performance was optimized using Bob and Eve. Results show that:

[0165] The proposed optimization scheme can improve the system's security performance.

[0166] For Bob and Eve's ABEPs, except at low SINR / SNR, the theoretical expression for PSK is very close to the facts with respect to 8-PSK.

[0167] The system offers satisfactory security, regardless of the transmitted signal or Bob's receiving beamforming. This means that security can still be guaranteed even in the event of unknown CSI eavesdropping.

[0168] In another embodiment of the present invention, a QR code-based communication security optimization system is provided, which can be used to implement the above-mentioned QR code-based communication security optimization method. Specifically, the system includes:

[0169] The model building module is used to build a communication security optimization model for QR codes. The model includes building a smart reflector IRS, an authorized user Bob equipped with a transmitting antenna and a receiving antenna, and a passive eavesdropper Eve equipped with a receiving antenna.

[0170] The problem modeling module is used to model problems based on the established communication security optimization model by applying signal-to-noise ratio constraints, power constraints, and IRS reflection coefficient constraints to authorized user Bob and passive eavesdropper Eve.

[0171] The problem-solving module is used to indirectly solve the established problem model by transforming it into a solution, and obtains the beamforming at the passive eavesdropper Eve's receiver, as well as the beamforming vector and signal of the authorized user Bob.

[0172] The analysis and verification module is used to analyze the average bit error rate of Bob and Eve based on the beamforming at the passive eavesdropper's receiver and the beamforming vector and signal of the authorized user Bob, thereby verifying the reliability of secure communication.

[0173] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0174] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions from the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used in the operation of a QR code-based communication security optimization method.

[0175] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the QR code-based communication security optimization method in the above embodiments.

[0176] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0177] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0178] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0179] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0180] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A communication security optimization method based on QR codes, characterized in that, include: A communication security optimization model for QR codes is established, which includes a smart reflective surface IRS, an authorized user Bob equipped with a transmitting antenna and a receiving antenna, and a passive eavesdropper Eve equipped with a receiving antenna. Based on the established communication security optimization model, the problem is modeled by constraining the signal-to-noise ratio, power, and IRS reflection coefficient of authorized user Bob and passive eavesdropper Eve. The established problem model is transformed and solved indirectly to obtain the beamforming at the passive eavesdropper Eve's receiver, as well as the beamforming vector and signal of the authorized user Bob; Based on the beamforming at the passive eavesdropper Eve's receiver and the beamforming vector and signal of the authorized user Bob, the average bit error rate of Bob and Eve is analyzed to verify the reliability of secure communication. In the model: secret information is mapped onto elements of the complex reflection coefficient of the smart reflective surface IRS, forming a microwave QR code. Bob sends an radio frequency signal to the IRS to obtain the QR code. Under the reflection of infrared light, the information of the QR code is modulated onto the radio frequency signal, which Bob can receive and Eve can eavesdrop on. In the model, the Bob-IRS, IRS-Bob, Bob-Eve, and IRS-Eve links are respectively Quasi-static flat fading, and the channel state information of the transmitted signal at Bob's location is completely known; when Bob transmits electromagnetic waves to the IRS in a time slot, the signals received by Bob and Eve are respectively: in, The signal is transmitted by Bob; It is the reflection coefficient matrix at the IRS; and The white Gaussian random vectors at Bob and Eve are respectively and express; for The reflection coefficient vector at the IRS further represents the signals received by Bob and Eve as follows: in, Information vector Using a normalized receiving beam, Bob and Eve's outputs are as follows: Bob's SNR and Eve's SINR are respectively: ； Problem modeling: By optimizing the transmission signal design and Bob's receive beamforming vector, Eve's SINR is minimized under the constraints of Bob's transmit power and the minimum allowable signal-to-noise ratio: in For Bob's transmit power budget, The threshold value is ; Beamforming at Eve receiver: Between Bob and Eve in the system , and The information does not affect each other; as a passive eavesdropper, Eve's optimal strategy is based on the assumption that the information used does not affect each other. and Maximize without security protection Maximize time In mathematics Bob can estimate this through the following optimization problem: The optimization problem P1 is solved using semidefinite relaxation SDR, yielding a rank-1 solution; definition use and The optimization problem P1 is equivalently represented as: let ,in The optimization problem P2 can be rewritten as: Ignoring the rank-1 constraint C11, the optimization problem P3 is rewritten as: The optimization problem P4 is convex, and the optimal solution to the optimization problem P4 is obtained. We then use its largest eigenvector to calculate the suboptimal solution to the optimization problem P1. .

2. The communication security optimization method based on QR codes according to claim 1, characterized in that, The problem is to optimize the beamforming vector and signal of the alternative parameter Bob: In the optimization problem P0, choose As an estimate of Eve's received beamforming vector; then, for the variables and Alternating optimization is performed in two steps. Step 1): Optimization Given The optimization problem P0 is simplified to: The optimization problem P5 is solved using SDR (Self-Depth Analysis) and then the solution with rank 1 is restored. definition , The optimization problem P5 is equivalently expressed as: make make The optimization problem P6 is rewritten as follows: Ignoring the rank-1 constraint C20, the optimization problem P7 is rewritten as: The optimization problem P8 is convex and can be solved using existing CVX tools; the optimal solution to the optimization problem P4 is obtained. By finding its largest eigenvector, we obtain the optimal or suboptimal solution to the optimization problem P5. ; Step 2): Optimization when pass When optimization increases, There is a larger feasible region for constraint C1; given x, the optimization problem (P0) simplifies to: Due to constraint C3, maximizing the objective function P9 is equivalent to: The Hermitian matrix was derived using spectral decomposition. Rewritten as in It is a product of A diagonal matrix composed of eigenvalues; Definition The optimization problem on page 9 is restated as follows: For the optimization problem P10, the optimal objective value is equal to... The largest eigenvalue; to obtain the optimal yes The largest eigenvector.

3. The communication security optimization method based on QR codes according to claim 1, characterized in that, Bob and Eve's Average Bit Error Rate (ABEP) Analysis: Use size The signal constellation diagram is represented as follows: The expression for the average symbol error probability ASEP is... The element's IRS is: in for The estimated vector, based on which a closed-form expression for the corresponding average bit error rate can be obtained, in Bob and Eve's... The ABEPs of the IRS of the elements are as follows: in, yes of Elements by and composition; yes of Elements by and Composition; the probability of QPSK in the l-th IRS element of Bob and Eve is: when hour, The ABEPs of the element are: Numerical simulations were performed to evaluate the security and confidentiality performance of the IRS-based QR code transmission system.

4. A communication security optimization system based on QR codes, characterized in that, include: The model building module is used to build a communication security optimization model for QR codes. The model includes building a smart reflector IRS, an authorized user Bob equipped with a transmitting antenna and a receiving antenna, and a passive eavesdropper Eve equipped with a receiving antenna. The problem modeling module is used to model problems based on the established communication security optimization model by applying signal-to-noise ratio constraints, power constraints, and IRS reflection coefficient constraints to authorized user Bob and passive eavesdropper Eve. The problem-solving module is used to indirectly solve the established problem model by transforming it into a solution, and obtains the beamforming at the passive eavesdropper Eve's receiver, as well as the beamforming vector and signal of the authorized user Bob. The analysis and verification module is used to analyze the average bit error rate of Bob and Eve based on the beamforming at the passive eavesdropper's receiver and the beamforming vector and signal of the authorized user Bob, and to verify the reliability of secure communication. In the model: secret information is mapped onto elements of the complex reflection coefficient of the smart reflective surface IRS, forming a microwave QR code. Bob sends an radio frequency signal to the IRS to obtain the QR code. Under the reflection of infrared light, the information of the QR code is modulated onto the radio frequency signal, which Bob can receive and Eve can eavesdrop on. In the model, the Bob-IRS, IRS-Bob, Bob-Eve, and IRS-Eve links are respectively Quasi-static flat fading, and the channel state information of the transmitted signal at Bob's location is completely known; when Bob transmits electromagnetic waves to the IRS in a time slot, the signals received by Bob and Eve are respectively: in, The signal is transmitted by Bob; It is the reflection coefficient matrix at the IRS; and The white Gaussian random vectors at Bob and Eve are respectively and express; for The reflection coefficient vector at the IRS further represents the signals received by Bob and Eve as follows: in, Information vector Using a normalized receiving beam, Bob and Eve's outputs are as follows: Bob's SNR and Eve's SINR are respectively: ； Problem modeling: By optimizing the transmission signal design and Bob's receive beamforming vector, Eve's SINR is minimized under the constraints of Bob's transmit power and the minimum allowable signal-to-noise ratio: in For Bob's transmit power budget, The threshold value is ; Beamforming at Eve receiver: Between Bob and Eve in the system , and The information does not affect each other; as a passive eavesdropper, Eve's optimal strategy is based on the assumption that the information used does not affect each other. and Maximize without security protection Maximize time In mathematics Bob can estimate this through the following optimization problem: The optimization problem P1 is solved using semidefinite relaxation SDR, yielding a rank-1 solution; definition use and The optimization problem P1 is equivalently represented as: let ,in The optimization problem P2 can be rewritten as: Ignoring the rank-1 constraint C11, the optimization problem P3 is rewritten as: The optimization problem P4 is convex, and the optimal solution to the optimization problem P4 is obtained. We then use its largest eigenvector to calculate the suboptimal solution to the optimization problem P1. .

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the QR code-based communication security optimization method as described in any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the QR code-based communication security optimization method as described in any one of claims 1 to 3.

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