An optimization method and system for vehicle covert communication interference strategy

Abstract

The present invention discloses a method and system for optimizing a vehicle covert communication interference strategy, including: (1) constructing a vehicle covert communication model, including a number of transmitting vehicles, a number of interfering vehicles, a base station, and a listener; (2) establishing a vehicle covert communication auction model, taking the base station as the buyer, submitting a value valuation set to the auction management party, where the value valuation set includes the value valuation of each spectrum allocated by the base station to each seller pair, and any transmitting vehicle and any interfering vehicle form a seller pair, generating bids according to costs, and submitting the bids, channel signal interference noise ratio, and covert threshold to the auction management party, and the auction management party 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; (3) solving the vehicle covert communication auction model to obtain an optimized vehicle covert communication interference strategy. The present invention can improve the covertness of vehicle covert communication.

Description

Technical Field

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

[0002] With the rapid development of in-vehicle sensors in intelligent 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 part of IoV, enables vehicles to interact with other vehicles, infrastructure, networks, and pedestrians, making daily vehicle operations safer, more environmentally friendly, and more efficient. However, due to the openness of the wireless channel, attackers can intercept, tamper with, or forge communication data, which may lead to incorrect decisions in traffic management systems and vehicles. Although traditional cryptographic methods can ensure communication security, they require frequent key and protocol updates in a dynamic environment, resulting in a large communication overhead. Covert communication, on the other hand, hides communication signals in background noise or other legitimate signals, reducing the probability of being detected by attackers and thus greatly enhancing the security of communication.

[0003] In high-traffic road scenarios, there are usually multiple vehicles that need to communicate, while the spectrum resources are limited, and the resources of in-vehicle devices are also limited. Therefore, an interference strategy optimization technology for spectrum resource allocation in vehicle covert communication systems is needed to improve the concealment of vehicle covert communication systems. Summary of the Invention

[0004] Aiming at the problems existing in the prior art, the purpose of the present invention is to provide a method, system, and device for optimizing a vehicle covert communication interference strategy that can improve concealment.

[0005] To achieve the above invention purpose, the present invention provides the following technical solutions:

[0006] A method for optimizing a vehicle covert communication interference strategy, comprising the following steps:

[0007] (1) Construct a vehicle covert communication model, where the vehicle covert communication model includes several transmitting vehicles that transmit covert signals, several interfering vehicles that transmit interference signals, a base station that receives the signals of the transmitting vehicles, and a listener;

[0008] (2)Establish a vehicle covert communication auction model. In the vehicle covert communication auction model, the base station is regarded as the buyer and submits a set of value valuations to the auction management party. The set of value valuations includes the value valuation of each spectrum of the base station assigned to each seller pair. Any transmitting vehicle and any interfering vehicle form a seller pair. The bid is generated according to the cost, and the bid, channel signal-to-interference-plus-noise ratio, and covert threshold are submitted to the auction management party. The auction management party solves the matching results of the spectrum, transmitting vehicle, and interfering vehicle that maximize the utility of the base station and the optimal transmission power of each transmitting vehicle according to the set of value valuations of the base station, the bids of the seller pairs, the channel signal-to-interference-plus-noise ratio, and the covert threshold.

[0009] (3)Solve the vehicle covert communication auction model to obtain the matching results and the optimal transmission power of each transmitting vehicle, and use the matching results and the optimal transmission power of the transmitting vehicle as the optimized vehicle covert communication interference strategy.

[0010] A computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor executes the computer program to implement the above method.

[0011] A vehicle covert communication interference strategy optimization system includes computer programs / instructions, and when the computer programs / instructions are executed by a processor, the above method is implemented.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0013] 1. The present invention proposes an optimization technology for vehicle covert communication interference strategies based on auction theory, which is applicable to vehicle covert communication scenarios. By selecting appropriate interfering vehicles and allocating spectrum resources and adjusting the transmission power, the communication covertness is improved.

[0014] 2. The present invention is a reverse VCG auction algorithm. The base station is regarded as the buyer and proposes covert communication requirements, while the transmitting vehicle and the interfering vehicle are regarded as the sellers and provide services. Under the premise of ensuring incentive compatibility, the optimal matching of the Alice vehicle and the interfering vehicle is achieved.

[0015] 3. To further reduce the computational complexity, the present invention proposes a Reverse Second Price Sealed Auction (SPSA). This algorithm constructs a unilateral preference list, sorts the seller pairs in non-increasing order, optimizes the selection of interfering vehicles, and at the same time retains incentive compatibility and individual rationality to approximately achieve the optimal matching. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1It is a schematic flow chart of the method for optimizing the vehicle covert communication interference strategy provided by the embodiments of the present invention;

[0017] Figure 2 It is a schematic diagram of the vehicle covert communication model provided by the embodiments of the present invention;

[0018] Figure 3 It is the vehicle covert communication auction model provided by the embodiments of the present invention. Detailed implementation manners

[0019] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention.

[0020] Embodiment 1 of the present invention provides a method for optimizing the vehicle covert communication interference strategy. As Figure 1 shown, it includes the following steps:

[0021] (1) Construct a vehicle covert communication model.

[0022] Among them, as Figure 2 shown, the vehicle covert communication model includes several transmitting vehicles that emit covert signals, several interfering vehicles that emit interference signals, a base station that receives the signals of the transmitting vehicles, and a listener. The transmitting vehicles are represented by Alice, and the set of transmitting vehicles is , A being the number of transmitting vehicles. The interfering vehicles are represented by Jam, and the interfering vehicles are idle vehicles. The set of interfering vehicles is , J being the number of interfering vehicles. The bandwidth for covert communication is divided into several segments of spectrum resources. The set of spectrum resources is , F being the number of spectrums. The base station is represented by Bob, and the base station is responsible for managing the spectrum resources. The listener is represented by Willie, and the listener monitors the signals emitted by the reflecting vehicles. The data transmission between Alice and Bob is assisted by Jam to counter Willie's monitoring.

[0023] In the vehicle covert communication model, all vehicles work synchronously within one time slot. The symbols of the transmitting vehicles and the interfering vehicles are encoded using Gaussian random variables. The interfering vehicles adjust their transmission power according to the requirements of the transmitting vehicles, so as to achieve covert information transmission.

[0024] When a certain transmitting vehicle needs to transmit information, it is necessary to select an interfering vehicle to send an interference signal. All vehicles are in half-duplex mode, and each vehicle has only one antenna. In the present invention, the research objective is to design the best combination of transmitting vehicles and interfering vehicles and the spectrum resource allocation scheme.

[0025] This embodiment is specifically studied under a block fading channel. It is understandable that other channels may also be used for the study.

[0026] The channel gain under block fading channel is:

[0027] ,

[0028] 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.

[0029] 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 interfering vehicle Jam, with a transmission power of P j . Then the signal received at Willie is expressed as:

[0030] ,

[0031] where H 1 indicates that Alice is transmitting, while H 0 indicates that Alice is not transmitting, represents the noise.

[0032] Based on the received signal , Willie performs binary hypothesis testing to determine whether Alice is transmitting. Denote the probabilities of H 0 and H 1 as P 0 and P 1 respectively. There are two types of detection errors for Willie, namely false alarm and missed detection. A false alarm means that when H 0 holds, Willie wrongly judges that Alice is transmitting; a missed detection means that when H 1 holds, Willie fails to detect that Alice is transmitting. Assume that the prior probabilities of H 1 and H 0 are equal. Denote the false alarm probability, missed detection probability, and detection error probability as P FA , P MD , and ξ respectively. Thus, ξ = P FA + P MD . Willie's goal is to minimize ξ, and the position information of the vehicles, transmission power, noise variance, codebook statistical model of Alice's vehicle, and the distances between the vehicles are known. When , the concealment of Alice can be ensured, where is the concealment threshold. The concealment rate can be expressed as:

[0033] ,

[0034] where k a,j,f represents the matching indicator variable. When k a,j,f = 1, it means that the f th spectrum resource is allocated to the a th transmitting vehicle and the j th interfering vehicle. represents the link from the j th transmitting vehicle to the base station with the assistance of the a th interfering vehiclef The signal-to-interference-plus-noise ratio (SINR) at a spectrum, which is expressed as:

[0035] ,

[0036] where is the noise variance at base station Bob. In the embodiment, it is assumed that Bob can estimate the complete channel state information (CSI) of all relevant links, including and , and store it in the cloud.

[0037] (2) Establish a Vehicular Covert Communication Auction Model (VCCAM).

[0038] Among them, as shown in Figure 3 , the participants in model VCCAM include base station Bob, transmitting vehicle Alice, jamming vehicle Jam, and the auction manager. Base station Bob acts as the buyer, transmitting vehicle Alice and jamming vehicle Jam act as the sellers, and the auction manager acts as a third-party intermediary, which can specifically be a cloud server, etc.

[0039] 2.1) Seller model.

[0040] Transmitting vehicle Alice and jamming vehicle Jam are regarded as two different types of sellers. To obtain utility from Bob, Alice provides covert information, while Jam provides assistance and services in covert communication. Therefore, the concept of seller pair is introduced. When the i-th transmitting vehicle Alice successfully matches with the j-th jamming vehicle Jam in the auction, they form a seller pair ( a ). a, j )

[0041] The cost of the seller pair is defined as: .

[0042] The seller pair ( a, j ) needs to submit its bid c a,j according to its cost s a,j . When participating in the auction, it can choose from three bidding strategies: Strategy a) bid equal to the cost; Strategy b) bid higher than the cost; Strategy c) bid less than the cost.

[0043] The information I S finally submitted by the seller pair is:

[0044] 。

[0045] In this embodiment, it is assumed that the seller is selfish. Providing better service also means higher costs for it. And better service means a higher concealment rate. After learning it can be calculated according to to obtain the concealment rate.

[0046] 2.2) Buyer model.

[0047] Bob is regarded as the buyer and has the ability to manage resource blocks (RBs). Its goal is to maximize the utility to meet its communication and data collection needs. Similar to Alice and Jam, Bob also submits a value matrix V to the auction manager:

[0048] ,

[0049] where v a,j,f represents the value evaluation of the f th spectrum allocated to the a th transmitting vehicle and the j th interfering vehicle, represents a monotonically increasing function, that is, positively correlated with .

[0050] 2.3) Auction manager model.

[0051] The auction manager receives the information from Alice and Jam and forwards it to Bob. Then, the auction manager manages the auction by solving the following two problems:

[0052] i) Determine the auction result: After receiving the bids and valuations, it is necessary to run the auction algorithm and decide the winning seller. Specifically, in the case of a buyer-dominated scenario where multiple sellers compete to offer the most favorable price or conditions, similar to the scenario of procurement or tendering. Specifically, when allocating the f th spectrum resource to the a th transmitting vehicle and the j th interfering vehicle, the matching indicator variable k a,j,f will be set to 1.

[0053] ii) Formulate the payment rule: The auction manager further uses a feasible payment rule to calculate the payment from the buyer to the winning seller pair. This payment provides an incentive 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 in covert communication. Therefore, designing a feasible payment rule is crucial.

[0054] 2.4) Design Goals.

[0055] When designing the vehicle covert communication auction model, reserve prices, single-round, and sealed-bid auctions without collusion between buyers and sellers are considered. The key design goals are incentive compatibility, individual rationality, and computational efficiency, which are defined as follows.

[0056] Computational Efficiency: An auction is said to have computational efficiency if the auction result can be computed within polynomial time.

[0057] Incentive Compatibility: An auction is said to have incentive compatibility if, for all participants, the optimal strategy is strategy (a), i.e., for each pair of sellers, the condition always holds. This means that no one can obtain more utility by misreporting their bids.

[0058] Individual Rationality: An auction is said to have individual rationality if a seller always obtains non-negative utility, i.e., always holds. In other words, no one can disrupt the stability of the auction by making irrational bids. Additionally, if an auction has both incentive compatibility and individual rationality, it is called a strategy-proof auction.

[0059] Therefore, the optimization problem for establishing the vehicle covert communication auction model is:

[0060] ,

[0061] ,

[0062] ,

[0063] ,

[0064] ,

[0065] ,

[0066] ,

[0067] ,

[0068] where, represents the total utility of the base station, K represents the matching result, represents the average detection error probability of the eavesdropper.

[0069] The above optimization problem is an NP-hard 0-1 integer programming problem. Specifically, the constraint ensures the secrecy of communication. represents that each resource block can only be in the set One of the launch vehicles and the set is used by one of the jamming vehicles. It means that each jamming vehicle can only assist one launch vehicle and can only use one spectrum. Finally, it means that each launch vehicle can only select one jamming vehicle and one spectrum.

[0070] Assume that all channels are quasi-static Rayleigh channels with a sufficiently long coherence time. The small-scale fading coefficient remains unchanged within a single time slot of the codeword length n, but varies independently between different slots.

[0071] The eavesdropper Willie receives the symbols sent by the a -th launch vehicle Alice with the help of the jamming vehicle Jam at the j-th position. These symbols follow a complex Gaussian distribution. The signal received by Willie is expressed as:

[0072] ,

[0073] represents the Gaussian distribution, represents the noise variance at the position of the eavesdropper Willie. Considering the strongest case that Willie faces, he knows all the information of the model, including the noise variance, the channel state information between the jamming vehicle and the eavesdropper, the channel state information between the launch vehicle and the eavesdropper, the way of generating Alice's random codebook and the way of generating Jam's random interference. Therefore, when any hypothesis is true, Willie has complete statistical knowledge of his observations. Using the Neyman-Person criterion, Willie's optimal detection for minimizing his detection error probability is the likelihood ratio test (LRT) :

[0074] ,

[0075] where are the probability density functions (PDFs) of the received signal 1 and 0 under H respectively. are under H 1 and 0 respectively.

[0076] Using the concept of the stochastic order theory, it can be concluded that the LRT is equivalent to the following detection:

[0077] ,

[0078] This corresponds to a threshold detection that compares the average received power of Willie with a threshold .

[0079] A common assumption is adopted in block - fading covert communication, that is, the block length . Therefore, can be expressed as:

[0080] ,

[0081] Note that Willie only knows the channel distribution information (CDI) between itself and each Jam vehicle, and does not have the exact instantaneous CSI of the channel coefficients between Jam and Willie . The following formula gives the optimal threshold that minimizes Willie's detection error probability according to the PDF of as well as the minimum detection error probability :

[0082] ,

[0083] The minimum detection error probability is from Willie's perspective, rather than Alice's. In a practical scenario, Alice does not have the instantaneous CSI of the channel coefficients between Alice and Willie . Therefore, to solve for the average detection error probability according to the probability density function of , it is expressed as:

[0084] ,

[0085] wherein, , represents the value of the probability density function of at the x position, and the covert constraint condition can be rewritten as:

[0086] .

[0087] From the above formula, it can be seen that the optimal transmit power a of the th transmitting vehicle Alice satisfies , that is, the optimal transmit power is obtained when the average detection error probability is equal to the covert threshold, thus deriving the calculation formula for the optimal transmit power as:

[0088] .

[0089] Higher transmission power means that Alice provides a higher concealment rate and enables Bob to obtain more utility. Therefore, according to the formula , can be rewritten as:

[0090] .

[0091] (3) Solve the vehicle covert communication auction model to obtain the matching result and the optimal transmission power of each transmitting vehicle, and use the matching result and the optimal transmission power of the transmitting vehicle as the optimized vehicle covert communication interference strategy.

[0092] Use the reverse VCG auction algorithm to solve the vehicle covert communication auction model, specifically as follows:

[0093] (A 3.1) Initialize K to 0;

[0094] (A 3.2) Randomly generate K and use the Monte Carlo method to obtain the optimal matrix of VCCAM K* ;

[0095] (A3.3) For each element in K k a,j,f , if its value is 1, then set the bid s a,j to infinity and use the Monte Carlo method to re-solve the optimal matrix of VCCAM ;

[0096] (A 3.4) Calculate the seller's revenue, that is, the buyer's expenditure, according to the following formula:

[0097] ,

[0098] where, is the value under the optimal matrix K* , while is the value of a under j when the th Alice vehicle and the th Jam vehicle do not participate in the auction. For the elements with a value of 0 in k a,j,f , the corresponding seller's revenue is set to 0.

[0099] As can be seen from the design objectives, the reverse VCG auction algorithm lacks computational efficiency, has incentive compatibility, and is individually rational. Therefore, it can be further optimized and simplified by adopting the second-price sealed 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, different from the VCG auction, in the second-price sealed auction, the revenues of Alice's vehicle and Jam's vehicle only compensate for the losses caused by the seller who submits the second-highest bid. To achieve this, the second-highest bid is determined by constructing a unified preference list. Specifically as follows:

[0100] (B 3.1) According to the value valuation of each spectrum assigned to each pair of sellers and the cost price, the utility is calculated using the following formula:

[0101] ,

[0102] In the formula, R a,j,f represents the utility of the f th spectrum assigned to the a th transmitting vehicle and the j th interfering vehicle, v a,j,f represents the value valuation set V in which the f th spectrum assigned to the a th transmitting vehicle and the j th interfering vehicle, c a,j is the cost of the pair of sellers of the a th transmitting vehicle and the j th interfering vehicle, respectively represent the spectrum resource set, the transmitting vehicle set, and the interfering vehicle set;

[0103] (B 3.2) Establish a set of overall preference lists based on the utility:

[0104] ,

[0105] In the formula, M represents the set of overall preference lists, M f represents the f th overall preference list, which internally stores the serial number pair ([[]] a, j, f ), represents that in M f , when , the serial number pair ([[]] a, j, f ) is ranked before the serial number pair , represents the fth spectrum assigned to the the utility of the th transmitting vehicle and the

[0106] (B 3.3)Assign values to the matching indication variables according to the utility according to the following formula;

[0107] ,

[0108] (B 3.4)According to the set of overall preference lists, calculate the revenue of each pair of sellers in each overall preference list according to the following formula:

[0109] ,

[0110] wherein, p a,j represents the revenue of the pair of sellers of the a th transmitting vehicle and the j th jamming vehicle, is the pair of sellers in the first serial number pair after ( M f ) in a, j, f , represents the cost of the pair of sellers , represents the bid of the pair of sellers for the f th spectrum, represents the loss of the pair of sellers . For the elements with a value of 0 in k a,j,f , the corresponding pair of sellers' revenue is set to 0.

[0111] Embodiment 2 of the present invention provides a computer device, and the embodiment of the present invention provides services for the implementation of the method in Embodiment 1 above. The device may include: a memory storing computer-executable programs; a processor coupled to the memory; the processor calls the computer-executable programs stored in the memory to execute the steps in the method described in Embodiment 1.

[0112] 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 for reading from and writing to a non-removable, non-volatile magnetic medium (commonly referred to as a "hard disk drive"). Programs / utilities with a set of (at least one) program modules may be stored in, for example, the memory, and such program modules include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. The implementation of a network environment may be included in each or some combination of these examples. The computer-executable programs of the program modules generally perform the functions and / or methods in the embodiments described in the present invention.

[0113] The processor executes various functional applications and data processing by running the programs stored in the memory, such as implementing the method provided in the first embodiment of the present invention.

[0114] The code of the computer-executable program can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages.

[0115] The third embodiment of the present invention provides a vehicle covert communication interference strategy optimization system, such as an app on a mobile phone, a tablet, an installation program on a computer, etc., including computer programs / instructions, and the computer programs / instructions implement the method described in the first embodiment when executed by a processor. The code of the computer-executable program for performing the operations of the present invention can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely 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 can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet). It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0116] It should be understood that the above embodiments and the descriptions in the specification are only the principles, main features and advantages of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the protection scope 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 to obtain 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; 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.

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 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.

6. The vehicle covert communication jamming strategy optimization method according to claim 1 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.

7. 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.

8. 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 7.

9. 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 7 is implemented.

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