Secure covert communication method and system based on intelligent reflecting surface, and medium

Abstract

The invention provides a safe covert communication method and system based on an intelligent reflecting surface and a medium, and belongs to the technical field of wireless communication, and the method comprises the steps that a transmitter transmits a signal, the intelligent reflecting surface reflects the signal transmitted by the transmitter, and a receiver, an eavesdropper and a monitoring party receive the signal transmitted by the transmitter and the signal reflected by the intelligent reflecting surface; wherein the receiver detects useful signals transmitted by the transmitter; in order to realize safe covert communication, taking the maximum safe covert transmission rate as a performance optimization index, taking a transmission power constraint and a covert transmission constraint as constraint conditions, and carrying out iterative solution to obtain an optimal IRS phase; wherein the security rate is defined according to the channel capacities of the transmitter-receiver and the transmitter-eavesdropper; taking the maximum transmission power of the signal transmitted by the transmitter as a transmission power constraint condition; a bounded uncertainty model is adopted to describe noise of a monitoring party, and the condition that the detection probability of the monitoring party on a signal sent by a transmitter is lower than a fixed value is used as a hidden transmission constraint condition. According to the method, physical layer security and covert communication are cooperatively considered, and the wireless communication security performance is comprehensively improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and particularly to a secure and covert communication method, system, and medium based on an intelligent reflecting surface. Background Art

[0002] Almost all critical infrastructures in modern society, such as those in the fields of energy, transportation, finance, and healthcare, highly rely on communication technologies. Weaknesses in communication security may lead to huge economic losses and even threaten national security and social stability. Therefore, providing all-round protection for communication systems has become a common concern internationally. However, over-relying on a single security method may bring unforeseen risks when designing complex communication systems. Each security method, no matter how exquisitely designed, has potential weaknesses. As long as attackers can identify and exploit these weaknesses, the entire communication system may face serious threats. For this reason, this chapter studies the combination of two security methods, physical layer security and covert communication, and improves the resilience of communication systems with multi-level security strategies, enabling them to resist more complex and diverse attacks and providing a more comprehensive and robust protection barrier for communication systems.

[0003] Intelligent reflecting surface (IRS) is an important concept in the research of wireless communication technologies in recent years. An intelligent reflecting surface consists of a large number of tiny and low-cost reflecting units, which are usually integrated into a continuous and large-area two-dimensional plane. These units can electronically control their electromagnetic responses. These reflecting units, IRS, can dynamically adjust the phase and amplitude of each reflecting unit, thereby controlling the reflection direction and characteristics of incident wireless signals. Utilizing the above signal regulation characteristics, IRS can optimize the signal propagation path in real time, ensuring that the signal propagates from the transmitter to the receiver in the best way. By controlling the signal propagation direction, it helps the signal bypass obstacles or enhance the signal quality in a specific area, reducing potential eavesdropping and attacks, and thus can be used to improve the security of communication systems.

[0004] Many technologies have studied the IRS-assisted physical layer security (PLS) problem. To maximize the achievable rate of the system while limiting the information leakage of potential eavesdroppers, Sun et al. jointly designed the transmit beamforming of the base station and the reflecting beamforming of IRS. By applying the alternating optimization (AO) and semidefinite relaxation (SDR) methods, Cui et al. maximized the secrecy rate of the legitimate communication link. Based on block coordinate descent and min-max techniques, Yu et al. developed two algorithms to solve the non-convex optimization problems of small and large-scale IRS.

[0005] Although physical layer security provides certain protection for wireless communication systems, its security is not sufficient. In military, diplomatic, and emergency response scenarios, in addition to protecting the security of communication information, it is equally important to hide the location and behavior of communication parties. Covert communication aims to conceal the existence of the communication process, making it difficult for opponents to detect any transmitted data, and plays an important role in these situations. Kong et al. maximized the achievable rate while maintaining transmission concealment by optimizing the transmission probability, transmit power, and IRS reflection matrix, and achieved the maximization of the concealment rate through a one-dimensional search method. Wu et al. adopted a one-dimensional search method to jointly optimize the transmit power, IRS reflection phase shift, and amplitude to improve the performance of covert communication.

[0006] However, relying on a single security method may make the communication system vulnerable to attacks that exploit the weaknesses of that specific technology. By jointly considering PLS and covert communication, the network can leverage the advantages of each method to develop a more comprehensive and effective security solution. Forouzesh et al. studied the joint physical layer security and covert communication to ensure the secure communication of one user and the covert communication of another user. Wang et al. used artificial noise to create secure and covert transmission conditions for multi-user downlink communication, where the transmitter sends confidential information to legitimate users in the presence of eavesdroppers and wiretappers. However, these technologies mainly focus on the design schemes of communication nodes and do not utilize IRS to regulate the propagation environment. Aaltun et al. considered the IRS-supported secure communication against eavesdroppers and wiretappers, but in the AO method, the authors abandoned the covert constraint of IRS phase shift optimization and only maximized the channel capacity of Bob for a given phase.

[0007] In summary, how to ensure the transmission of more confidential information without being detected is an urgent problem to be solved in the field of secure and covert information transmission. Summary of the Invention

[0008] To solve the above problems, the present invention provides a secure and covert communication method, system, and medium based on an intelligent reflecting surface, which jointly considers physical layer security and covert communication to comprehensively improve the security performance of wireless communication.

[0009] To achieve the above object, the present invention provides the following technical solutions.

[0010] A secure and covert communication method based on an intelligent reflecting surface, comprising the following steps:

[0011] The transmitter emits a signal, the intelligent reflecting surface reflects the signal emitted by the transmitter, the receiver, the eavesdropper, and the wiretapper receive the signal emitted by the transmitter and the signal reflected by the intelligent reflecting surface; wherein, the receiver detects the useful signal emitted by the transmitter.

[0012] To achieve secure and covert communication, the maximum secure and covert transmission rate is used as the performance optimization metric, and the transmission power constraint and the covert transmission constraint are used as constraints to iteratively solve for the optimal IRS phase;

[0013] Among them, the secure rate is defined according to the channel capacities between the transmitter - receiver and the transmitter - eavesdropper; the maximum transmission power of the transmitter's transmitted signal is used as the transmission power constraint condition; the bounded uncertainty model is adopted to describe the noise of the eavesdropping party, and the detection probability of the eavesdropping party for the transmitter's transmitted signal being lower than a fixed value is used as the covert transmission constraint condition.

[0014] Preferably, the signals received by the receiver, eavesdropper, and eavesdropping party from the transmitter are respectively:

[0015]

[0016]

[0017]

[0018] Among them,

[0019]

[0020]

[0021]

[0022] In the formula, and are respectively the channel coefficients from the transmitter to the intelligent reflecting surface, receiver, eavesdropper, and eavesdropping party; and are respectively the channel coefficients from the transmitter directly to the receiver, eavesdropper, and eavesdropping party; is the diagonal phase shift matrix of Rose; θ l ∈[0, 2π) is the phase shift of the l-th element φ l of the incident signal, l = 1,..., L; s is the transmitted signal with distribution ; and are respectively the noises at the receiver, eavesdropper, and eavesdropping party; P is the transmission power of the transmitter.

[0023] Preferably, the secure and covert transmission rate is used as the performance optimization metric, and its definition is:

[0024] R s (Φ) = (R B (Φ) - R E (Φ)) +

[0025]

[0026] Among them, R B and R E are the channel capacities of the transmitter-receiver and the transmitter-listener, respectively.

[0027] Preferably, the bounded uncertainty model is used to describe the noise of the listener, and the detection probability of the listener for the signal sent by the transmitter is lower than a fixed value as the covert transmission constraint condition, including the following steps:

[0028] Use the bounded uncertainty model to describe the noise at the listener, and its probability density function PDF is:

[0029]

[0030] In the formula, ρ is a parameter quantifying the size of the uncertainty;

[0031] The test hypothesis of the listener is:

[0032]

[0033] Among them, H0 represents that the transmitter is in the silent state, and H1 represents that the transmitter is in the transmission state;

[0034] Determine the false alarm probability and the miss detection probability, which are respectively expressed as:

[0035]

[0036]

[0037] Let the detection error probability satisfy the condition:

[0038] ξ = P FA + P MD ≥ 1 - κ

[0039] Among them, κ is an arbitrarily small positive value; the detection error probability ξ is calculated as:

[0040]

[0041] To determine the threshold λ, let P|h w | 2 = t w and calculate the average detection error probability:

[0042]

[0043] For the listener, the optimal threshold λ * should take values between and between; after taking the partial derivative with respect to λ, we get:

[0044]

[0045] Then the optimal threshold is:

[0046]

[0047] Furthermore, the average detection error probability is obtained:

[0048]

[0049] Note that ξ≥1 - κ, when at this time

[0050] Then the threshold that the signal power received by the eavesdropper should satisfy is:

[0051]

[0052] Then the covert transmission constraint is:

[0053] P|h w | 2 ≤η.

[0054] Preferably, the iterative solution to obtain the optimal IRS phase includes the following steps:

[0055] The optimization problem is:

[0056]

[0057] s.t.P|h w | 2 ≤η

[0058] P≤P max

[0059] |φ l |=1, l = 1,..., L

[0060] When the IRS phase is given, combining the two power constraints, the optimal transmission power is:

[0061]

[0062] In the formula, P max is the maximum transmission power;

[0063] Substituting this into the optimization problem, then:

[0064]

[0065] s.t.P|h w |2 ≤ η

[0066] |φ l | = 1, l = 1, ..., L

[0067] Define t as an auxiliary variable, satisfying |t| 2 = 1, then the optimization problem is transformed into:

[0068]

[0069]

[0070]

[0071]

[0072] t1 > 0

[0073]

[0074]

[0075] Wherein:

[0076]

[0077]

[0078] For this problem, the optimal t1 is:

[0079]

[0080] After discarding the rank - 1 constraint, use the optimization tool CVX to solve;

[0081] Use the Gaussian randomization technique to map the obtained optimal solution to a feasible solution of the above - mentioned optimization problem as the final optimization result.

[0082] Preferably, the step of using the Gaussian randomization technique to map the obtained optimal solution to a feasible solution of the above - mentioned optimization problem as the final optimization result includes the following steps:

[0083] Decompose the eigenvalues of into where U is a unitary matrix and Σ is a diagonal matrix; the column vectors of U form an orthonormal basis and are the eigenvectors of

[0084] Let where Iteratively obtain a new one that satisfies the constraints Achieve the maximum secure and concealed transmission rate;

[0085] According to the corresponding Get the optimal φ H :

[0086]

[0087] Where [x] (1:L) represents a vector containing the first L elements of x.

[0088] A secure covert communication system based on an intelligent reflective surface, the system comprising:

[0089] processor;

[0090] a memory having stored thereon a computer program executable on the processor;

[0091] Wherein, when the computer program is executed by the processor, the steps of the secure and covert communication method based on the intelligent reflective surface are implemented.

[0092] A computer-readable storage medium stores a data processing program, and when the data processing program is executed by a processor, the steps of the secure covert communication method based on an intelligent reflective surface are implemented.

[0093] Beneficial effects of the present invention:

[0094] The present invention proposes a secure covert communication method, system and medium based on intelligent reflective surface, which synergistically considers physical layer security and covert communication to comprehensively improve the security performance of wireless communication. The method uses IRS to adjust the wireless transmission environment, and improves the security and covert rate of the system by jointly adjusting the transmission power and IRS phase without adding any additional energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] Figure 1 is an optimization flow chart of an embodiment of the present invention;

[0096] Figure 2 The rate of the security and concealment scenario in the embodiment of the present invention varies with P max Change curve;

[0097] Figure 3 The security concealment rate of the embodiment of the present invention varies with x B Change curve;

[0098] Figure 4 It is a system model of the embodiment of the present invention. DETAILED DESCRIPTION

[0099] To make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not used to limit the present invention.

[0100] Embodiment 1

[0101] The present invention proposes a secure and covert communication method based on an intelligent reflecting surface. The flowchart of the optimization process is as Figure 1 shown, and specifically includes the following steps:

[0102] The scenario of this embodiment is as Figure 4 shown. Consider a SISO system assisted by IRS (Rose) with a direct link existing. During the transmission, an eavesdropper (Eve) and a monitor (Willie) attempt to eavesdrop on and detect their communication process. Both Eve and Willie are equipped with a single antenna. The number of reflecting elements at Rose is denoted by L. First, assume that the CSI of all channels is known and all channels in the system undergo quasi-static flat fading.

[0103] The signals received by the receiver, the eavesdropper, and the monitor from the transmitter are respectively:

[0104]

[0105]

[0106]

[0107] where

[0108]

[0109]

[0110]

[0111] In the formula, and are respectively the channel coefficients from the transmitter to the intelligent reflecting surface, the receiver, the eavesdropper, and the monitor; and are respectively the channel coefficients from the transmitter directly to the receiver, the eavesdropper, and the monitor; is the diagonal phase shift matrix of Rose; θ l ∈[0, 2π) is the phase shift of the l-th element φ l of the incident signal, l = 1,..., L; s is the transmission signal with a distribution of ; and They are the noises at the receiver, eavesdropper, and monitoring party respectively; P is the transmission power of the transmitter.

[0112] The specific steps are as follows:

[0113] S1: The transmitter emits a signal, the intelligent reflecting surface reflects the signal emitted by the transmitter, the receiver, eavesdropper, and monitoring party receive the signal emitted by the transmitter and the signal reflected by the intelligent reflecting surface; among them, the receiver detects the useful signal emitted by the transmitter.

[0114] S2: To achieve secure and covert communication, taking the maximum secure and covert transmission rate as the performance optimization index, and taking the transmission power constraint and the covert transmission constraint as the constraint conditions, iteratively solve to obtain the optimal IRS phase.

[0115] Among them, the secure rate is defined according to the channel capacity between the transmitter - receiver and the transmitter - eavesdropper; taking the maximum transmission power of the signal emitted by the transmitter as the transmission power constraint condition; using a bounded uncertainty model to describe the noise of the monitoring party, and making the detection probability of the monitoring party for the signal sent by the transmitter lower than a fixed value as the covert transmission constraint condition.

[0116] (1) Taking the secure and covert transmission rate as the performance optimization index, its definition is:

[0117] R s (Φ)=(R B (Φ)-R E (Φ)) +

[0118]

[0119] Among them, R B and R E are the channel capacities between the transmitter - receiver and the transmitter - monitoring party respectively.

[0120] (2) Using a bounded uncertainty model to describe the noise of the monitoring party, and making the detection probability of the monitoring party for the signal sent by the transmitter lower than a fixed value as the covert transmission constraint condition, including the following steps:

[0121] Using a bounded uncertainty model to describe the noise at the monitoring party, and its probability density function PDF is:

[0122]

[0123] In the formula, ρ is the parameter quantifying the size of the uncertainty;

[0124] The test hypothesis of the monitoring party is:

[0125]

[0126] Among them, H0 indicates that the transmitter is in a silent state, and H1 indicates that the transmitter is in a transmission state;

[0127] Determine the false alarm probability and the miss detection probability, which are respectively expressed as:

[0128]

[0129]

[0130] Let the detection error probability satisfy the condition:

[0131] ξ = P FA + P MD ≥ 1 - κ

[0132] Among them, κ is an arbitrarily small positive value; the detection error probability ξ is calculated as:

[0133]

[0134] To determine the threshold λ, let P|h w | 2 = t w And calculate the average detection error probability:

[0135]

[0136] For the eavesdropper, the optimal threshold λ * should take values between and ; After taking the partial derivative of λ, we get:

[0137]

[0138] Then the optimal threshold is:

[0139]

[0140] Furthermore, the average detection error probability is obtained:

[0141]

[0142] Note that ξ ≥ 1 - κ, when ,

[0143] Then the threshold that the signal power received by the eavesdropper should satisfy is:

[0144]

[0145] Then the covert transmission constraint is:

[0146] P|h w | 2 ≤ η.

[0147] (3) Iteratively solve to obtain the optimal IRS phase, including the following steps:

[0148] The optimization problem is:

[0149]

[0150] s.t. P|h w | 2 ≤ η

[0151] P ≤ P max

[0152] |φ l | = 1, l = 1, …, L

[0153] When the IRS phase is given, combining the two power constraints, the optimal transmission power is:

[0154]

[0155] where P max is the maximum transmit power;

[0156] Substitute it into this optimization problem, then:

[0157]

[0158] s.t. P|h w | 2 ≤ η

[0159] |φ l | = 1, l = 1,..., L

[0160] Define t as an auxiliary variable, satisfying |t| 2 = 1, then the optimization problem is transformed into:

[0161]

[0162]

[0163]

[0164]

[0165] t1 > 0

[0166]

[0167]

[0168] where:

[0169]

[0170]

[0171] For this problem, the optimal t1 is:

[0172]

[0173] After discarding the rank 1 constraint, the optimization tool CVX is used to solve the problem;

[0174] Use Gaussian randomization technology to find the optimal solution Mapping to the feasible solution of the above optimization problem as the final optimization result includes the following steps:

[0175] Will The eigenvalue decomposition of where U is a unitary matrix, Σ is a diagonal matrix; the column vectors of U form a standard orthonormal basis, and are The eigenvectors of , and the diagonal elements of Σ are the corresponding eigenvalues;

[0176] set up in Iterate to obtain a new one that satisfies the constraints Achieve the maximum secure and concealed transmission rate;

[0177] According to the corresponding Get the optimal φ H :

[0178]

[0179] Where [x] (1:L) represents a vector containing the first L elements of x.

[0180] In this embodiment, a simulation diagram is used to demonstrate the impact of IRS on the SISO joint security covert communication system.

[0181] The positions of Alice, Rose, Bob, Eve and Willie are (x A ,y A ,z A ), (x R ,y R ,z R ), (x B ,y B ,z B ), (x E ,y E ,z E ) and (x W ,y W ,z W)。The distance d from node i to node j ij is defined as:

[0182]

[0183] Assume that Alice and the IRS are on the same horizontal plane, and the three receiving nodes are on the same horizontal plane. The vertical distance between the two planes is z R . The large-scale path loss is expressed as:

[0184]

[0185] where PL0 is the path loss at the reference distance d0 = 1m, d is the link distance, and "lg" represents the logarithm to the base 10. The path loss exponent is denoted by μ. In the simulation, PL0 = -30dB is set. The path loss exponents of the links from Alice to Bob, Eve, and Willie are denoted as μ AB , μ AE , μ AW , respectively. The path loss exponents of the links from the IRS to Bob, Eve, and Willie are denoted as μ RB , μ RE and μ RW , respectively. The path loss exponent of the link from Alice to the IRS is μ AR . Generally, it is assumed that the IRS is properly placed, so the path loss on this link can be ignored. The IRS is equipped with L = L y L z reflective elements. The iterative error tolerance threshold is defined as ε. The number of Gaussian randomizations is 1000.

[0186] Figure 2 Shows the comparison of the optimization method with the optimal phase for Bob, the random phase of the IRS, and the secure secrecy rate without the IRS in the scenario where both Willie and Eve exist. The positions of Alice, Rose, Bob, Eve, and Willie are (0,0,2), (0,28,2), (0,30,0), (0,35,0), and (0,40,0), respectively, and L y = L z = 8, μ AR = 2.5, μ AB = μ AE = μ AW = 4, μ RB = 2.5, μ RE = μ RW = 3, ρ = 3dB, κ = 0.01, ε = 10 -5 . It can be seen that the secure secrecy rate of the proposed algorithm at Pmax When it is small, it increases with the increase of P max , but flattens out when P max is large. This is because when P max is small, the transmission power is mainly limited by P max , while when P max is large, the transmission power is mainly limited by the secrecy constraint. Therefore, even if P max increases further, the actual transmission power remains basically unchanged. In addition, it can also be seen that the proposed optimized phase method is superior to the optimal phase for Bob, the random phase of IRS, and the case without IRS.

[0187] Figure 3 shows the comparison of the secure secrecy rate between the optimization method and the optimal phase for Bob and the random phase of IRS in the scenario where Willie and Eve exist simultaneously. The positions of Alice, Rose, Bob, Eve, and Willie are (0,0,3), (0,50,3), (0,30,0), (0,60,0), and (0,70,0) respectively, and L y =L z =8, μ AR =2, μ AB =μ AE =μ AW =4, μ RB =μ RE =μ RW =2.5, P max =-5dBm, ρ = 3dB, κ = 0.01, ε = 10 -5 . As can be seen from Figure 3 , with the increase of x B , the secure secrecy rate gradually decreases. This is because as the distance between Bob and other nodes increases, the signal attenuation becomes larger, the signal-to-noise ratio decreases, and thus Bob's channel capacity becomes smaller. In addition, the secure secrecy rate of the proposed optimized phase method is superior to the optimal phase for Bob and the random phase of IRS, verifying the effectiveness of the proposed method.

[0188] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A secure and covert communication method based on intelligent reflecting surface, characterized in that, It includes the following steps: A transmitter emits a signal, an intelligent reflecting surface reflects the signal emitted by the transmitter, a receiver, an eavesdropper, and a monitoring party receive the signal emitted by the transmitter, as well as the signal reflected by the intelligent reflecting surface; among them, the receiver detects the useful signal emitted by the transmitter. To achieve secure and covert communication, taking the maximum secure and covert transmission rate as the performance optimization index, and taking the transmission power constraint and the covert transmission constraint as the constraint conditions, iteratively solve to obtain the optimal IRS phase. Among them, the secure rate is defined according to the channel capacity between the transmitter and the receiver and between the transmitter and the eavesdropper; taking the maximum transmission power of the signal emitted by the transmitter as the transmission power constraint condition; using a bounded uncertainty model to describe the noise of the monitoring party, and making the detection probability of the monitoring party for the signal sent by the transmitter lower than a fixed value as the covert transmission constraint condition.

2. The secure and covert communication method based on intelligent reflecting surface according to claim 1, wherein The signals received by the receiver, the eavesdropper, and the monitoring party from the transmitter are respectively: Among them, wherein, and are the channel coefficients from the transmitter to the intelligent reflecting surface, the receiver, the eavesdropper, and the monitoring party, respectively; and are the channel coefficients from the transmitter directly to the receiver, the eavesdropper, and the monitoring party, respectively; is the diagonal phase shift matrix of Rose; θ l ∈ [0, 2π) is the phase shift of the l-th element φ of the incident signal l , l = 1, ..., L; s is the transmitted signal with a distribution of ; and are the noises at the receiver, the eavesdropper, and the monitoring party, respectively; P is the transmission power of the transmitter.

3. The method for secure and covert communication based on intelligent reflecting surface according to claim 2, wherein, The secure and covert transmission rate is used as the performance optimization index, and its definition is: R s (Φ) = (R B (Φ) - R E (Φ)) + where R B and R E are the channel capacities of the transmitter-receiver and the transmitter-listener, respectively.

4. The secure and covert communication method based on intelligent reflecting surface according to claim 3, characterized in that, The step of using a bounded uncertainty model to describe the noise of the monitoring party and making the detection probability of the monitoring party for the signal sent by the transmitter lower than a fixed value as the covert transmission constraint condition includes the following steps: Use a bounded uncertainty model to describe the noise at the monitoring party, and its probability density function PDF is: In the formula, ρ is a parameter quantifying the size of the uncertainty; The test hypothesis of the monitoring party is: Among them, H0 represents that the transmitter is in a silent state, and H1 represents that the transmitter is in a transmission state; Determine the false alarm probability and the miss detection probability, which are respectively expressed as: Let the detection error probability satisfy the condition: ξ = P FA + P MD ≥ 1 - κ Among them, κ is an arbitrarily small positive value; the detection error probability ξ is calculated as: To determine the threshold λ, let P|h w | 2 = t w and calculate the average detection error probability: For the listener, the optimal threshold λ * should take values between and ; After taking the partial derivative of λ, we get: Then the optimal threshold is: Furthermore, the average detection error probability is obtained: Note that ξ ≥ 1 - κ, when time Then the threshold that the signal power received by the monitoring party should satisfy is: Then the covert transmission constraint is: P|h w | 2 ≤ η。 5. The method for secure and covert communication based on intelligent reflecting surface according to claim 4, characterized in that The step of iteratively solving to obtain the optimal IRS phase includes the following steps: The optimization problem is: s.t.P|h w | 2 ≤η P≤P max |φ l | = 1, l = 1, ..., L When a given IRS phase is given, combining the two power constraints, the optimal transmission power is: Where P max is the maximum transmission power; Substitute it into this optimization problem, then: s.t.P|h w | 2 ≤η |φ l | = 1, l = 1, ..., L Definition Let \(t\) be an auxiliary variable satisfying \(|t| 2 = 1\), then the optimization problem is transformed into: t1>0 Among them: For this problem, the optimal t1 is: After discarding the rank-1 constraint, use the optimization tool CVX to solve; Use the Gaussian randomization technique to map the optimal solution sought to a feasible solution of the above optimization problem as the final optimization result.

6. The method for secure and covert communication based on intelligent reflecting surface according to claim 5, characterized in that Mapping the optimal solution to be obtained to a feasible solution of the above optimization problem by using the Gaussian randomization technique as the final optimization result, including the following steps: ​ Decompose the eigenvalue of into where U is a unitary matrix and Σ is a diagonal matrix; the column vectors of U form an orthonormal basis and are eigenvectors of , and the diagonal elements of Σ are the corresponding eigenvalues; Set wherein Iteratively obtain a new one that satisfies the constraints Achieve the maximum secure and covert transmission rate; According to the corresponding obtain the optimal φ H : where, [x] (1:L) denotes a vector containing the first L elements in x.

7. A secure and covert communication system based on intelligent reflecting surface, characterized in that, The system includes: A processor; A memory, on which a computer program that can run on the processor is stored; Among them, when the computer program is executed by the processor, it implements the steps of the secure and covert communication method based on an intelligent reflecting surface as described in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, A data processing program is stored on the computer-readable storage medium, and when the data processing program is executed by the processor, it implements the steps of the secure and covert communication method based on an intelligent reflecting surface as described in any one of claims 1 to 6.

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