Relay selection anti-eavesdropping secure transmission method based on secrecy capacity in UASNs

Abstract

The invention discloses a relay selection anti-eavesdropping secure transmission method based on secrecy capacity in UASNs, and the method comprises the following specific steps: a sensor node s sends a data packet to a destination node d, a relay node r forwards the data packet to the destination node d, an active eavesdropping node e tries to intercept information forwarded by the relay node r, and the active eavesdropping node e transmits the information to the destination node d; an interference node j sends artificial noise to e to deteriorate a channel thereof; according to the method, the relay cooperative communication technology and the game theory are combined, the selfish intermediate node cooperative communication is stimulated, and the security of the network is quantified by the secrecy capacity, so that the physical layer security communication under the passive eavesdropping channel in the underwater acoustic communication is realized. The method has good performance in the frequency selective underwater acoustic channel with long time delay, and when the UASNs suffer from active eavesdropping attack of malicious nodes, the security of the system can be ensured to the maximum extent.

Description

Technical Field

[0001] The present invention relates to a relay selection anti - eavesdropping secure transmission method based on secrecy capacity in UASNs, belonging to the technical field of wireless communication security. Background Art

[0002] In recent years, Underwater Acoustic Sensor Networks (UASNs) as an emerging technology have been widely applied in ocean exploration. UASNs are network systems where sensor nodes with acoustic channels and computing capabilities achieve data acquisition and communication. However, due to the lack of direct physical protection for remote network deployment and the inherent broadcast nature of the underwater acoustic channel, UASNs are extremely vulnerable to active eavesdropping attacks by malicious nodes, affecting network performance. Therefore, there is an urgent need for an efficient secure transmission mechanism to achieve fast and sustainable transmission of ocean data.

[0003] Relay cooperative communication technology improves the reliability and anti - interference ability of information transmission in UASNs by constructing a virtual multiple - antenna system. Due to the particularity of the underwater environment, energy - constrained relay nodes often show selfishness during the cooperation process, that is, they refuse to participate in communication cooperation to save their own energy, thus affecting the overall communication performance. To encourage relay nodes to actively participate in cooperative communication, game theory can be introduced to design a reasonable revenue distribution and resource optimization mechanism to ensure efficient and stable underwater information transmission.

[0004] To ensure the security and reliability of underwater communication, traditional methods mainly rely on cryptographic secure transmission technologies, but they have defects such as high computational complexity and large communication overhead. In contrast, Physical Layer Security (PLS) uses the inherent physical characteristics such as the randomness and difference of the wireless channel to ensure information security, which is more suitable for the UASNs network environment restricted by cost and energy. Secrecy Capacity (SC), as the core index of PLS, is defined as the upper limit of the secure transmission rate that the system can achieve in the presence of eavesdroppers. Therefore, the present invention uses secrecy capacity as the evaluation index of the system security performance, designs a corresponding secure transmission method by analyzing the channel characteristics in the active eavesdropping scenario, so as to defend against the active eavesdropping attacks of malicious nodes and achieve highly secure underwater communication transmission. Summary of the Invention

[0005] In order to improve the security of underwater sensor networks and reduce the energy consumption of network nodes, the present invention designs a relay selection anti - eavesdropping secure transmission method based on secrecy capacity in UASNs.

[0006] The technical solution of the present invention is as follows:

[0007] A secure transmission method based on secrecy capacity for relay selection against eavesdropping in UASNs, the method comprising the following steps:

[0008] Step 1: Set up the network model

[0009] There are K friendly intermediate nodes in the network. The intermediate nodes cooperate in communication as relay nodes and can also act as jamming nodes to impose artificial noise on the eavesdropping nodes to deteriorate the eavesdropping channel. The sensor node s transmits a data packet to the relay node r with a transmission power The relay node r then decodes and forwards the data packet to the destination node b. Assuming there is an active eavesdropper e in the network trying to intercept the legitimate data packet forwarded from the relay node, the jamming node imposes artificial noise on it;

[0010] Step 2: Screen the candidate relay nodes

[0011] In the signal broadcast stage, screen the decoding capabilities of the intermediate nodes; set the relay received signal-to-noise ratio threshold w0, compare the signal-to-noise ratio of the intermediate nodes with the received channel ratio threshold; then further compare the gains of the intermediate nodes and the eavesdropping nodes; define the channel advantage ratio, compare the channel advantage ratio of the intermediate nodes with 1, and screen out the candidate relay nodes;

[0012] Step 3: Screen the optimal relay-jamming node group to maximize the network secrecy capacity

[0013] In the signal transmission stage, establish a Bertrand game model, set the revenue functions of the network nodes, analyze the game strategies of different relay-jamming node groups with the goal of maximizing the system secrecy capacity, and finally solve for the optimal relay-jamming node group under game equilibrium.

[0014] Preferably, the specific steps of step 1 are as follows:

[0015] 1.1 The system adopts a multi-node two-hop model in cooperative communication. In the first time slot, the sensor node s sends a legitimate signal to the relay node r, and the relay node r sends a NOTICE data packet to the jamming node j;

[0016] 1.2 In the second time slot, the relay node r decodes the legitimate signal and forwards it to the destination node b. During this process, the active eavesdropping node e intercepts the legitimate signal, and the jamming node j sends artificial noise to the active eavesdropping node e;

[0017] 1.3 After receiving the legitimate signal, the destination node d sends a NOTICE data packet to the jamming node j;

[0018] 1.4 After receiving the NOTICE data packet, the jamming node j stops sending interference signals to the eavesdropping node e;

[0019] 1.5 The relay node communicates in a half-duplex manner.

[0020] Preferably, the specific steps of step 2 are as follows:

[0021] 2.1 Screen the decoding capabilities of the intermediate nodes, the steps are as follows:

[0022] 2.1.1 Define the intermediate node as ρ, the intermediate node ρ with relay function r ∈ρ, the intermediate node ρ with interference function j ∈ρ, and ρ r ≠ρ j ;

[0023] 2.1.2 Set the relay reception signal-to-noise ratio threshold as w0;

[0024] 2.1.3 Define the signal-to-noise ratio of the intermediate node as γ l , and the mathematical expression is

[0025]

[0026] In the formula, represents the transmission power of the relay node, represents the transmission power of the interference node, represents the channel gain between the relay node and the destination node, represents the channel gain between the interference node and the destination node, σ 2 represents the variance of the additive white Gaussian noise of the communication link;

[0027] 2.1.4 If γ l ≥w0, then this intermediate node is defined as the to-be-determined relay node ρ′ r , otherwise it is defined as the to-be-determined interference node ρ′ j ;

[0028] 2.2 Compare the gain magnitudes between the intermediate node and the eavesdropping node, the steps are as follows:

[0029] 2.2.1 Define the channel advantage ratio as the ratio of the channel gain between the intermediate node and the destination node to the channel gain between the eavesdropping node and the destination node, that is

[0030]

[0031] In the formula, represents the channel gain between the intermediate node and the destination node, represents the channel gain between the eavesdropping node and the destination node;

[0032] 2.2.2 When θ rWhen it is greater than 1 and the channel quality of the intermediate node is higher than that of the eavesdropping node, then this intermediate node ρ″ r is more likely to become a relay node, and vice versa, it is classified as a pending interference node ρ′ j .

[0033] Preferably, the specific steps of step 3 are as follows:

[0034] 3.1 The power group of the intermediate node is

[0035]

[0036] 3.2 Define the signal-to-noise ratio from the relay node r to the eavesdropping node e as

[0037]

[0038] wherein, represents the channel gain between the eavesdropping node and the destination node, represents the channel gain between the jamming node and the eavesdropping node, represents the variance of the additive white Gaussian noise at the eavesdropping node;

[0039] 3.3 According to Shannon's theorem, the channel capacity C of the legitimate channel l and the channel capacity C of the eavesdropping channel e are respectively defined as

[0040]

[0041] wherein, β represents the channel bandwidth of the given legitimate communication link and eavesdropping link.

[0042] 3.4 The secrecy capacity C of the system s is defined as

[0043]

[0044] 3.5 Construct a Bertrand game model

[0045] Define the sensor node s as the game buyer, and the relay nodes and interference nodes selected from the intermediate nodes as the game sellers; the sensor node s purchases a certain amount of service power from the buyers for relay cooperative communication and sending artificial noise to maximize the secure transmission rate of the system, and the sellers sell the service power to the buyers to obtain corresponding rewards;

[0046] 3.5.1 The power cost z of the relay node r and the power cost z of the interference node j constitute the price vector defined as

[0047] z i={z j ,z r} (8)

[0048] 3.5.2 The remaining energy percentage of the sensor node s is defined as

[0049]

[0050] where γ s ∈[0,1], W is the total energy of the node, and W c is the consumed energy of the node;

[0051] 3.5.3 The power cost of the remaining energy of the node is defined as

[0052]

[0053] 3.5.4 The transmission cost of the node is defined as

[0054]

[0055] where d represents the communication transmission distance, Q represents the power cost of the remaining energy of the node, f represents the communication frequency, α represents the absorption coefficient, and k represents the path loss exponent;

[0056] 3.5.5 The revenue function of the sensor node is defined as the difference between the product of the revenue coefficient and the secrecy capacity of the main channel and the service rewards paid to the relay node and the interference node and the transmission cost. The mathematical expression is

[0057]

[0058] where a is the revenue coefficient;

[0059] 3.5.6 The revenue function of the relay-interference node group is defined as the difference between the revenue of the node group and the power cost paid; The mathematical expression is

[0060]

[0061] where b is the service power cost of the intermediate node. The intermediate node competes for the power purchase of the sensor node by adjusting the price. The choice of price and power will affect the purchase decision of the sensor node and the revenue of the intermediate node;

[0062] 3.5.7 In the system, the goals of the sensor node and the intermediate node are both to maximize their respective game revenues; The problem that the sensor node needs to solve is expressed as:

[0063]

[0064] r∈ρ″ r ,j∈ρ′ j, r ≠ j

[0065] where p t,total represents the total power limit for each time slot;

[0066] 3.5.8 The problems to be solved by the intermediate nodes are expressed as

[0067]

[0068] 3.6 The influencing factors for determining the optimal relay-jammer node group, and the selection formula for the relay-jammer node group is expressed as

[0069]

[0070] 3.7 According to Equation (5) and Equation (6), Equation (16) is written as

[0071]

[0072] 3.8 When the signal-to-noise ratio of the node approaches infinity, that is, all intermediate nodes can accurately decode the information of the sensor node, Equation (17) is further simplified to

[0073]

[0074] 3.9 According to Equation (18), when and at this time, maximizing and can obtain the optimal selection strategy;

[0075] 3.10 The selection strategy of the optimal relay-jammer node group requires that under a certain power constraint, it needs to satisfy

[0076]

[0077] where represents the channel gain between the sensor node and the relay node, and q is the ratio coefficient of the transmission powers of the relay node and the jammer node, satisfying q >> 1;

[0078] 3.11 To maximize the game revenue of the relay-jammer node group i, taking the derivative of Equation (12) and Equation (13) with respect to the power of the relay node gives

[0079]

[0080] 3.12 Let Equation (22) be 0, we get

[0081]

[0082] where A1, A2, and A3 are the powers respectively The quadratic, linear coefficients and constant term of the corresponding equation are all related to the price z r ;

[0083] 3.13 Solving equation (23) gives

[0084]

[0085] wherein, it must satisfy that the profit function C of the sensor node is > 0;

[0086] 3.14 Screening the solutions in equation (27) gives

[0087]

[0088] 3.15 Taking the derivative of equations (12) and (13) with respect to the power of the interfering node gives

[0089]

[0090] 3.16 Letting equation (29) be 0 gives

[0091]

[0092] wherein, B1, B2, B3, B4, and B5 are respectively the quartic, cubic, quadratic, linear coefficients and constant term of the power corresponding equation, and are all related to the price z j ;

[0093] 3.17 Obtained from (30), the power of the interfering node is a function of the power of the relay node and the unit price z of the interference power j , that is

[0094]

[0095] 3.18 To obtain the pricing strategies of the relay node r and the interfering node j, taking the first derivative of equation (13) with respect to the power price z i gives

[0096]

[0097] 3.19 Letting (3.18) be 0 gives

[0098]

[0099] 3.20 It is difficult to obtain a closed-form solution for equation (30). Therefore, substituting equations (28) and (36) into equation (38) gives

[0100]

[0101] 3.21 Obtained according to Equations (23) and (30), the prices of the relay node and the interference node are respectively

[0102]

[0103] 3.22 Substitute Equation (40) into Equation (13) to obtain

[0104]

[0105]

[0106] 3.23 Obtained from Equation (42), is a function of , and the IRMA algorithm is used to solve Equation (42).

[0107] 3.24 Initialize the parameters; N represents the number of iterations, ε represents the iteration threshold constraint, and eta represents the learning rate, which is used to control the speed of policy update; and respectively represent the initial regret values of the relay node and the interference node, which are used to record the historical policy improvement space of the relay node and the interference node;

[0108] 3.25 Randomly select the relay node price z r (p r ) and the interference node price z j (p j ) and substitute them into Equations (12) and (13) to obtain the relay service power p′ r and the interference service power p′ j ;

[0109] 3.26 Calculate the intermediate node revenue C i ;

[0110] 3.27 When the difference between the intermediate node revenue of the Nth iteration and the intermediate node revenue of the (N - 1)th iteration is less than or equal to ε, stop the iteration, and at this time, obtain the optimal strategies of each node in the equilibrium state and

[0111] 3.28 When the difference between the intermediate node revenue of the Nth iteration and the intermediate node revenue of the (N - 1)th iteration is greater than ε, update the regret values of the relay node and the interference node

[0112] 3.29 Update the relay node policy to be

[0113]

[0114] The interference node strategy is updated to

[0115]

[0116] The beneficial effects of the present invention are as follows:

[0117] The present invention combines relay cooperative communication technology and game theory to effectively resist active eavesdropping attacks and suppress the impact of the selfish behavior of network nodes on the security of the system. The security performance of the communication network is quantified by the secrecy capacity, and an incentive mechanism based on Bertrand game is constructed to optimize the cooperation strategy of selfish nodes. On this basis, the IRMA algorithm is used to solve the game equilibrium to ensure that the nodes improve the overall security of the system while maximizing their own benefits. The present invention has good performance in the frequency-selective underwater acoustic channel with long delay. When UASNs are subjected to active eavesdropping attacks by malicious nodes, the security of the system can be guaranteed to the greatest extent. Brief Description of the Drawings

[0118] Figure 1 It is the system model. Detailed Embodiments

[0119] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.

[0120] A secure transmission method for relay selection based on secrecy capacity in UASNs, the method comprising the following steps:

[0121] Step 1: Set the network model

[0122] There are K friendly intermediate nodes in the network. The intermediate nodes act as relay nodes for cooperative communication and can also act as interference nodes to impose artificial noise on the eavesdropping nodes to deteriorate the eavesdropping channel; the sensor node s transmits a data packet to the relay node r with a transmission power and the relay node r then decodes and forwards the data packet to the destination node b. Assume that there is an active eavesdropper e in the network trying to intercept the legitimate data packet forwarded by the relay node, and the interference node imposes artificial noise on it;

[0123] Step 2: Screen the pending relay nodes

[0124] During the signal broadcasting phase, screen the decoding capabilities of intermediate nodes; set the relay reception signal-to-noise ratio threshold w0, and compare the signal-to-noise ratio of the intermediate nodes with the reception channel ratio threshold; then further compare the gain magnitudes of the intermediate nodes and the eavesdropping nodes; define the channel advantage ratio, compare the channel advantage ratio of the intermediate nodes with 1, and screen out the pending relay nodes;

[0125] Step 3: Screen the optimal relay-jamming node group to maximize the network secrecy capacity

[0126] During the signal transmission phase, establish a Bertrand game model, set the revenue functions of the network nodes, analyze the game strategies of different relay-jamming node groups with the goal of maximizing the system secrecy capacity, and finally solve for the optimal relay-jamming node group under the game equilibrium.

[0127] Preferably, the specific steps of step 1 are as follows:

[0128] 1.1 The system adopts a multi-node two-hop model in cooperative communication. In the first time slot, the legitimate signal sent by the sensor node s to the relay node r, and the relay node r sends a NOTICE data packet to the jamming node j;

[0129] 1.2 In the second time slot, the relay node r decodes the legitimate signal and forwards it to the destination node b. During this process, the active eavesdropping node e intercepts the legitimate signal, and the jamming node j sends artificial noise to the active eavesdropping node e;

[0130] 1.3 After receiving the legitimate signal, the destination node d sends a NOTICE data packet to the jamming node j;

[0131] 1.4 After receiving the NOTICE data packet, the jamming node j stops sending interference signals to the eavesdropping node e;

[0132] 1.5 The relay node communicates in a half-duplex manner.

[0133] Preferably, the specific steps of step 2 are as follows:

[0134] 2.1 Screen the decoding capabilities of intermediate nodes, the steps are as follows:

[0135] 2.1.1 Define the intermediate nodes as ρ, the intermediate node ρ with relay function r ∈ρ the intermediate node ρ with jamming function j ∈ρ, and ρ r ≠ρ j ;

[0136] 2.1.2 Set the relay reception signal-to-noise ratio threshold as w0;

[0137] 2.1.3 Define the signal-to-noise ratio of the intermediate nodes as γ l, the mathematical expression is

[0138]

[0139] In the formula, represents the transmission power of the relay node, represents the transmission power of the interfering node, represents the channel gain between the relay node and the destination node, represents the channel gain between the interfering node and the destination node, σ 2 represents the variance of the additive white Gaussian noise of the communication link;

[0140] 2.1.4 If γ l ≥ w0, then this intermediate node is defined as a to-be-determined relay node ρ′ r , otherwise it is defined as a to-be-determined interfering node ρ′ j ;

[0141] 2.2 Compare the gain magnitudes between the intermediate node and the eavesdropping node, the steps are as follows:

[0142] 2.2.1 Define the channel advantage ratio as the ratio of the channel gain between the intermediate node - destination node to the channel gain between the eavesdropping node - destination node, that is

[0143]

[0144] In the formula, represents the channel gain between the intermediate node and the destination node, represents the channel gain between the eavesdropping node and the destination node;

[0145] 2.2.2 When θ r > 1, the channel quality of the intermediate node is higher than that of the eavesdropping node, then this intermediate node p″ r is more likely to become a relay node, otherwise it is classified as a to-be-determined interfering node ρ′ j .

[0146] Preferably, the specific steps of step 3 are as follows:

[0147] 3.1 The power group of the intermediate node is

[0148]

[0149] 3.2 Define the signal-to-noise ratio of the relay node r to the eavesdropping node e as

[0150]

[0151] In the formula, represents the channel gain between the eavesdropping node and the destination node, represents the channel gain between the eavesdropping jamming node and the eavesdropping node, and represents the variance of the additive white Gaussian noise at the eavesdropping node;

[0152] 3.3 According to Shannon's theorem, the channel capacity C of the legitimate channel l and the channel capacity C of the eavesdropping channel e are respectively defined as

[0153]

[0154] wherein, β represents the channel bandwidth of a given legitimate communication link and eavesdropping link.

[0155] 3.4 The secrecy capacity C of the system s is defined as

[0156]

[0157] 3.5 Construct a Bertrand game model

[0158] Define the sensor node s as the game buyer, and the relay node and jamming node selected from the intermediate nodes as the game sellers; the sensor node s purchases a certain amount of service power from the buyers for relay cooperative communication and sending artificial noise to maximize the secure transmission rate of the system, and the sellers sell the service power to the buyers to obtain corresponding rewards;

[0159] 3.5.1 The power cost z of the relay node r and the power cost z of the jamming node j constitute a price vector defined as

[0160] z i ={z j ,z r} (8)

[0161] 3.5.2 The remaining energy percentage of the sensor node s is defined as

[0162]

[0163] wherein, γ s ∈[0,1], W is the total energy of the node, and W c is the consumed node energy;

[0164] 3.5.3 The power cost of the remaining energy of the node is defined as

[0165]

[0166] 3.5.4 The transmission cost of the node is defined as

[0167]

[0168] In the formula, d represents the communication transmission distance, Q represents the power cost of the remaining energy of the node, f represents the communication frequency, α represents the absorption coefficient, and k represents the path loss exponent;

[0169] 3.5.5 The revenue function of the sensor node is defined as the difference between the product of the revenue coefficient and the secrecy capacity of the main channel and the service rewards paid to the relay node and the interference node and the transmission cost. The mathematical expression is

[0170]

[0171] In the formula, a is the revenue coefficient;

[0172] 3.5.6 The revenue function of the relay-interference node group is defined as the difference between the revenue of the node group and the power cost paid; the mathematical expression is

[0173]

[0174] In the formula, b is the service power cost of the intermediate node. The intermediate node competes for the power purchase of the sensor node by adjusting the price, and the choice of price and power will affect the purchase decision of the sensor node and the revenue of the intermediate node;

[0175] 3.5.7 In the system, the goals of both the sensor node and the intermediate node are to maximize their respective game revenues; the problem that the sensor node needs to solve is expressed as:

[0176]

[0177] In the formula, p t,total represents the total power limit per time slot;

[0178] 3.5.8 The problem that the intermediate node needs to solve is expressed as

[0179]

[0180] 3.6 Determine the influencing factors for the optimal relay-interference node group. The selection formula for the relay interference node group is expressed as

[0181]

[0182] 3.7 According to formula (5) and formula (6), formula (16) is written as

[0183]

[0184] 3.8 When the signal-to-noise ratio of the node approaches infinity, that is, all intermediate nodes can accurately decode the information of the sensor node, formula (17) is further simplified to

[0185]

[0186] 3.9 According to formula (18), when and maximize and to obtain the optimal selection strategy;

[0187] 3.10 The selection strategy of the optimal relay-jammer node group requires that under a certain power constraint, it needs to satisfy

[0188]

[0189] wherein, represents the channel gain between the sensor node and the relay node, q is the ratio coefficient of the transmission powers of the relay node and the jammer node, satisfying q >> 1;

[0190] 3.11 To maximize the game revenue of the relay-jammer node group i, take the derivatives of formulas (12) and (13) with respect to the power of the relay node to obtain

[0191]

[0192] 3.12 Let formula (22) be 0, to obtain

[0193]

[0194] wherein, A1, A2, and A3 are respectively the quadratic, linear coefficients and constant terms of the equation corresponding to the power and are all related to the price z r ;

[0195] 3.13 Solve formula (23) to obtain

[0196]

[0197] wherein, it must satisfy that the revenue function C of the sensor node is > 0;

[0198] 3.14 Screen the solutions in formula (27) to obtain

[0199]

[0200] 3.15 Take the derivatives of formulas (12) and (13) with respect to the power of the jammer node to obtain

[0201]

[0202] 3.16 Let formula (29) be 0, to obtain

[0203]

[0204]

[0205] In the formula, B1, B2, B3, B4, and B5 are the power of the fourth, third, second, first coefficients and the constant term of the corresponding equation, all of which are related to the price z j ;

[0206] 3.17 is obtained from (30), and the interference node power is the function of the relay node power and the unit price z of the interference power j , that is

[0207]

[0208] 3.18 To obtain the pricing strategies of the relay node r and the interference node j, the first derivative of Equation (13) with respect to the power price z i is obtained as

[0209]

[0210] 3.19 Let (3.18) be 0, and we get

[0211]

[0212] 3.20 It is difficult to obtain a closed-form solution for Equation (30). Therefore, substituting Equation (28) and Equation (36) into Equation (38), we get

[0213]

[0214] 3.21 According to Equation (23) and Equation (30), the prices of the relay node and the interference node are respectively

[0215]

[0216] 3.22 Substituting Equation (40) into Equation (13), we get

[0217]

[0218] 3.23 From Equation (42), we get is a function of , and the IRMA algorithm is used to solve Equation (42).

[0219] 3.24 Initialize the parameters; N represents the number of iterations, ε represents the iteration threshold constraint, and eta represents the learning rate, which is used to control the speed of policy update; and respectively represent the initial regret values of the relay node and the interference node, which are used to record the historical strategy improvement spaces of the relay node and the interference node;

[0220] 3.25 Randomly select the relay node price z r (p r ) and the interference node price z j (p j ) and substitute them into equations (12) and (13) to obtain the relay service power p′ r and the interference service power p′ j ;

[0221] 3.26 Calculate the intermediate node revenue C i ;

[0222] 3.27 When the difference between the intermediate node revenue in the Nth iteration and the intermediate node revenue in the (N - 1)th iteration is less than or equal to ε, stop the iteration. At this time, obtain the optimal strategies of each node in the equilibrium state and

[0223] 3.28 When the difference between the intermediate node revenue in the Nth iteration and the intermediate node revenue in the (N - 1)th iteration is greater than ε, update the regret values of the relay node and the interference node

[0224] 3.29 Update the relay node strategy to

[0225]

[0226] 3.30 Update the interference node strategy to

[0227]

Claims

1. A relay selection anti-eavesdropping secure transmission method based on secrecy capacity in UASNs, characterized in that, It includes the following steps: Step 1: Set up the network model There are K friendly intermediate nodes in the network. The intermediate nodes can cooperate in communication as relay nodes and can also act as interfering nodes to impose artificial noise on the eavesdropping nodes to deteriorate the eavesdropping channel. The sensor node s transmits a data packet to the relay node r with a transmission power to the relay node r. The relay node r then decodes and forwards the data packet to the destination node b. Assume that there is an active eavesdropper e in the network attempting to intercept the legitimate data packet forwarded from the relay node, and the interfering node imposes artificial noise on it; Step 2: Screen the pending relay nodes In the signal broadcast phase, screen the decoding capabilities of the intermediate nodes; set the relay reception signal-to-noise ratio threshold w0, compare the signal-to-noise ratio of the intermediate nodes with the reception channel ratio threshold; then further compare the gain magnitudes between the intermediate nodes and the eavesdropping nodes; define the channel advantage ratio, compare the channel advantage ratio of the intermediate nodes with 1, and screen out the pending relay nodes; Step 3: Screen the optimal relay-jamming node group to maximize the network secrecy capacity In the signal transmission phase, establish a Bertrand game model, set the revenue functions of the network nodes, analyze the game strategies of different relay-jamming node groups with the goal of maximizing the system secrecy capacity, and finally solve for the optimal relay-jamming node group under the game equilibrium.

2. The relay selection anti-eavesdropping secure transmission method based on secrecy capacity in UASNs according to claim 1, characterized in that The specific steps of the said Step 1 are as follows: 1.1 The system adopts a multi-node two-hop model in cooperative communication In the first time slot, the sensor node s sends a legitimate signal to the relay node r, and the relay node r sends a NOTICE data packet to the jamming node j; 1.2 In the second time slot, the relay node r decodes the legitimate signal and forwards it to the destination node b. During this process, the active eavesdropping node e intercepts the legitimate signal, and the jamming node j sends artificial noise to the active eavesdropping node e; 1.3 After receiving the legitimate signal, the destination node d sends a NOTICE data packet to the jamming node j; 1.4 After receiving the NOTICE data packet, the jamming node j stops sending interference signals to the eavesdropping node e; 1.5 The relay node communicates in a half-duplex manner.

3. A method for secure transmission against eavesdropping with relay selection based on secrecy capacity in UASNs according to claim 2, characterized in that The specific steps of the said Step 2 are as follows: 2.1 Screen the decoding capabilities of the intermediate nodes, and the steps are as follows: 2.1.1 Define the intermediate node as ρ, and the intermediate node ρ with relay function r ∈ρ, and the intermediate node ρ with interference function j ∈ρ, and ρ r ≠ρ j ; 2.1.2 Set the relay reception signal-to-noise ratio threshold as w0; 2.1.3 Define the signal-to-noise ratio of the intermediate node as γ l , and the mathematical expression is Wherein, represents the transmission power of the relay node, represents the transmission power of the interfering node, represents the channel gain between the relay node and the destination node, represents the channel gain between the interfering node and the destination node, σ 2 represents the variance of the additive white Gaussian noise of the communication link; 2.1.4 If γ l ≥ w0, then this intermediate node is defined as a relay node to be determined ρ′ r , otherwise it is defined as an interference node to be determined ρ′ j ; 2.2 Compare the gain magnitudes between the intermediate nodes and the eavesdropping nodes, and the steps are as follows: 2.2.1 Define the channel advantage ratio as the ratio of the channel gain between the intermediate node and the destination node to the channel gain between the eavesdropping node and the destination node, that is wherein, represents the channel gain between the intermediate node and the destination node, represents the channel gain between the eavesdropping node and the destination node; 2.2.2 When θ r > 1, the channel quality of the intermediate node is higher than that of the eavesdropping node. Then, this intermediate node ρ″ r is more likely to become a relay node. Conversely, it is classified as a pending interference node ρ′ j .

4. A method for secure transmission against eavesdropping with relay selection based on secrecy capacity in UASNs according to claim 3, characterized in that, The specific steps of the said Step 3 are as follows: 3.1 The power group of the intermediate nodes is 3.2 Define the signal-to-noise ratio from the relay node r to the eavesdropping node e as wherein, represents the channel gain between the eavesdropping node and the destination node, represents the channel gain between the jamming - eavesdropping node and the eavesdropping node, represents the variance of the additive white Gaussian noise at the eavesdropping node; 3.3 According to Shannon's theorem, the channel capacity C of the legitimate channel l and the channel capacity C of the wiretap channel e are respectively defined as wherein, β represents the channel bandwidth of a given legitimate communication link and an eavesdropping link; 3.4 Secrecy Capacity \(C\) of the System s is defined as 3.5 Construct a Bertrand game model Define the sensor node s as the game buyer, and the relay nodes and jamming nodes screened from the intermediate nodes as the game sellers; the sensor node s purchases a certain amount of service power from the buyers for relay cooperative communication and sending artificial noise to maximize the secure transmission rate of the system, and the sellers sell the service power to the buyers to obtain corresponding rewards; 3.5.1 Power cost of relay nodes z r and power cost of interference nodes z j The price vector composed of is defined as z i ={z j ,z r}(8) 3.5.2 Define the remaining energy percentage of the sensor node s as where γ s ∈ [0, 1], W is the total energy of the node, and W c is the energy consumed by the node; 3.5.3 Define the power cost of the remaining energy of the node as 3.5.4 The transmission cost of a node is defined as In the formula, d represents the communication transmission distance, Q represents the power cost of the remaining energy of the node, f represents the communication frequency, α represents the absorption coefficient, and k represents the path loss exponent; 3.5.5 Define the revenue function of the sensor node as the difference between the product of the revenue coefficient and the main channel secrecy capacity and the service rewards and transmission costs paid to the relay node and the jamming node. The mathematical expression is In the formula, a is the revenue coefficient; 3.5.6 The revenue function of the relay-jamming node group is defined as the difference between the revenue of the node group and the power cost paid; the mathematical expression is where b is the service power cost of the intermediate node. The intermediate node competes for the power purchase of the sensor node by adjusting the price. The selection of the price and power will affect the purchase decision of the sensor node and the revenue of the intermediate node; 3.5.7 In the system, the objectives of both the sensor node and the intermediate node are to maximize their respective game revenues; the problem that the sensor node needs to solve is expressed as: where p t,total represents the total power limit for each time slot; 3.5.8 The problem that the intermediate node needs to solve is expressed as 3.6 Determine the influencing factors for the optimal relay-jamming node group. The selection formula of the relay-jamming node group is expressed as 3.7 According to formula (5) and formula (6), formula (16) is written as 3.8 When the signal-to-noise ratio of the node approaches infinity, that is, all intermediate nodes can accurately decode the information of the sensor node, formula (17) is further simplified to 3.9 According to formula (18), when and is true, maximizing and can obtain the optimal selection strategy; 3.10 The selection strategy of the optimal relay-jamming node group requires that under a certain power constraint, it needs to satisfy In the formula, represents the channel gain between the sensor node and the relay node, q is the ratio coefficient of the transmission powers of the relay node and the interference node, and q >> 1 is satisfied; 3.11 To maximize the game payoff of the relay-jammer node group \(i\), take the derivative of equations (12) and (13) with respect to the power of the relay node The derivative is obtained as follows 3.12 Let formula (22) be 0, and we get Wherein, A1, A2, and A3 are respectively the quadratic, linear coefficients, and constant term of the corresponding equation, all of which are related to the price z ; r related; 3.13 Solve formula (23), and we get Wherein, The revenue function C of the sensor node must satisfy C>0; 3.14 Screen the solutions in formula (27) to get 3.15 Differentiate equations (12) and (13) with respect to the power of the interfering node to obtain 3.16 Let formula (29) be 0, and we get where B1, B2, B3, B4, and B5 are the fourth, third, second, first coefficients and the constant term of the corresponding equation, respectively, and are all related to the price z ; j related; 3.17 is obtained from (30), where the interfering node power is the relay node power and the unit price z of the interference power j is a function of, that is 3.18 To obtain the pricing strategies for the relay node r and the interfering node j, formula (13) takes the first derivative with respect to the power price z i The first derivative is obtained as follows 3.19 Let (3.18) be 0, and we get 3.20 It is difficult to obtain a closed-form solution for formula (30). Therefore, substitute formula (28) and formula (36) into formula (38) to get 3.21 According to formula (23) and formula (30), the prices of the relay node and the jamming node are respectively 3.22 Substitute formula (40) into formula (13) to get 3.23 is obtained from Equation (42), which is a function of and the IRMA algorithm is used to solve Equation (42). 3.24 Initialization parameters; N represents the number of iterations, ε represents the iterative threshold constraint, and eta represents the learning rate, which is used to control the speed of policy update; and respectively represent the initial regret values of the relay node and the interference node, which are used to record the historical policy improvement space of the relay node and the interference node; 3.25 Randomly select the price z of the relay node r (p r ) and the price z of the interfering node j (p j ) and substitute them into equations (12) and (13) to obtain the relay service power p′ r and the interfering service power p′ j ; 3.26 Calculate the revenue C of the intermediate node i ; 3.27 Stop the iteration when the difference between the intermediate node payoffs in the Nth iteration and the intermediate node payoffs in the (N - 1)th iteration is less than or equal to ε. At this time, obtain the optimal strategies of each node in the equilibrium state and 3.28 When the difference between the intermediate node revenue of the Nth iteration and the intermediate node revenue of the (N - 1)th iteration is greater than ε, update the regret values of the relay node and the interference node 3.29 Update the relay node strategy to 3.30 Update the jamming node strategy to

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