Vehicle covert communication interference strategy optimization method and system

Abstract

The invention discloses a vehicle covert communication interference strategy optimization method and system, and the method comprises the steps: (1) constructing a vehicle covert communication model which comprises a plurality of transmitting vehicles, a plurality of interference vehicles, a base station and a listener; (2) establishing a vehicle covert communication auction model, taking a base station as a buyer, submitting a value estimation set to an auction management party, the value estimation set comprising a value estimation value allocated to each seller pair by each spectrum of the base station, forming the seller pair by any transmitting vehicle and any interference vehicle, generating a bid according to the cost, and sending the bid to the auction management party; the bid, the channel signal interference noise ratio and the hidden threshold are submitted to an auction management party, and the auction management party solves the matching result of the frequency spectrum, the transmitting vehicle and the interference vehicle which enable the base station utility to be maximum and the optimal transmitting power of each transmitting vehicle; and (3) solving the vehicle covert communication auction model to obtain an optimized vehicle covert communication interference strategy. According to the invention, the concealment of vehicle covert communication can be improved.

Description

Technical Field

[0001] The present invention relates to vehicle communication technology, and in particular to a vehicle concealed communication interference strategy optimization method and system. Background Art

[0002] With the rapid development of on-board sensors in smart vehicles, the Internet of Vehicles (IoV) has become a new paradigm for real-time traffic monitoring and autonomous driving. Vehicle-to-Everything (V2X) communication, as an important component of IoV, enables vehicles to interact with other vehicles, infrastructure, networks, and pedestrians, making daily vehicle operations safer, greener, and more efficient. However, due to the openness of wireless channels, attackers can intercept, tamper with, or forge communication data, which may lead to incorrect decisions by traffic management systems and vehicles. Although traditional cryptographic methods can ensure communication security, they require frequent key and protocol updates in dynamic environments, resulting in large communication overhead. Covert communication reduces the probability of being detected by attackers by hiding communication signals in background noise or other legitimate signals, thereby greatly improving the security of communication.

[0003] In high-traffic road scenarios, there are usually multiple vehicles that need to communicate, but spectrum resources are limited, and the resources of the vehicle-mounted equipment themselves are also limited. Therefore, a jamming strategy optimization technology for spectrum resource allocation in a vehicle covert communication system is needed to improve the concealment of the vehicle covert communication system. Summary of the invention

[0004] In view of the problems existing in the prior art, the purpose of the present invention is to provide a vehicle covert communication jamming strategy optimization method, system and device that can improve concealment.

[0005] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions: A vehicle covert communication jamming strategy optimization method comprises the following steps: (1) constructing a vehicle covert communication model, which includes a number of transmitting vehicles that transmit covert signals, a number of jamming vehicles that transmit jamming signals, a base station that receives the signals of the transmitting vehicles, and an eavesdropper; (2) Establishing a vehicle covert communication auction model, in which the base station is regarded as the buyer and submits a value valuation set to the auction manager. The value valuation set includes the value valuation of each spectrum allocated to each seller pair by the base station. Any transmitting vehicle and any interfering vehicle form a seller pair, and a bid is generated according to the cost. The bid, channel signal interference noise ratio, and concealment threshold are submitted to the auction manager. The auction manager solves the matching result of the spectrum, transmitting vehicle, and interfering vehicle that maximizes the utility of the base station, and the optimal transmission power of each transmitting vehicle based on the value valuation set of the base station, the bid of the seller pair, the channel signal interference noise ratio, and the concealment threshold. (3) Solving the vehicle covert communication auction model, obtaining matching results and the optimal transmission power of each transmitting vehicle, and using the matching results and the optimal transmission power of the transmitting vehicle as the optimized vehicle covert communication jamming strategy.

[0006] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above method.

[0007] A vehicle covert communication jamming strategy optimization system includes a computer program / instruction, and the computer program / instruction implements the above method when executed by a processor.

[0008] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention proposes a vehicle covert communication jamming strategy optimization technology based on auction theory, which is suitable for vehicle covert communication scenarios. By selecting suitable jamming vehicles and spectrum resource allocation and adjusting the transmission power, the communication concealment is improved.

[0009] 2. The present invention is a reverse VCG auction algorithm. The base station acts as a buyer and proposes covert communication requirements, while the transmitting vehicle and the jamming vehicle act as sellers and provide services. Under the premise of ensuring incentive compatibility, the optimal matching of Alice's vehicle and the jamming vehicle is achieved.

[0010] 3. To further reduce the computational complexity, the present invention proposes a reverse second price sealed auction algorithm (SPSA). The algorithm constructs a one-sided preference list and sorts the seller pairs in a non-increasing order to optimize the selection of the interfering vehicle while retaining incentive compatibility and individual rationality to approximately achieve the optimal match. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a flow chart of a vehicle covert communication jamming strategy optimization method provided by an embodiment of the present invention; Figure 2 is a schematic diagram of a vehicle covert communication model provided by an embodiment of the present invention; Figure 3 This is a vehicle covert communication auction model provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0012] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0013] Embodiment 1 of the present invention provides a vehicle covert communication jamming strategy optimization method, such as Figure 1 As shown, the following steps are included: (1) Construct a vehicle covert communication model.

[0014] Among them, Figure 2 As shown in Figure 1, the vehicle covert communication model includes several transmitting vehicles that transmit covert signals, several interfering vehicles that transmit interfering signals, a base station that receives the signals of the transmitting vehicles, and an eavesdropper. The transmitting vehicle is represented by Alice, and the set of transmitting vehicles is , A is the number of transmitting vehicles. Jam vehicles are represented by Jam, which are idle vehicles. The jamming vehicle set is , J is the number of interfering vehicles. The bandwidth used for covert communication is divided into several spectrum resources, and the spectrum resource set is , F is the number of spectrum. The base station is represented by Bob, which is responsible for managing spectrum resources. The listener is represented by Willie, who listens to the signal emitted by the reflected vehicle. The data transmission between Alice and Bob is completed with the assistance of Jam to counter Willie's monitoring.

[0015] In the vehicle covert communication model, all vehicles work synchronously in a time slot. The symbols of the transmitting vehicle and the interfering vehicle are encoded with Gaussian random variables. The interfering vehicle adjusts the transmission power according to the requirements of the transmitting vehicle, thereby realizing covert information transmission.

[0016] When a transmitting vehicle wants to transmit information, it needs to select an interference vehicle to send an interference signal. All vehicles are in half-duplex mode, and each vehicle has only one antenna. In this invention, the research goal is to design the best combination of transmitting vehicles and interference vehicles and spectrum resource allocation scheme.

[0017] This embodiment is specifically studied under a block fading channel. It is understandable that other channels may also be used for the study.

[0018] The channel gain under block fading channel is: , In the formula, Indicates a The channel from the vehicle to the base station uses f The channel gain when the spectrum is Indicates a The channel from the transmitting vehicle to the listener uses f The channel gain when the spectrum is Indicates j The channel from the interfering vehicle to the base station adopts the f The channel gain when the spectrum is Indicates j The channel from the interfering vehicle to the listener adopts the f The channel gain when the spectrum is α a,b For the a The small-scale fading coefficient of the channel between the transmitting vehicle and the base station, α a,w Indicates a The small-scale fading coefficient of the channel from the transmitting vehicle to the listener, α j,b Indicates j The small-scale fading coefficient of the channel from the interfering vehicle to the base station, α j,w Indicates j The small-scale fading coefficient of the channel from the interfering vehicle to the listener includes path loss and shadow fading. Indicates a Channel selection between the transmitting vehicle and the base station f The channel coefficient when the spectrum is is the channel coefficient of the corresponding channel.

[0019] Assume that all nodes are synchronized within the time slot boundary, the transmission codeword length is n, and all Alice and Jam share the same zero-mean standard complex Gaussian codebook. a The information sequence transmitted by the transmitting vehicle Alice , Indicates a The i-th signal sent by the transmitting vehicle has a transmission power of P a ; The corresponding jamming vehicle is the jth jamming vehicle Jam, and the jamming signal sequence emitted by the jth jamming vehicle Jam is , represents the i-th signal of the j-th jamming vehicle Jam, with a transmission power of P j . Then the signal received at Willie It is expressed as: , Among them, H1 means Alice is transmitting, and H0 means Alice is not transmitting. Indicates noise.

[0020] Willie based on the received signal Perform binary hypothesis detection to determine whether Alice is transmitting. Let the probabilities of H0 and H1 be P0 and P1 respectively. There are two types of errors in Willie's detection, namely false alarm and missed detection. False alarm means that in the case of H0, Willie mistakenly judges that Alice is transmitting; missed detection means that in the case of H1, Willie does not detect that Alice is transmitting. Assume that the prior probabilities of H1 and H0 are equal. Denote the false alarm probability, missed detection probability and detection error probability as P FA , P MD and ξ, so ξ=P FA +P MD Willie's goal is to minimize ξ, and he knows the vehicle's location information, transmission power, noise variance, Alice's vehicle codebook statistical model, and the distance between each vehicle. Alice’s privacy can be ensured when , where is the privacy threshold. The privacy rate can be expressed as: , in k a,j,f Represents a matching indicator variable, when k a,j,f =1, it means that the f The spectrum resources are allocated to a The launch vehicle and j A disruptive vehicle. Indicated in j With the assistance of an interfering vehicle a The link from the transmitting vehicle to the base station adopts the f The signal-to-interference-noise ratio (SINR) for a spectrum is expressed as: , in is the noise variance at the base station Bob. In the embodiment, it is assumed that Bob can estimate the complete channel state information (CSI) of all the links related to him, including and and store it in the cloud.

[0021] (2) Establish the Vehicular Covert Communication Auction Model (VCCAM).

[0022] Among them, Figure 3 As shown, the participants in the model VCCAM include base station Bob, transmitting vehicle Alice, interfering vehicle Jam and auction management party. Base station Bob acts as the buyer, transmitting vehicle Alice and interfering vehicle Jam act as sellers, and the auction management party acts as a third-party intermediary, which can be a cloud server, etc.

[0023] 2.1) Seller model.

[0024] The transmitting vehicle Alice and the jamming vehicle Jam are considered as two different types of sellers. In order to obtain utility from Bob, Alice provides covert information, while Jam provides help and services in covert communication. Therefore, the concept of seller pairs is introduced. a When the transmitting vehicle Alice successfully matches with the jth jamming vehicle Jam, they form a seller pair ( a,j ).

[0025] The cost to the seller is defined as: .

[0026] Sellers a,j ) should be based on its cost c a,j Submit their bid s a,j When participating in an auction, you can choose from three bidding strategies: strategy a) bid equal to cost; strategy b) bid higher than cost; strategy c) bid less than cost.

[0027] The final seller's information I S for: .

[0028] In this example, it is assumed that the seller is selfish. The better the service it provides, the higher its cost. And the better the service, the higher the concealment rate. Afterwards, you can Calculate the concealment rate.

[0029] 2.2) Buyer model.

[0030] Bob is considered a buyer with the ability to manage resource blocks (RBs). His goal is to maximize utility to meet his communication and data collection needs. Similar to Alice and Jam, Bob also submits a value matrix V to the auction manager: , In the formula, va,j,f Indicates f The spectrum is allocated to a The launch vehicle and j The value of the interfering vehicle is estimated. represents a monotonically increasing function, that is, Positive correlation.

[0031] 2.3) Auction management model.

[0032] The auction manager receives Alice and Jam's information and forwards it to Bob. The auction manager then manages the auction by solving the following two problems: i) Determine the auction result: After receiving the bid and valuation, the auction algorithm needs to be run and the winning seller needs to be determined. Specifically, in the buyer-dominated market, multiple sellers compete to bid to see who can offer the best price or terms, similar to the scenario of procurement or bidding. Specifically, when the first f The spectrum resources are allocated to a The launch vehicle and j When there are interfering vehicles, the matching indicator variable k a,j,f will be set to 1.

[0033] ii) Develop a payment rule: The auction administrator further uses a feasible payment rule to calculate the payment from the buyer to the winning seller pair. This payment provides incentives for Alice and Jam to perform high-quality tasks. For example, Alice is incentivized to transmit at the maximum rate to obtain more utility. Jam is incentivized to obtain more utility by assisting covert communication. Therefore, designing a feasible payment rule is crucial.

[0034] 2.4) Design objectives.

[0035] When designing the auction model for covert vehicle communication, reserve price, single round, and sealed auctions without buyer-seller collusion are considered. The key design goals are incentive compatibility, individual rationality, and computational efficiency, which are defined as follows.

[0036] Computational efficiency: An auction is said to be computationally efficient if the auction results can be computed in polynomial time.

[0037] Incentive compatibility: If the optimal strategy for all participants is strategy (a), that is, for each seller pair, the condition If the above is always true, then the auction is said to be incentive compatible, which means that no one can gain more utility by submitting an incorrect bid.

[0038] Individual rationality: If the seller always obtains non-negative utility, that is, If the above two conditions always hold, then the auction is said to have individual rationality. In other words, no one can destabilize the auction by making irrational bids. In addition, if the auction has both incentive compatibility and individual rationality, then it is called a strategically robust auction.

[0039] Therefore, the optimization problem of establishing the vehicle covert communication auction model is: , , , , , , , , In the formula, represents the total utility of the base station, K represents the matching result, Represents the average detection error probability of the listener.

[0040] The above optimization problem is an NP-hard 0-1 integer programming problem. Specifically, the constraints Ensures the confidentiality of communication. Indicates that each resource block can only be aggregated A launch vehicle and assembly One of the following interferes with the use of the vehicle. means that each interfering vehicle can only help one transmitting vehicle and can only use one spectrum. Finally, It means that each transmitting vehicle can only select one interfering vehicle and one spectrum.

[0041] Assume that all channels are quasi-static Rayleigh channels with sufficiently long coherence times. The small-scale fading coefficients remain constant within a single time slot of codeword length n, but vary independently between different slots.

[0042] The listener Willie receives the a The symbols sent by Alice, a transmitting vehicle, with the help of the jth interfering vehicle Jam follow a complex Gaussian distribution. The signal received by Willie It is expressed as: , represents a Gaussian distribution, represents the noise variance at the position of the listener Willie. Consider the strongest case faced by Willie, he knows all the information of the model, including the noise variance, the channel state information between the interfering vehicle and the listener, the channel state information between the transmitting vehicle and the listener, Alice's random codebook generation method, and Jam's random interference generation method. Therefore, when any hypothesis is true, Willie has complete statistical knowledge of his observations. Using the Neyman-Person criterion, Willie's optimal detection that minimizes his detection error probability is the likelihood ratio test (LRT) : , in Receive signals at H1 and H0 respectively The probability density function (PDF) of . They are Probability distribution under H1 and H0.

[0043] Using the concepts of random order theory, it can be concluded that LRT is equivalent to the following test: , This corresponds to a Willie average received power With threshold Compare the threshold detection.

[0044] A common assumption in block fading covert communication is that the block length .therefore, It can be expressed as: , Note that Willie only knows the channel distribution information (CDI) between itself and each Jam vehicle, but does not have the channel coefficients between Jam and Willie. The exact instantaneous CSI of The PDF of gives the optimal threshold that minimizes the probability of Willie detection error and the minimum detection error probability : , Minimum detection error probability It is from Willie's perspective, not Alice's. In reality, Alice does not have the channel coefficient between Alice and Willie. Therefore, according to The probability density function is used to solve the average detection error probability, which is expressed as: , In the formula, , Indicates the x position The value of the probability density function, the hidden constraint can be rewritten as: .

[0045] From the above formula, we can see that a The optimal transmission power of the transmitting vehicle Alice satisfy , which is the optimal transmission power The optimal transmission power is obtained when the average detection error probability is equal to the concealment threshold. The calculation formula is: .

[0046] Higher transmission power means Alice provides higher concealment rate and enables Bob to obtain more utility. Therefore, according to the formula , can be rewritten as: .

[0047] (3) Solving the vehicle covert communication auction model, obtaining matching results and the optimal transmission power of each transmitting vehicle, and using the matching results and the optimal transmission power of the transmitting vehicle as the optimized vehicle covert communication jamming strategy.

[0048] The reverse VCG auction algorithm is used to solve the vehicle covert communication auction model, as follows: (A 3.1) Initialize K to 0; (A 3.2) Randomly generate K and use the Monte Carlo method to obtain the optimal matrix of VCCAM K* ; (A3.3) For each element in K k a,j,f , if its value is 1, then set the bid s a,j is infinite, and the Monte Carlo method is used to solve the optimal matrix of VCCAM again ; (A 3.4) Calculate the seller’s income, i.e. the buyer’s expenditure, according to the following formula: , In the formula, is the optimal matrix K*The value below It is in a Alice’s vehicle and j Jam vehicles are not included in the auction. Down For k a,j,f For elements with a median value of 0, the corresponding seller’s income is set to 0.

[0049] It can be seen from the design goals that the reverse VCG auction algorithm lacks computational efficiency, has incentive compatibility, and has individual rationality. Therefore, further optimization can be performed and simplified by adopting a second-price sealed bid auction. Similar to the VCG auction, Bob is required to submit his payment according to the rules of the second-price sealed bid auction. However, unlike the VCG auction, in the second-price sealed auction, the revenue of Alice's vehicle and Jam's vehicle only compensates the losses caused by the seller who submitted the second-highest bid. To achieve this, the second-highest bid is determined by constructing a unified preference list. The details are as follows: (B 3.1) Based on the estimated value of each spectrum allocated to each seller and the cost price, the utility is calculated using the following formula: , In the formula, R a,j,f Indicates f The spectrum is allocated to a The launch vehicle and j The utility of a disturbing vehicle, v a,j,f Represents a collection of value estimates V Middle f The spectrum is allocated to a The launch vehicle and j The value of the interfering vehicle is estimated. c a,j For the a The launch vehicle and j The cost of a seller interfering with the vehicle is They represent spectrum resource set, transmitting vehicle set, and interfering vehicle set respectively; (B 3.2) Establish a set of overall preference lists based on utility: , In the formula, M represents the overall preference list set, M f Indicates f A total preference list, which stores serial number pairs ( a,j,f ), Indicated in Mf In, when When the sequence number is ( a,j,f ) in the sequence number pair Front, Indicates that the fth spectrum is allocated to the The launch vehicle and The utility of a disruptive vehicle; (B 3.3) Assign values ​​to the matching indicator variables according to the following formula based on the utility; , (B 3.4) Based on the set of overall preference lists, calculate the income of each seller pair in each overall preference list according to the following formula: , In the formula, p a,j Indicates the a The launch vehicle and j The seller of the vehicle interferes with the income, is M f Located in ( a,j,f ) in the first pair of serial numbers after the seller, Indicates that the seller The cost, Indicates that the seller For f Spectrum bids, Indicates that the seller For the loss k a,j,f For elements with a median value of 0, the corresponding seller’s income is set to 0.

[0050] Embodiment 2 of the present invention provides a computer device, and the embodiment of the present invention provides services for implementing the method of embodiment 1 of the present invention. The device may include: a memory storing a computer executable program; a processor coupled to the memory; the processor calls the computer executable program stored in the memory to execute the steps in the method described in embodiment 1.

[0051] The memory may include computer system readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory. The device may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the memory may be used to read and write non-removable, non-volatile magnetic media (commonly referred to as a "hard drive"). A program / utility having a set (at least one) of program modules may be stored in, for example, the memory, such program modules including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The computer executable program of the program module typically performs the functions and / or methods in the embodiments described in the present invention.

[0052] The processor executes various functional applications and data processing by running the program stored in the memory, such as implementing the method provided in the first embodiment of the present invention.

[0053] The code of the computer executable program can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" language or similar programming languages.

[0054] Embodiment 3 of the present invention provides a vehicle concealed communication jamming strategy optimization system, such as an app on a mobile phone, a tablet, an installation program on a computer, etc., including a computer program / instruction, and the computer program / instruction is executed by a processor to implement the method described in embodiment 1. The code of the computer executable program for performing the operation of the present invention can be written in one or more programming languages ​​or a combination thereof, and the programming language includes an object-oriented programming language, such as Java, Smalltalk, C++, and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet). It should be noted that, in this document, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0055] It should be understood that the above embodiments and descriptions only describe the principles, main features and advantages of the present invention. Without departing from the spirit and scope of the present invention, the present invention may be subject to various changes and improvements, and these changes and improvements all fall within the scope of protection of the present invention.

Claims

1. A vehicle covert communication jamming strategy optimization method, characterized in that: The steps include: (1) constructing a vehicle covert communication model, which includes a number of transmitting vehicles that transmit covert signals, a number of jamming vehicles that transmit jamming signals, a base station that receives the signals of the transmitting vehicles, and an eavesdropper; (2) Establishing a vehicle covert communication auction model, in which the base station is regarded as the buyer and submits a value valuation set to the auction manager. The value valuation set includes the value valuation of each spectrum allocated to each seller pair by the base station. Any transmitting vehicle and any interfering vehicle form a seller pair, and a bid is generated according to the cost. The bid, channel signal interference noise ratio, and concealment threshold are submitted to the auction manager. The auction manager solves the matching result of the spectrum, transmitting vehicle, and interfering vehicle that maximizes the utility of the base station, and the optimal transmission power of each transmitting vehicle based on the value valuation set of the base station, the bid of the seller pair, the channel signal interference noise ratio, and the concealment threshold. (3) Solving the vehicle covert communication auction model, obtaining matching results and the optimal transmission power of each transmitting vehicle, and using the matching results and the optimal transmission power of the transmitting vehicle as the optimized vehicle covert communication jamming strategy.

2. The vehicle covert communication jamming strategy optimization method according to claim 1 is characterized in that: In the vehicle covert communication model, all vehicles work synchronously in a time slot, the symbols of the transmitting vehicle and the interfering vehicle are encoded using Gaussian random variables, and the interfering vehicle adjusts the transmission power according to the requirements of the transmitting vehicle, thereby realizing covert information transmission.

3. The vehicle covert communication jamming strategy optimization method according to claim 1 is characterized in that: The value estimation set sent by the base station is: , In the formula, v a,j,f Represents a collection of value estimates V Middle f The spectrum is allocated to a The launch vehicle and j The value of the interfering vehicle is estimated. represents a monotonically increasing function, represents the hidden threshold, Indicated in j With the assistance of an interfering vehicle a The link from the transmitting vehicle to the base station adopts the f The signal-to-interference-noise ratio for the spectrum is is the noise variance, P j Indicates j The transmission power of the interfering vehicle, Indicates a The channel from the vehicle to the base station uses f The channel gain when the spectrum is Indicates j The channel from the interfering vehicle to the base station adopts the f The channel gain when the spectrum is α j,w , α a,w Respectively represent j The interfering vehicle a The small-scale fading coefficient of the channel from the transmitting vehicle to the listener.

4. The vehicle covert communication jamming strategy optimization method according to claim 1 is characterized in that: The information submitted by the seller is as follows: , In the formula, I S Indicates the information submitted by the seller. s a,j For the a The launch vehicle and j The sellers of the interfering vehicles bid on Indicated in j With the assistance of an interfering vehicle a The link from the transmitting vehicle to the base station adopts the f The signal-to-interference-noise ratio for the spectrum is represents the hidden threshold, They represent spectrum resource set, transmitting vehicle set, and interfering vehicle set respectively.

5. The vehicle covert communication jamming strategy optimization method according to claim 1 is characterized in that: The optimization problem of the vehicle covert communication auction model is: ， ， ， ， ， ， ， , In the formula, represents the total utility of the base station, K represents the matching result, k a,j,f Represents a matching indicator variable, when k a,j,f =1, it means that the f The spectrum resources are allocated to a The launch vehicle and j Interfering vehicles, They represent the spectrum resource set, the transmitting vehicle set, and the interfering vehicle set respectively. v a,j,f Represents a collection of value estimates V Middle f The spectrum is allocated to a The launch vehicle and j The value of the interfering vehicle is estimated. s a,j For the a The launch vehicle and j The sellers of the interfering vehicles bid on c a,j For the a The launch vehicle and j The cost of the seller pair of the interfering vehicle is represented by a The launch vehicle and j The seller of the vehicle interferes with the income, represents the average detection error probability of the listener, Indicated in j With the assistance of an interfering vehicle a The link from the transmitting vehicle to the base station adopts the f The signal-to-interference-noise ratio for the spectrum is represents the hidden threshold, Indicates a The launch vehicle and j The utility of a seller interfering with the vehicle.

6. The vehicle covert communication jamming strategy optimization method according to claim 5 is characterized in that: The average detection error probability of the listener is specifically: ， In the formula, P a , P j Respectively represent a Launch vehicle, j The transmission power of the interfering vehicle, α j,w , α a,w Respectively represent j The interfering vehicle a The small-scale fading coefficient of the channel from the transmitting vehicle to the listener.

7. The vehicle covert communication jamming strategy optimization method according to claim 5 is characterized in that: The optimal transmission power of the transmitting vehicle is: ， In the formula, Indicates a The optimal transmission power of each transmitting vehicle, P j represents the transmission power of the jth interfering vehicle, represents the concealment threshold, α j,w , α a,w Respectively represent j The interfering vehicle a The small-scale fading coefficient of the channel from the transmitting vehicle to the listener.

8. The vehicle covert communication jamming strategy optimization method according to claim 1 is characterized in that: Step (3) specifically includes: (3.1) Based on the estimated value of each spectrum allocated to each seller and the cost price, the utility is calculated using the following formula: ， In the formula, R a,j,f Indicates f The spectrum is allocated to a The launch vehicle and j The utility of a disturbing vehicle, v a,j,f Represents a collection of value estimates V Middle f The spectrum is allocated to a The launch vehicle and j The value of the interfering vehicle is estimated. c a,j For the a The launch vehicle and j The cost of a seller interfering with the vehicle is They represent spectrum resource set, transmitting vehicle set, and interfering vehicle set respectively; (3.2) Establish a set of overall preference lists based on utility: ， In the formula, M represents the overall preference list set, M f Indicates f A total preference list, which stores serial number pairs ( a,j, f ), Indicated in M f In, when When the sequence number is ( a,j,f ) in the sequence number pair Front, Indicates that the fth spectrum is allocated to the The launch vehicle and The utility of a disruptive vehicle; (3.3) According to the utility, the matching indicator variable is assigned a value according to the following formula; ， (3.4) Based on the set of overall preference lists, the income of each seller pair in each overall preference list is calculated according to the following formula: ， In the formula, p a,j Indicates the a The launch vehicle and j The seller of the vehicle interferes with the income, is M f Located in ( a,j,f ) in the first pair of serial numbers after the seller, Indicates that the seller The cost, Indicates that the seller For f Spectrum bids, Indicates that the seller loss.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: The processor executes the computer program to implement the method according to any one of claims 1 to 8.

10. A vehicle covert communication jamming strategy optimization system, comprising a computer program / instructions, characterized in that: When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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