A Method for Predicting the Cybersecurity Performance of STAR-RIS Networks under Active Eavesdropping

Abstract

The present invention relates to the field of communication security technology, and discloses a method, system, device and medium for predicting the security performance of a STAR-RIS network under active eavesdropping. A STAR-RIS network model under active eavesdropping is constructed; a first legitimate signal received by a legitimate user and a second legitimate signal eavesdropped by an active eavesdropping user are obtained; the signal-to-noise ratios of the first legitimate signal and the second legitimate signal are determined; the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel are obtained by using the gamma distribution; the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal are obtained; the probability of security outage of the STAR-RIS network under active eavesdropping is obtained to realize the prediction of the security performance of the STAR-RIS network.

Description

Technical Field

[0001] The present invention relates to the field of network security technology, and particularly relates to a method, system, device and medium for predicting the security performance of a STAR-RIS network under active eavesdropping. Background Art

[0002] Reconfigurable Intelligent Surface (RIS) has high spectral and energy efficiency and is considered one of the key technologies for the sixth-generation mobile communication system. Traditional RIS only has a reflection function and cannot serve users located behind the RIS, only achieving semi-coverage. For this reason, a RIS that can simultaneously transmit and reflect (Simultaneous Transmitting And Reflecting, STAR) has been proposed. STAR-RIS can serve users located behind the RIS through transmission, thus achieving full coverage.

[0003] To improve network security, STAR-RIS is introduced into the wireless network. There may be eavesdroppers in the STAR-RIS network, which affects the security performance of the STAR-RIS network. However, only the case of passive eavesdroppers is considered in the current STAR-RIS network. In the actual network, there are often active eavesdroppers. Different from passive eavesdroppers who can only passively eavesdrop on information, active eavesdroppers will actively send interference information to disrupt legitimate communication while eavesdropping on information, and their security threat is greater. Therefore, it is particularly important to predict the security performance of the STAR-RIS network under active eavesdropping. Summary of the Invention

[0004] The purpose of the present invention is to provide a method, system, device and medium for predicting the security performance of a STAR-RIS network under active eavesdropping, so as to realize the prediction of the security performance of the STAR-RIS network under active eavesdropping.

[0005] To solve the above technical problems, an embodiment of the present invention provides a method for predicting the security performance of a STAR-RIS network under active eavesdropping. The STAR-RIS network under active eavesdropping includes: a base station, a legitimate user, an active eavesdropping user, and a STAR-RIS device having a plurality of transmission units and a plurality of reflection units; the active eavesdropping user and the base station are on the same side of the STAR-RIS device, the active eavesdropping user is directly connected to the base station, the legitimate user is on the other side of the STAR-RIS device, and the legitimate user is connected to the base station through the STAR-RIS device;

[0006] Among them, legitimate users are used to receive legitimate signals sent by the base station through the STAR-RIS device. Active eavesdropping users are used to eavesdrop on and interfere with the legitimate signals sent by the base station to legitimate users. The STAR-RIS device is used to enhance the legitimate channel for legitimate users to receive legitimate signals and weaken the eavesdropping channel for active eavesdropping users to eavesdrop on legitimate signals;

[0007] The method includes:

[0008] Respectively obtain the first legitimate signal received by the legitimate user and the second legitimate signal eavesdropped by the active eavesdropping user in the STAR-RIS network under active eavesdropping, and determine the signal-to-noise ratios of the first legitimate signal and the second legitimate signal respectively through the phases of the transmission unit and the reflection unit in the STAR-RIS;

[0009] According to the signal-to-noise ratios of the first legitimate signal and the second legitimate signal, adopt the gamma distribution to obtain the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel;

[0010] According to the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel, and the relationship between the signal-to-noise ratio and the equivalent channel gain, respectively obtain the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal;

[0011] According to the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal, obtain a closed expression for the security outage probability of the STAR-RIS network under active eavesdropping, so as to predict the security performance of the STAR-RIS network under active eavesdropping through the closed expression of the security outage probability of the STAR-RIS network.

[0012] In some alternative embodiments, the first legitimate signal received by the legitimate user is:

[0013]

[0014] The second legitimate signal eavesdropped by the active eavesdropping user is:

[0015]

[0016] In the formula, P A and P J respectively represent the transmission powers of the base station and the active eavesdropping user, x A represents the legitimate signal sent by the base station, x J is the interference signal sent by the active eavesdropping user, x A and x J are preset energy-normalized signals, h an 、h nb 、h ne and h ae respectively represent A→Rn Link, R n →B Link, R n Complex channel coefficients of the →E link and the A→E link, where A represents the base station, B represents the legitimate user, E represents the active eavesdropping user, and R n represents the nth reflection / transmission unit in the STAR-RIS device, N represents the total number of STAR-RIS reflection and transmission units, and the complex channel coefficient h an , h nb , h ne and h ae all follow the Nakagami-m random distribution with shape factors and spread factors of (m ar , Ω ar ), (m rb , Ω rb ), (m re , Ω re ), and (m ae , Ω ae ), respectively. j 2 = -1 represents the imaginary unit, θ t,n ∈ [0, 2π) and θ r,n ∈ [0, 2π) represent the phases of the nth transmission unit and reflection unit, respectively. N t and N r represent the numbers of transmission units and reflection units, respectively, and N t +N r = N. η ∈ [0, 1] represents the ratio of the interference power caused by the active eavesdropping user's full-duplex communication to its own interference to the transmission power P J of the active eavesdropping user. n b and n e represent the noises when the legitimate user receives the legitimate signal and the active eavesdropping user eavesdrops on the legitimate signal, respectively. The noise powers of n b and n e are both N0.

[0017] In some alternative embodiments, the phase of the transmission unit in the STAR-RIS device is:

[0018]

[0019] The phase of the reflection unit in the STAR-RIS device is:

[0020]

[0021] The signal-to-noise ratio of the first legitimate signal is:

[0022]

[0023] The signal-to-noise ratio of the second legal signal is:

[0024]

[0025] In the formula, ∠h an , ∠h nb , ∠h ne and ∠h ae respectively represent the phases of the complex channel coefficients h an , h nb , h ne and h ae . |h an |, |h nb |, |h ne |and |h ae | respectively represent the amplitudes of the complex channel coefficients h an , h nb , h ne and h ae . γ = P A / N0 represents the average signal-to-noise ratio of the base station, and γ J = P J / N0 represents the average interference-to-noise ratio of the active eavesdropping user. is the equivalent channel gain of the legitimate channel. is the equivalent channel gain of the interference channel when the active eavesdropping user interferes with the legitimate user. is the equivalent channel gain of the eavesdropping channel. Y follows an exponential distribution, and the probability density function of Y is

[0026] In some alternative embodiments, the probability density function of the equivalent channel gain of the legitimate channel is:

[0027]

[0028] The probability density function of the equivalent channel gain Z of the eavesdropping channel is:

[0029]

[0030] In the formula, represents the gamma function. is the inverse scale parameter of X. is the shape parameter of X. is the inverse scale parameter of Z. is the shape parameter of Z. μ X (k) represents the k-th moment of X, and μ Z (k) represents the k-th moment of Z;

[0031] μ X (k) and μZ (k) are respectively expressed as:

[0032]

[0033] In the formula,

[0034] In some alternative embodiments, the signal-to-noise ratio γ of the first legitimate signal b has a probability density function of:

[0035]

[0036] The signal-to-noise ratio γ of the second legitimate signal e has a probability density function of:

[0037]

[0038] In the formula,

[0039] In some alternative embodiments, the security outage probability of the STAR-RIS network under active eavesdropping is represented by the probability that the security rate C s of the STAR-RIS network is lower than a predetermined security rate R;

[0040] The security rate of the STAR-RIS network is:

[0041] C s (γ b , γ e ) = (log2(1 + γ b ) - log2(1 + γ e )) + ;

[0042] In the formula, (x) + = max(x, 0) represents taking the maximum value of x and 0;

[0043] The security outage probability of the STAR-RIS network under active eavesdropping is approximately expressed as:

[0044]

[0045] In the formula, Pr[·] represents the security outage probability, and δ = 2 R is the preset threshold for security outage;

[0046] Substitute the probability density functions of γ b and γ e into it, and integrate with respect to γ b to obtain:

[0047]

[0048] Make a variable substitution After that, the security outage probability of the STAR-RIS network under active eavesdropping is as follows:

[0049]

[0050] In the formula, Ψ(·,·;·) is the Tricomi confluent hypergeometric function.

[0051] An embodiment of the present invention also provides a security outage prediction system for the STAR-RIS network under active eavesdropping. The STAR-RIS network under active eavesdropping includes: a base station, a legitimate user, an active eavesdropping user, and a STAR-RIS device with multiple transmission units and multiple reflection units; the active eavesdropping user and the base station are on the same side of the STAR-RIS device, the active eavesdropping user is directly connected to the base station, the legitimate user is on the other side of the STAR-RIS, and the legitimate user is connected to the base station through the STAR-RIS device;

[0052] Among them, the legitimate user is used to receive the legitimate signal sent by the base station through the STAR-RIS device, the active eavesdropping user is used to eavesdrop on and interfere with the legitimate signal sent by the base station to the legitimate user, and the STAR-RIS device is used to enhance the legitimate channel for the legitimate user to receive the legitimate signal and weaken the eavesdropping channel for the active eavesdropping user to eavesdrop on the legitimate signal;

[0053] The system includes:

[0054] A signal-to-noise ratio acquisition module, configured to respectively acquire the first legitimate signal received by the legitimate user and the second legitimate signal eavesdropped by the active eavesdropping user in the STAR-RIS network under active eavesdropping, and respectively determine the signal-to-noise ratios of the first legitimate signal and the second legitimate signal through the phases of the transmission unit and the reflection unit in the STAR-RIS;

[0055] A first function construction module, configured to obtain the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel by using the gamma distribution according to the signal-to-noise ratios of the first legitimate signal and the second legitimate signal;

[0056] A second function construction module, configured to respectively obtain the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal according to the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel, and the relationship between the signal-to-noise ratio and the equivalent channel gain;

[0057] A security performance prediction module, which is used to obtain a closed-form expression of the security outage probability of the STAR-RIS network under active eavesdropping according to the probability density function of the signal-to-noise ratio of the first legitimate signal and the second legitimate signal, so as to predict the security performance of the STAR-RIS network under active eavesdropping through the closed-form expression of the security outage probability of the STAR-RIS network.

[0058] An embodiment of the present invention also provides a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, instructions executable by the at least one processor are stored in the memory, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the above-mentioned method for predicting the security performance of the STAR-RIS network under active eavesdropping.

[0059] An embodiment of the present invention also provides a computer-readable storage medium, storing a computer program, and when the computer program is executed by a processor, the above-mentioned method for predicting the security performance of the STAR-RIS network under active eavesdropping is implemented.

[0060] The method for predicting the security performance of the STAR-RIS network under active eavesdropping provided by the present invention has at least the following beneficial effects:

[0061] The present invention takes into account the active eavesdroppers with greater security threats in the STAR-RIS network. Therefore, according to the STAR-RIS network including a base station, legitimate users, active eavesdropping users, and STAR-RIS devices, by obtaining the legitimate signals received by the legitimate users and the legitimate signals eavesdropped by the active eavesdropping users, the signal-to-noise ratios of the respective corresponding links are determined, and then the probability distributions of the equivalent channel gains of the respective corresponding links and the probability distributions of the signal-to-noise ratios of the respective corresponding links are obtained. Finally, a closed-form expression of the security outage probability of the STAR-RIS network is determined through the probability distribution of the link signal-to-noise ratio, so as to characterize the security performance of the STAR-RIS network.

[0062] Because the security outage probability refers to the performance index of the system when the legitimate users cannot safely receive information at a predetermined rate, the closed-form expression of the security outage probability can be used to predict the security outage probability of the STAR-RIS network under different network configurations, eavesdropper strategies, and system parameters, thus effectively realizing the prediction of the security performance of the STAR-RIS network under active eavesdropping. Description of the Drawings

[0063] One or more embodiments are illustrated by way of example in the pictures in the corresponding drawings, and these exemplary illustrations do not limit the embodiments.

[0064] Figure 1A schematic diagram of a STAR - RIS network under active eavesdropping provided according to an embodiment of the present invention;

[0065] Figure 2 A flowchart of a method for predicting the security performance of a STAR - RIS network under active eavesdropping provided according to an embodiment of the present invention;

[0066] Figure 3 A curve schematic diagram of the theoretical value and simulation value of the security outage probability provided according to an embodiment of the present invention Figure 1 ;

[0067] Figure 4 A curve schematic diagram of the theoretical value and simulation value of the security outage probability provided according to an embodiment of the present invention Figure 2 。 Detailed implementation manners

[0068] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, those of ordinary skill in the art can understand that in the embodiments of the present invention, many technical details are presented for the readers to better understand the present invention. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions required to be protected by the present invention can still be implemented. The division of the following embodiments is for convenience of description and should not constitute any limitation on the specific implementation manner of the present invention. The various embodiments can be combined and cross - referenced with each other on the premise of no contradiction.

[0069] An embodiment of the present invention relates to a method for predicting the security performance of a STAR - RIS network under active eavesdropping. The structure of the STAR - RIS network under active eavesdropping in this embodiment is as Figure 1 shown, including: a base station Alice (A), a legitimate user Bob (B), an active eavesdropping user Eve (E), and a STAR - RIS device with multiple reflection units and multiple transmission units. Eve is located in the reflection area (on the same side) of the STAR - RIS device, while Bob is located in the transmission area (on the back) of the STAR - RIS device. In this embodiment, it is assumed that the direct link between Alice and Bob is blocked, while there is a direct link between Alice and Eve, that is, the active eavesdropping user is directly connected to the base station, and the legitimate user is connected to the base station through the STAR - RIS device.

[0070] Among them, the legitimate user is used to receive the legitimate signal sent by the base station through the STAR - RIS device. The active eavesdropping user is used to eavesdrop on and interfere with the legitimate signal sent by the base station to the legitimate user. The STAR - RIS device is used to enhance the legitimate channel for the legitimate user to receive the legitimate signal and weaken the eavesdropping channel for the active eavesdropping user to eavesdrop on the legitimate signal.

[0071] Both the base station and the legitimate user are configured with a single antenna, while the active eavesdropping user is configured with two antennas and operates in full-duplex mode. One antenna is used for passive eavesdropping of legitimate information, and at the same time, the other antenna is used for actively transmitting interference information to disrupt legitimate communication. The number of transmission units and reflection units in the STAR-RIS device is N, and the nth reflection unit / transmission unit of the STAR-RIS device is denoted as R n , Use h an , h ae , h ne and h nb to represent the complex channel coefficients of the A→R n link, A→E link, R n →E link, and R n →B link, respectively. The complex channel coefficients of all links: h an , h ae , h ne and h nb , follow the Nakagami-m random distribution with shape factors and spread factors of (m ar , Ω ar ), (m rb , Ω rb ), (m re , Ω re ), and (m ae , Ω ae ), respectively.

[0072] The implementation details of the STAR-RIS network security performance prediction method under active eavesdropping in this embodiment are specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing this solution.

[0073] The specific process of the STAR-RIS network security performance prediction method under active eavesdropping in this embodiment can be as Figure 2 shown and includes:

[0074] Step 201: Respectively obtain the first legitimate signal received by the legitimate user and the second legitimate signal eavesdropped by the active eavesdropping user in the STAR-RIS network under active eavesdropping, and determine the signal-to-noise ratios of the first legitimate signal and the second legitimate signal through the phases of the transmission units and reflection units in the STAR-RIS.

[0075] Referring to the STAR-RIS network architecture as Figure 1 shown, the first legitimate signal received by the legitimate user is:

[0076]

[0077] The second legitimate signal eavesdropped by the active eavesdropper is:

[0078]

[0079] where P A and P J represent the transmit powers of the base station and the active eavesdropper respectively, x A represents the legitimate signal transmitted by the base station, x J is the interference signal transmitted by the active eavesdropper, x A and x J are pre-set energy-normalized signals, h an , h nb , h ne and h ae represent the complex channel coefficients of the A→R n link, R n →B link, R n →E link and A→E link respectively. A represents the base station, B represents the legitimate user, E represents the active eavesdropper, and R n represents the nth reflection / transmission unit in the STAR-RIS device, N represents the total number of STAR-RIS reflection and transmission units. The complex channel coefficients h an , h nb , h ne and h ae all follow the Nakagami-m random distribution with shape factors and spread factors of (m ar ,Ω ar ), (m rb ,Ω rb ), (m re ,Ω re ) and (m ae ,Ω ae ) respectively. j 2 =-1 represents the imaginary number, θ t,n ∈[0,2π) and θ r,n ∈[0,2π) represent the phases of the nth transmission unit and reflection unit respectively. N t and N r represent the numbers of transmission units and reflection units respectively, and N t +N r =N. η∈[0,1] represents the ratio of the interference power caused by the active eavesdropper using full-duplex communication to its own interference to the transmit power P J of the active eavesdropper. n b and n e represent the noises when the legitimate user receives the legitimate signal and the active eavesdropper eavesdrops on the legitimate signal respectively. n b and ne The noise power of both is N0.

[0080] In a specific implementation, to simultaneously enhance the received signal of the legitimate user B (i.e., the first legitimate signal) and suppress the received signal of the active eavesdropping user E (i.e., the second legitimate signal), the phase values of the transmission unit and the reflection unit in the STAR-RIS device are respectively:

[0081]

[0082] At this time, the signal-to-noise ratios of the received signals of B and E can be expressed as:

[0083]

[0084] In the formula, ∠h an , ∠h nb , ∠h ne and ∠h ae respectively represent the phases of the complex channel coefficients h an , h nb , h ne and h ae , |h an |, |h nb |, |h ne | and |h ae respectively represent the amplitudes of the complex channel coefficients h an , h nb , h ne and h ae , γ = P A / N0 represents the average signal-to-noise ratio of the base station, γ J = P J / N0 represents the average interference noise ratio of the active eavesdropping user, is the equivalent channel gain of the legitimate channel, is the equivalent channel gain of the interference channel when the active eavesdropping user interferes with the legitimate user, is the equivalent channel gain of the eavesdropping channel, Y follows an exponential distribution, and the probability density function of Y is

[0085] Step 202: According to the signal-to-noise ratios of the first legitimate signal and the second legitimate signal, use the gamma distribution to obtain the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel.

[0086] Specifically, use the gamma distribution to approximate the equivalent channel gain X of the legitimate channel and the equivalent channel gain Z of the eavesdropping channel respectively, and obtain the probability density function of the equivalent channel gain of the legitimate channel as:

[0087]

[0088] The probability density function of the equivalent channel gain \(Z\) of the eavesdropping channel is as follows:

[0089]

[0090] wherein, represents the gamma function, is the inverse scale parameter of \(X\), is the shape parameter of \(X\), is the inverse scale parameter of \(Z\), is the shape parameter of \(Z\), \(\mu\) X \(\mu_{X}(k)\) represents the \(k\)-th moment of \(X\), \(\mu\) Z \(\mu_{Z}(k)\) represents the \(k\)-th moment of \(Z\);

[0091] \(\mu\) X \(\mu_{X}(k)\) and \(\mu\) Z \(\mu_{Z}(k)\) are respectively expressed as:

[0092]

[0093] wherein,

[0094] Step 203: According to the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel, and the relationship between the signal-to-noise ratio and the equivalent channel gain, respectively obtain the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal.

[0095] Among them, the probability density function of the signal-to-noise ratio \(\gamma_{1}\) of the first legitimate signal b is as follows:

[0096]

[0097] The probability density function of the signal-to-noise ratio \(\gamma_{2}\) of the second legitimate signal e is as follows:

[0098]

[0099] wherein,

[0100] Step 204: According to the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal, obtain a closed-form expression for the security outage probability of the STAR-RIS network under active eavesdropping, so as to predict the security performance of the STAR-RIS network under active eavesdropping through the closed-form expression of the security outage probability of the STAR-RIS network.

[0101] Specifically, the security rate is the maximum information rate at which secure communication can be maintained between legitimate transceiver nodes, and is defined as the legitimate user channel capacity \(C_{1}\) b and the eavesdropping user channel capacity \(C_{2}\)e is the difference, while the security outage probability of the STAR-RIS network under active eavesdropping is represented by the probability that the security rate C of the STAR-RIS network s is lower than the predetermined security rate R.

[0102] The security rate C of the STAR-RIS network s can be expressed as:

[0103] C s (γ b ,γ e ) = (C b -C e ) + = (log2(1 + γ b ) - log2(1 + γ e )) + ;

[0104] where (x) + = max(x, 0) represents taking the maximum value of the variable x and 0.

[0105] The security outage probability of the STAR-RIS network under active eavesdropping is approximately expressed as:

[0106]

[0107] where Pr[·] represents the security outage probability, and δ = 2 R is the preset threshold value for security outage.

[0108] Substitute the probability density functions of γ b and γ e into the approximate expression of the security outage probability, and integrate with respect to γ b to obtain the SOP expression:

[0109]

[0110] Make a variable substitution to derive the final SOP expression (i.e., the closed-form expression of the security outage probability of the STAR-RIS network):

[0111]

[0112] where Ψ(·,·;·) is the Tricomi confluent hypergeometric function.

[0113] In one example, the following simulation verification is performed on the theoretical expression of the security outage probability, and the simulation parameters are set as follows: For a two-dimensional planar network topology, the coordinates of Alice, Bob, STAR-RIS, and Eve are (0, 0), (10, 0), (Rx, Ry), and (6, 2) respectively. The relationship between the complex channel extension factor and the path loss is: and where d ar 、d rb 、d re and d ae are the distances between Alice and STAR-RIS, STAR-RIS and Bob, STAR-RIS and Eve, and Alice and Eve respectively. τ ar =τ rb =τ re =τ ae =2 is the path loss factor. Rx = 8, Ry = 0, m ar =m rb =2, m ae =m re =1, N = 100, γ = 10dB, R = 0.1bps / Hz, η = 0.1.

[0114] Figure 3 This is the curve graph of the theoretical value and the simulation value of the security outage probability when the number of transmission units of STRAT-RIS in this embodiment changes. It can be found from the figure that the theoretical value and the simulation value match perfectly, which proves the correctness and accuracy of the theoretical expression of the present invention. In addition, the results in the figure also show that the security outage probability increases with the increase of γ J , because the larger γ J is, the greater the interference of the active eavesdropping user to the legitimate user. In addition, fixing the interference noise ratio γ J , the security outage probability will increase with the increase of the number of transmission units of STRAT-RIS. This is because the more the number of transmission units, the larger the received signal-to-noise ratio of Bob will be. This shows that the security of the system can be guaranteed by increasing the number of transmission units of STRAT-RIS to counter the active eavesdropper.

[0115] Figure 4It is a curve graph of the theoretical value and simulation value of the secure outage probability when the coordinates of STRAT-RIS change in the embodiment. Three ways of coordinate change of STRAT-RIS are considered in the graph: 1) changing along the x-axis between B and E; 2) changing along the upper semi-circular arc with the center at (8, 0) and a radius of 2; 3) changing along the lower semi-circular arc with the center at (8, 0) and a radius of 2. It can be seen from the graph that when STAR-RIS is located at the coordinates (9.9, 0), (9.9, 0.6) and (9.3, 1.5) respectively, the secure outage probability of the system under the corresponding mode reaches the minimum. This is because when the coordinates of STRAT-RIS are located at the above positions respectively, STRAT-RIS can meet the dual conditions of being the closest to B and the farthest from E under the corresponding mode. This provides theoretical guidance for the optimal placement position of STAR-RIS in the actual network.

[0116] In this embodiment, considering that there are active eavesdroppers with greater security threats in the STAR-RIS network, therefore, according to the STAR-RIS network including a base station, legitimate users, active eavesdropping users and STAR-RIS devices, by obtaining the legitimate signals received by the legitimate users and the legitimate signals eavesdropped by the active eavesdropping users, the signal-to-noise ratios of the respective corresponding links are determined, and then the probability distributions of the equivalent channel gains of the respective corresponding links and the probability distributions of the signal-to-noise ratios of the respective corresponding links are obtained. Finally, a closed expression of the secure outage probability of the STAR-RIS network is determined through the probability distribution of the link signal-to-noise ratio, so as to characterize the security performance of the STAR-RIS network. Because the secure outage probability refers to the performance index of the system when the legitimate users cannot safely receive information at a predetermined rate, through the closed expression of the secure outage probability, the secure outage probability of the STAR-RIS network under different network configurations, eavesdropper strategies and system parameters can be predicted, thus effectively realizing the prediction of the security performance of the STAR-RIS network under active eavesdropping.

[0117] The step division of the above various methods is only for clear description. When implemented, they can be combined into one step or some steps can be split into multiple steps. As long as they include the same logical relationship, they are all within the protection scope of the present invention; adding insignificant modifications to the algorithm or process or introducing insignificant designs, but not changing the core design of its algorithm and process are all within the protection scope of the invention.

[0118] Another embodiment of the present invention relates to a system for predicting the security performance of a STAR-RIS network under active eavesdropping. The implementation details of the system for predicting the security performance of the STAR-RIS network under active eavesdropping in this embodiment are specifically described below. The following content is only implementation details provided for convenient understanding and is not necessary for implementing this solution.

[0119] The STAR-RIS network under active eavesdropping in this embodiment includes: a base station, a legitimate user, an active eavesdropping user, and a STAR-RIS device with multiple transmission units and multiple reflection units; the active eavesdropping user and the base station are on the same side of the STAR-RIS device, the active eavesdropping user is directly connected to the base station, the legitimate user is on the other side of the STAR-RIS, and the legitimate user is connected to the base station through the STAR-RIS device.

[0120] Among them, the legitimate user is used to receive the legitimate signal sent by the base station through the STAR-RIS device, the active eavesdropping user is used to eavesdrop on and interfere with the legitimate signal sent by the base station to the legitimate user, and the STAR-RIS device is used to enhance the legitimate channel for the legitimate user to receive the legitimate signal and weaken the eavesdropping channel for the active eavesdropping user to eavesdrop on the legitimate signal.

[0121] The security performance prediction system of the STAR-RIS network under active eavesdropping in this embodiment includes:

[0122] A signal-to-noise ratio acquisition module, which is used to respectively acquire the first legitimate signal received by the legitimate user and the second legitimate signal eavesdropped by the active eavesdropping user in the STAR-RIS network under active eavesdropping, and respectively determine the signal-to-noise ratios of the first legitimate signal and the second legitimate signal through the phases of the transmission unit and the reflection unit in the STAR-RIS.

[0123] A first function construction module, which is used to obtain the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel by using the gamma distribution according to the signal-to-noise ratios of the first legitimate signal and the second legitimate signal.

[0124] A second function construction module, which is used to respectively obtain the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal according to the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel, and the relationship between the signal-to-noise ratio and the equivalent channel gain.

[0125] A security performance prediction module, which is used to obtain a closed-form expression of the security outage probability of the STAR-RIS network under active eavesdropping according to the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal, so as to predict the security performance of the STAR-RIS network under active eavesdropping through the closed-form expression of the security outage probability of the STAR-RIS network.

[0126] It is not difficult to find that this embodiment is a system embodiment corresponding to the above method embodiment, and this embodiment can be implemented in cooperation with the above method embodiment. The relevant technical details and technical effects mentioned in the above embodiment are still valid in this embodiment. To avoid repetition, they are not elaborated here. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied to the above embodiment.

[0127] It is worth mentioning that each module involved in this embodiment is a logical module. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or can be implemented by a combination of multiple physical units. In addition, to highlight the innovative part of the present invention, units not closely related to solving the technical problems proposed by the present invention are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

[0128] Another embodiment of the present invention relates to a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the active eavesdropping STAR-RIS network security performance prediction method in the above embodiments.

[0129] Among them, the memory and the processor are connected by a bus. The bus can include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and the memory together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, so they will not be further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, and provides a unit for communicating with various other devices on the transmission medium. The data processed by the processor is transmitted on the wireless medium through the antenna. Further, the antenna also receives data and transmits the data to the processor.

[0130] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interface, voltage regulation, power management, and other control functions. The memory can be used to store data used by the processor when executing operations.

[0131] Another embodiment of the present invention relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the above method embodiments are implemented.

[0132] That is, those skilled in the art can understand that all or part of the steps in the methods of the above embodiments can be completed by instructing relevant hardware through a program. The program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0133] Those of ordinary skill in the art can understand that the above embodiments are specific embodiments for implementing the present invention, and in practical applications, various changes can be made to them in form and details without departing from the spirit and scope of the present invention.

Claims

1. A method for predicting the security performance of STAR-RIS networks under active eavesdropping, characterized in that, The STAR-RIS network under active eavesdropping includes: a base station, legitimate users, an active eavesdropping user, and a STAR-RIS device with multiple transmission units and multiple reflection units; the active eavesdropping user and the base station are on the same side of the STAR-RIS device, the active eavesdropping user is directly connected to the base station, the legitimate users are on the other side of the STAR-RIS device, and the legitimate users are connected to the base station through the STAR-RIS device; Among them, the legitimate users are used to receive the legitimate signals sent by the base station through the STAR-RIS device, the active eavesdropping user is used to eavesdrop on and interfere with the legitimate signals sent by the base station to the legitimate users, and the STAR-RIS device is used to enhance the legitimate channel for the legitimate users to receive the legitimate signals and weaken the eavesdropping channel for the active eavesdropping user to eavesdrop on the legitimate signals; The method includes: Respectively obtain the first legitimate signal received by the legitimate users and the second legitimate signal eavesdropped by the active eavesdropping user in the STAR-RIS network under active eavesdropping, and determine the signal-to-noise ratios of the first legitimate signal and the second legitimate signal respectively through the phases of the transmission units and reflection units in the STAR-RIS; According to the signal-to-noise ratios of the first legitimate signal and the second legitimate signal, use the gamma distribution to obtain the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel; According to the probability density functions of the equivalent channel gains of the legitimate channel and the eavesdropping channel, and the relationship between the signal-to-noise ratio and the equivalent channel gain, respectively obtain the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal; According to the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal, obtain a closed-form expression for the security outage probability of the STAR-RIS network under active eavesdropping, so as to predict the security performance of the STAR-RIS network under active eavesdropping through the closed-form expression of the security outage probability of the STAR-RIS network; Among them, the first legitimate signal received by the legitimate users is: The second legitimate signal eavesdropped by the active eavesdropping user is: Where, P A and P J represent the transmission powers of the base station and the active eavesdropping user respectively, x A represents the legitimate signal sent by the base station, x J is the interference signal sent by the active eavesdropping user, x A and x J are preset energy-normalized signals, h an , h nb , h ne and h ae represent the complex channel coefficients of the A→R n link, R n →B link, R n →E link and A→E link respectively. A represents the base station, B represents the legitimate user, E represents the active eavesdropping user, and R n represents the nth reflection / transmission unit of the STAR-RIS, N represents the total number of reflection and transmission units in the STAR-RIS device. The complex channel coefficients h an , h nb , h ne and h ae all follow the Nakagami-m random distribution with shape factors and spread factors of (m ar , Ω ar ), (m rb , Ω rb ), (m re , Ω re ) and (m ae , Ω ae ) respectively. j 2 = -1 represents the imaginary number, θ t,n ∈ [0, 2π) and θ r,n ∈ [0, 2π) represent the phases of the nth transmission unit and reflection unit respectively. N t and N r represent the numbers of transmission units and reflection units respectively, and N t +N r = N. η ∈ [0, 1] represents the ratio of the interference power caused by the active eavesdropping user using full-duplex communication to its own interference to the transmission power P J of the active eavesdropping user. n b and n e represent the noises when the legitimate user receives the legitimate signal and the active eavesdropping user eavesdrops on the legitimate signal respectively. The noise powers of n b and n e are both N0; The phase of the transmission unit in the STAR-RIS device is: The phase of the reflection unit in the STAR-RIS device is: The signal-to-noise ratio of the first legitimate signal is: The signal-to-noise ratio of the second legitimate signal is: where ∠h an , ∠h nb , ∠h ne and ∠h ae respectively represent the phases of the complex channel coefficients h an , h nb , h ne and h ae ; |h an |, |h nb |, |h ne |and |h ae |respectively represent the magnitudes of the complex channel coefficients h an , h nb , h ne and h ae ; γ = P A / N0 represents the average signal-to-noise ratio of the base station, γ J = P J / N0 represents the average interference-to-noise ratio of the active eavesdropping user, is the equivalent channel gain of the legitimate channel, Y = is the equivalent channel gain of the interference channel when the active eavesdropping user interferes with the legitimate user, is the equivalent channel gain of the eavesdropping channel, Y follows an exponential distribution, and the probability density function of Y is λ = N t Ω rb Ω re .

2. The method for predicting the cybersecurity performance of the STAR-RIS network under active eavesdropping according to claim 1, wherein, The probability density function of the equivalent channel gain X of the legitimate channel is: The probability density function of the equivalent channel gain Z of the eavesdropping channel is: In the formula, represents the gamma function, is the inverse scale parameter of X, is the shape parameter of X, is the inverse scale parameter of Z, is the shape parameter of Z, μ X (k) represents the k-th moment of X, μ Z (k) represents the k-th moment of Z; μ X (k) and μ Z (k) are respectively expressed as: In the formula, 3. The active eavesdropping-based STAR-RIS network security performance prediction method according to claim 2, wherein The signal-to-noise ratio γ of the first legal signal b has a probability density function as follows: The signal-to-noise ratio γ of the second legal signal e has a probability density function as follows: In the formula, 4. The active eavesdropping-based STAR-RIS network security performance prediction method according to claim 3, wherein The security outage probability of the STAR-RIS network under active eavesdropping is represented by the probability that the security rate C s of the STAR-RIS network is lower than a predetermined security rate R; The security rate of the STAR-RIS network is: C s (γ b ,γ e ) = (log2(1 + γ b ) - log2(1 + γ e )) + ; where (x) + = max(x, 0) means taking the maximum value between x and 0; The security outage probability of the STAR-RIS network under active eavesdropping is approximately expressed as: where Pr[·] represents the safety outage probability, and δ = 2 R is the preset threshold for safety outage; Substitute the probability density functions of γ b and γ e into it. Integrate with respect to γ b The integration gives: Make a variable substitution After that, the cybersecurity outage probability of the STAR-RIS network under active eavesdropping is as follows: In the formula, Ψ(·,·;·) is the Tricomi confluent hypergeometric function.

5. A security performance prediction system for STAR-RIS networks under active eavesdropping, characterized in that, The STAR-RIS network under active eavesdropping includes: a base station, legitimate users, an active eavesdropping user, and a STAR-RIS device with multiple transmission units and multiple reflection units; the active eavesdropping user and the base station are on the same side of the STAR-RIS device, the active eavesdropping user is directly connected to the base station, the legitimate users are on the other side of the STAR-RIS, and the legitimate users are connected to the base station through the STAR-RIS device; Among them, legitimate users are used to receive legitimate signals sent by the base station through the STAR-RIS device. Active eavesdropping users are used to eavesdrop on and interfere with the legitimate signals sent by the base station to legitimate users. The STAR-RIS device is used to enhance the legitimate channel for legitimate users to receive legitimate signals and weaken the eavesdropping channel for active eavesdropping users to eavesdrop on legitimate signals; The system includes: A signal-to-noise ratio acquisition module, which is used to respectively acquire the first legitimate signal received by a legitimate user and the second legitimate signal eavesdropped by an active eavesdropping user in the STAR-RIS network under active eavesdropping, and respectively determine the signal-to-noise ratios of the first legitimate signal and the second legitimate signal through the phases of the transmission unit and the reflection unit in the STAR-RIS; Among them, the first legitimate signal received by the legitimate user is: The second legitimate signal eavesdropped by the active eavesdropping user is: Where, P A and P J respectively represent the transmission powers of the base station and the active eavesdropping user, x A represents the legitimate signal sent by the base station, x J is the interference signal sent by the active eavesdropping user, x A and x J are pre-set energy-normalized signals, h an and h nb and h ne and h ae respectively represent the complex channel coefficients of the A→R n link, R n →B link, R n →E link and A→E link. A represents the base station, B represents the legitimate user, E represents the active eavesdropping user, and R n represents the nth reflection / transmission unit of the STAR-RIS, N represents the total number of reflection and transmission units in the STAR-RIS device. The complex channel coefficients h an and h nb and h ne and h ae all follow the Nakagami-m random distribution with shape factors and spread factors of (m ar ,Ω ar ), (m rb ,Ω rb ), (m re ,Ω re ), and (m ae ,Ω ae ), respectively. j 2 =-1 represents the imaginary number, θ t,n ∈[0,2π) and θ r,n ∈[0,2π) represent the phases of the nth transmission unit and reflection unit, respectively. N t and N r represent the numbers of transmission units and reflection units, respectively, and N t +N r =N. η∈[0,1] represents the ratio of the interference power caused by the active eavesdropping user's full-duplex communication to its own interference to the transmission power P J of the active eavesdropping user. n b and n e represent the noises when the legitimate user receives the legitimate signal and the active eavesdropping user eavesdrops on the legitimate signal, respectively. The noise powers of n b and n e are both N0; A first function construction module, which is used to obtain the probability density function of the equivalent channel gain of the legitimate channel and the eavesdropping channel by using the gamma distribution according to the signal-to-noise ratios of the first legitimate signal and the second legitimate signal; Among them, the phase of the transmission unit in the STAR-RIS device is: The phase of the reflection unit in the STAR-RIS device is: The signal-to-noise ratio of the first legitimate signal is: The signal-to-noise ratio of the second legitimate signal is: where ∠h an , ∠h nb , ∠h ne and ∠h ae respectively represent the phases of the complex channel coefficients h an , h nb , h ne and h ae ; |h an |, |h nb |, |h ne |and |h ae respectively represent the magnitudes of the complex channel coefficients h an , h nb , h ne and h ae ; γ = P A / N0 represents the average signal-to-noise ratio of the base station, γ J = P J / N0 represents the average interference-to-noise ratio of the active eavesdropping user, is the equivalent channel gain of the legitimate channel, is the equivalent channel gain of the interference channel when the active eavesdropping user interferes with the legitimate user, is the equivalent channel gain of the eavesdropping channel, Y follows an exponential distribution, and the probability density function of Y is λ = N t Ω rb Ω re ; A second function construction module, which is used to respectively obtain the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal according to the probability density function of the equivalent channel gain of the legitimate channel and the eavesdropping channel and the relationship between the signal-to-noise ratio and the equivalent channel gain; A security performance prediction module, which is used to obtain a closed-form expression of the security outage probability of the STAR-RIS network under active eavesdropping according to the probability density functions of the signal-to-noise ratios of the first legitimate signal and the second legitimate signal, so as to predict the security performance of the STAR-RIS network under active eavesdropping through the closed-form expression of the security outage probability of the STAR-RIS network.

6. A computer device, characterized in that, Includes: At least one processor; And a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for predicting the security performance of the STAR-RIS network under active eavesdropping as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for predicting the security performance of the STAR-RIS network under active eavesdropping as described in any one of claims 1 to 4.

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