Multi-hop unmanned aerial vehicle network security communication method and system under interference and eavesdropping mixed attack

Abstract

The invention discloses a multi-hop unmanned aerial vehicle network security communication method and system under interference and eavesdropping mixed attack, and the method comprises the steps: enabling a ground controller to sense the network topology of a legal unmanned aerial vehicle group and the position information of an attacker unmanned aerial vehicle in the face of the interference and eavesdropping mixed attack initiated by an attacker in the environment; and iteratively solving the problem by using an external approximation algorithm, and finally, reasonably selecting the role of each legal unmanned aerial vehicle, including an idle node, a routing node or a friendly jammer. The selected routing nodes form a multi-hop secure communication path, and the friendly jammer provides security defense for each hop of path. Meanwhile, by controlling the sending power of the routing node and the interference power of the friendly jammer, the channel capacity of a secure communication path and the eavesdropping channel capacity of an attacker can be further balanced, so that the secrecy rate in the service data transmission process is improved.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) communication security, and in particular to a network security communication method and system for multi-hop UAVs under a hybrid attack of interference and eavesdropping. Background Technology

[0002] In recent years, thanks to their advantages of mobility, flexibility, and rapid deployment, drones have been widely used in disaster relief, critical infrastructure security inspections, and military applications. However, issues such as data leakage due to eavesdropping attacks during drone communication, or the inability of the receiving end to obtain complete information due to interference attacks, have also attracted considerable attention. From a data perspective, eavesdropping can be prevented by sending misleading messages or encrypting the data. For example, Chinese patent publication number CN120602927A proposes a drone communication security and low-power energy consumption optimization system, which improves the data's anti-decryption and anti-tampering capabilities through dynamic S-Box generation, AES encryption, and hybrid encryption. C. Fan et al. [C. Fan, H. Liu, B. Li, C. Zhao and S. Mao, "Adversarial Game Against Hybrid Attacks in UAV Communications With Partial Information," in IEEE Transactions on Vehicular Technology, vol. 71, no. 2, pp. 2204-2208, Feb. 2022, doi: 10.1109 / TVT.2021.3132934.] considered the communication security between legitimate drones and base stations, proposing that legitimate drones evade eavesdropping by alternating between sending normal and misleading information.

[0003] Encryption-based drone communication security suffers from drawbacks such as complex encryption processes leading to long encryption times. Furthermore, its security relies entirely on key security; if an attacker obtains the key, the defense becomes completely ineffective. Similarly, defenses relying on sending misleading messages also fail if attackers learn the alternation intervals between normal and misleading messages or can distinguish between normal and misleading signals. Therefore, a more robust approach is to address the inherent characteristics of the drone itself, considering trajectory optimization or power control to resist both active and passive eavesdropping attacks. For example, Chinese patent publication number CN110855342B proposes a control method, device, electronic device, and storage medium for drone communication security. This patent considers communication systems with eavesdroppers and addresses the uncertainty of user location by modeling the scenario into a drone transmission power sub-problem model and a flight trajectory sub-problem model. Finally, it solves these two sub-problem models to ensure the maximum average confidentiality rate for legitimate users in the worst-case scenario. H. Wu et al. [H. Wu, M. Li, Q. Gao, Z. Wei, N. Zhang and X. Tao, "Eavesdropping and Anti-Eavesdropping Game in UAV Wiretap System: A Differential Game Approach," in IEEE Transactions on Wireless Communications, vol. 21, no. 11, pp. 9906-9920, Nov. 2022, doi: 10.1109 / TWC.2022.3180395.] considered a scenario where a drone acts as a base station for communication with ground users, during which the communication data may be eavesdropped on by attackers in the environment. Therefore, this paper proposes to optimize the trajectory so that the drone base station can avoid eavesdroppers as much as possible, and to perform power control based on the current location of the drone base station to balance the user's signal reception and eavesdropping prevention.

[0004] After modeling the communication scenario, a suitable method needs to be selected to solve it. Reinforcement learning can respond promptly to dynamic scenarios without prior knowledge. Chinese patent publication number CN120812594A proposes a multi-UAV intelligent secure communication method and system based on digital twins. Considering the dynamic changes in the location of eavesdroppers, it uses deep reinforcement learning to obtain flight trajectory strategies for the UAV system under different situations, effectively avoiding eavesdropping. Y. Ding et al. [Y. Ding et al., "Collaborative Communication and Computation for Secure UAV-Enabled MEC Against Active Aerial Eavesdropping,"in IEEE Transactions on Wireless Communications, vol. 23, no. 11, pp. 15915-15929, Nov. 2024, doi: 10.1109 / TWC.2024.3435017.] considers a scenario where ground equipment offloads data to the UAV for computation, a process that may be subject to eavesdropping by attackers. Therefore, this paper proposes a secure edge computing solution based on reinforcement learning, which effectively defends against aerial eavesdropping attacks by optimizing time allocation, transmit power, local and offloaded computing bits, and drone trajectories.

[0005] In the aforementioned drone application scenarios, only eavesdropping attacks launched by attackers in the environment are considered, while the possibility of attackers launching interference attacks in real-world scenarios, preventing the receiving end from receiving complete and valid information, is ignored. Furthermore, in scenarios where drones are performing remote tasks, it is unreasonable to only consider the security of single-hop communication. Summary of the Invention

[0006] The purpose of this invention is to solve the problems in the prior art.

[0007] The technical solution adopted by this invention to solve its technical problem is: to provide a network security communication method for multi-hop UAVs under a mixed attack of interference and eavesdropping, comprising the following steps:

[0008] Sensing the environmental situation, including the status of legitimate drones and attackers, the distance between legitimate drones and attackers, and channel gain;

[0009] Construct a communication security optimization model with multiple constraints and coupling;

[0010] For the aforementioned multi-constraint coupled communication security optimization model, reconstruct the objective function;

[0011] The objective function is solved iteratively based on an external approximation algorithm.

[0012] Preferably, the status of the legitimate drone and the attacker is obtained through the following steps:

[0013] Introducing friendly interference decision variables ,in, Indicating legal drones In idle state Indicating legal drones Acting as a friendly jammer to perform friendly interference against attackers, with a friendly jamming power of [value missing]. ;

[0014] Consider legal drones and ground controller ,node and nodes The communication status between them introduces routing decision variables. ,in, Represents a node and nodes They do not communicate with each other. Represents a node Give nodes Sending service data, with a transmission power of The nodes include legitimate drones and ground controllers;

[0015] Introducing decision variables To represent the attacker's drone The state in which, Indicates attacker drone Launch an eavesdropping attack. Indicates attacker drone Initiate a jamming attack with a jamming power of .

[0016] Preferably, the distance between the legitimate drone and the attacker is obtained through the following steps:

[0017] Establish a three-dimensional Cartesian coordinate system and a ground controller. The horizontal coordinate is legal drones The horizontal coordinate is Fixed flight altitude is attacker drone The horizontal coordinate is Fixed flight altitude is ;

[0018] Determine the ground controller With legal drones Distance between Ground controller With attacker drones Distance between legal drones and legal drones Distance between legal drones and attacker drones Distance between .

[0019] Preferably, the channel gain is obtained through the following steps:

[0020] Assuming all devices in the scenario are equipped with only one omnidirectional antenna, and the antenna gain of the omnidirectional antenna is constant, a legal drone is defined. The antenna gain is attacker drone The antenna gain is Ground controller The antenna gain is Given the antenna gain and range, consider a legal unmanned aerial vehicle (UAV) in an air-to-air model. and attacker drones , can obtain nodes and nodes The channel gain between them is:

[0021] ;

[0022] in, It is the reference gain coefficient of the Loss Channel. It is the path loss exponent of the Loss-Oriented (LoS) channel;

[0023] In the ground-to-air model, the ground controller With nodes The channel gain between them is:

[0024] ;

[0025] in, According to the ground controller With nodes Angle of elevation between The baseline gain coefficient obtained after calculating the Loss probability. For ground controller With nodes Angle of elevation between The path loss exponent is obtained after calculating the Loss of Path (LoS) probability.

[0026] Preferably, the construction of the multi-constraint coupled communication security optimization model includes the following steps:

[0027] In the safe path, if Then the routing node and routing nodes The communication channel capacity between them is:

[0028] ;

[0029] ;

[0030] in, It is the bandwidth of the communication channel. It is environmental noise;

[0031] If there are attackers in the environment During an eavesdropping attack, the routing node and eavesdropping drones The eavesdropping channel capacity between them is:

[0032] ;

[0033] ;

[0034] If multiple attackers launch eavesdropping attacks simultaneously in an environment, the maximum eavesdropping channel capacity in the environment is defined as:

[0035] ;

[0036] Finally define the routing node and routing nodes The confidentiality rate of the communication process is:

[0037] ;

[0038] Extending single-hop communication into multi-hop communication, the objective function is expressed as:

[0039] ;

[0040] in, The solution set for the final selection of routing nodes. To ultimately select the solution set of the friendly jammer, The set of interference power solutions for each friendly jammer. Send the power solution set to the routing node.

[0041] Preferably, the multi-constraint coupled communication security optimization model reconstructs the objective function by including the following steps:

[0042] For the Max-Min problem, by introducing an auxiliary variable Add a constraint, represented as:

[0043] ;

[0044] in, This represents the minimum confidentiality rate in the path. It is a constant;

[0045] The objective function is equivalently replaced with:

[0046] ;

[0047] The optimization problem is further restructured because... ,when At that time, the constraint becomes:

[0048] ;

[0049] when At that time, the constraint becomes:

[0050] ;

[0051] Therefore, it is directly omitted. ;

[0052] for Introduce an auxiliary variable Indicates in Send business data to The maximum eavesdropping capacity in the environment during the process is represented by the following constraint:

[0053] ;

[0054] Through auxiliary variables Reconstruct the objective function:

[0055] ;

[0056] in, This is the set of maximum eavesdropping channel capacities across all single-hop paths.

[0057] Preferably, the iterative solution of the objective function based on the external approximation algorithm includes the following steps:

[0058] Initialization parameters, including the upper bound The lower realm Precision threshold and maximum number of iterations Define a set of integer solutions that satisfy the constraints. Substitute this into the subproblem, solve the subproblem to obtain a set of solutions. This indicates that after selecting the path and the friendly jammer, optimization was achieved to obtain a jamming power of [value missing]. The transmission power is At that time, it can maximize the minimum confidentiality rate along the entire path. And the maximum eavesdropping channel capacity in the environment is Update the Nether ;

[0059] Based on the solutions to the subproblems, a linear approximation of the nonlinear constraints is constructed using Taylor expansion, and this approximation is added to the main problem for solution, yielding the fixed integer variables of the subproblems in the next iteration. and continuous variables Update the upper boundary ;

[0060] calculate The value, if or the number of iterations is greater than If the condition is met, the iteration stops; otherwise, the iteration continues to solve the subproblem and the main problem until the iteration termination condition is met.

[0061] The final solution is the path with the minimum confidentiality rate that is maximized.

[0062] This invention also provides a network security communication system for multi-hop drones under a hybrid attack of interference and eavesdropping, comprising:

[0063] The environmental perception module senses the environmental situation, including the status of legitimate drones and attackers, the distance between legitimate drones and attackers, and the channel gain.

[0064] The model building module constructs a communication security optimization model with multiple constraints and coupling.

[0065] The objective function reconstruction module reconstructs the objective function of the multi-constraint coupled communication security optimization model.

[0066] The objective function solving module iteratively solves the objective function based on an external approximation algorithm.

[0067] The present invention also provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements any of the methods described above.

[0068] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements any of the methods described above.

[0069] The present invention has the following beneficial effects:

[0070] (1) This invention introduces a drone that supports role switching and uses an external approximation algorithm to solve the problem to obtain a security strategy, including reasonably selecting a secure transmission path from the source node to the target node and reasonably setting up a friendly jammer to ensure the security of each hop path.

[0071] (2) In view of the broadcast characteristics of the signal, the present invention further controls the transmission power of the routing node and the interference power of friendly interference to improve the security of the entire communication system.

[0072] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments, but the present invention is not limited to the embodiments. Attached Figure Description

[0073] Figure 1 This is a flowchart illustrating the method steps of a multi-hop UAV network security communication method under a hybrid attack of interference and eavesdropping, according to an embodiment of the present invention.

[0074] Figure 2 This is a scenario diagram illustrating the multi-hop UAV network security communication method under a hybrid attack of interference and eavesdropping, as described in an embodiment of the present invention.

[0075] Figure 3 This is a flowchart illustrating the network security communication method for multi-hop UAVs under a hybrid attack of interference and eavesdropping, according to an embodiment of the present invention.

[0076] Figure 4 This is a schematic diagram of the structure of a multi-hop UAV network security communication system under a hybrid attack of interference and eavesdropping, according to an embodiment of the present invention.

[0077] Figure 5 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0078] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0079] To address communication security in multi-hop UAV networks, this invention proposes a network security communication method and system for multi-hop UAVs under a hybrid attack of interference and eavesdropping. By introducing UAVs that support role switching and utilizing an external approximation algorithm to solve the problem, a security strategy is derived. This strategy includes rationally selecting secure transmission paths from the source node to the target node and appropriately configuring friendly jammers to ensure the security of each hop path. Furthermore, considering the broadcast characteristics of signals, this invention further controls the transmission power of routing nodes and the interference power of friendly jammers to improve the overall security of the communication system.

[0080] See Figure 1 As shown in the figure, an embodiment of the present invention provides a network security communication method for multi-hop drones under a hybrid attack of interference and eavesdropping, comprising the following steps:

[0081] S101, Sensing the environmental situation, including the status of the legitimate drone and the attacker, the distance between the legitimate drone and the attacker, and the channel gain;

[0082] S102, Construct a communication security optimization model with multiple constraints and coupling;

[0083] S103, Reconstruct the objective function for the multi-constraint coupled communication security optimization model;

[0084] S104, The objective function is solved iteratively based on the external approximation algorithm.

[0085] For details, see Figure 2 As shown, the secure communication scenario considered in this invention is comprised of... Ground controller , A legal drone and The attack drones consist of several groups, including any legitimate drone. Arbitrary attacker drone The network topology of the legitimate drone swarm and the positions of the attacker's drones remain constant. Considering long-distance transmission, the ground controller... Select a secure path within the legitimate drone network topology to send business data to the legitimate drones. Attackers launched a combined attack of eavesdropping and interference on the transmission process.

[0086] In step S101, the status of the legitimate drones and the attacker is obtained in the following way. In the legitimate drone swarm, besides the legitimate drones... In addition, each legal drone Selectable roles include message sender, message receiver, idle, or friendly jammer. A friendly jamming decision variable is introduced. ,in, Indicating legal drones In idle state Indicating legal drones Acting as a friendly jammer to perform friendly interference against attackers, with a friendly jamming power of [value missing]. Consider nodes and nodes The communication status between them introduces routing decision variables. ,in, Represents a node and nodes They do not communicate with each other. Represents a node Give nodes Sending service data, with a transmission power of The nodes include legitimate drones and ground controllers. and This refers to the collection of all legal drones and ground controllers, if... Represents a node and Selected as a node in the safe path Give The sending power of the message is Similarly, attacker drones can also choose to launch eavesdropping or jamming attacks, thus introducing decision variables. To represent the attacker's drone The state in which, Indicates attacker drone Launch an eavesdropping attack. Indicates attacker drone Initiate a jamming attack with a jamming power of In step S101, the distance between the legitimate drone and the attacker is obtained in the following way: A three-dimensional Cartesian coordinate system is established, and the ground controller... The horizontal coordinate is legal drones The horizontal coordinate is Fixed flight altitude is attacker drone The horizontal coordinate is Fixed flight altitude is The ground controller can be determined. With legal drones Distance between Ground controller With attacker drones Distance between legal drones and legal drones Distance between legal drones and attacker drones Distance between .

[0087] In step S101, the channel gain is obtained in the following way. Assuming all devices in the scenario are equipped with only one omnidirectional antenna, and the antenna gain of the omnidirectional antenna is constant, a legal UAV is defined. The antenna gain is attacker drone The antenna gain is Ground controller The antenna gain is Given the antenna gain and range, in an air-to-air model, the node... and nodes The channel gain between them is:

[0088]

[0089] in, It is the reference gain coefficient of the Loss Channel. This is the path loss exponent of the Loss-of-Sight (LoS) channel. In the ground-to-air model, the ground controller... With nodes The channel gain between them is:

[0090]

[0091] in, According to the ground controller With nodes Angle of elevation between The baseline gain coefficient obtained after calculating the Loss probability. For ground controller With nodes Angle of elevation between The path loss exponent is obtained after calculating the Loss of Path (LoS) probability.

[0092] Specifically, the construction of the multi-constraint coupled communication security optimization model in S102 is achieved in the following way. In the security path, if When, then the routing node and routing nodes The communication channel capacity between them is:

[0093]

[0094]

[0095] in, It is the bandwidth of the communication channel. This refers to noise in the environment. In this scenario, it's assumed that each channel has the same bandwidth. However, if there is an attacker in the environment... During an eavesdropping attack, the routing node and eavesdropping drones The eavesdropping channel capacity between them is:

[0096]

[0097]

[0098] If multiple attackers launch eavesdropping attacks simultaneously in an environment, the maximum eavesdropping channel capacity in the environment is defined as:

[0099]

[0100] Ultimately, routing nodes can be defined. and routing nodes The confidentiality rate of the communication process is:

[0101]

[0102] Further extending single-hop communication to multi-hop communication, the security of business data transmission in a multi-hop secure path depends on the minimum single-hop communication confidentiality rate. Therefore, the optimization objective is to maximize the minimum confidentiality rate in the secure path, which is the objective function:

[0103]

[0104] in, The solution set for the final selection of routing nodes. To ultimately select the solution set of the friendly jammer, The set of interference power solutions for each friendly jammer. Send the power solution set to the routing node.

[0105] Specifically, S103 includes relaxation and reconstruction of the mixed integer optimization problem. Observing the objective function, firstly, for the Max-Min problem, an auxiliary variable can be introduced. And add a constraint:

[0106]

[0107] Perform equivalent substitution, where This represents the minimum confidentiality rate in the path. It is a constant. Therefore, the objective function can be equivalently replaced by:

[0108]

[0109] because contain and is a non-smooth and non-differentiable function, therefore the problem needs further restructuring. For ,when At that time, the constraint becomes:

[0110]

[0111] And because This represents the minimum confidentiality rate throughout the entire path, and therefore can be omitted. .when At that time, the constraint becomes:

[0112]

[0113] when much smaller hour, Even if the value is negative, this constraint is still satisfied, so it can be omitted directly. .for Introduce an auxiliary variable Indicates in Send business data to During the process, the maximum eavesdropping capacity in the environment. Therefore, it can be used and the following constraints:

[0114]

[0115] Refactor the optimization problem:

[0116]

[0117] in, This is the set of maximum eavesdropping channel capacities across all single-hop paths.

[0118] Specifically, in step S104, the optimization problem is solved iteratively based on an external approximation algorithm. For this objective problem, the variables to be optimized include integer variables and continuous variables, where the integer variables include the friendly interference decision variable. and routing decision variables Continuous variables include friendly interference power variables. Transmit power variable And the maximum eavesdropping channel capacity of all single-hop paths in the secure path. Therefore, this problem is a mixed-integer nonlinear programming (MINLP) problem, and we consider using the external approximation (OA) algorithm to solve it. The OA algorithm divides the MINLP problem into a main problem and subproblems. The subproblems are nonlinear programming (NLP) problems obtained by fixing the integer variables in the original problem, while the main problem is a mixed-integer linear programming (MILP) problem obtained by removing all nonlinear constraints from the original problem.

[0119] Initialization parameters, including the upper bound The lower realm Precision threshold and maximum number of iterations Define a set of integer solutions that satisfy the constraints. Substitute this into the subproblem, solve the subproblem to obtain a set of solutions. This indicates that after selecting the path and the friendly jammer, optimization was achieved to obtain a jamming power of [value missing]. The transmission power is At that time, it can maximize the minimum confidentiality rate along the entire path. And the maximum eavesdropping channel capacity in the environment is Update the Nether Based on the solutions to the subproblems, a linear approximation of the nonlinear constraints is constructed using Taylor expansion, and this approximation is added to the main problem for solution, yielding the fixed integer variables of the subproblems in the next iteration. and continuous variables Update the upper boundary .calculate The value, if or the number of iterations is greater than If the condition is met, the iteration stops; otherwise, iterate through the subproblems and the main problem until the termination condition is met. The final solution is the path with the minimum confidentiality maximized.

[0120] In summary, please refer to the methodology and process. Figure 3 As shown.

[0121] See Figure 4 The diagram shown is a structural schematic of a multi-hop UAV network security communication system under a hybrid attack of interference and eavesdropping according to an embodiment of the present invention, comprising:

[0122] The environmental perception module 401 perceives the environmental situation, including the status of the legitimate drone and the attacker, the distance between the legitimate drone and the attacker, and the channel gain.

[0123] Model building module 402 constructs a multi-constraint coupled communication security optimization model;

[0124] The objective function reconstruction module 403 reconstructs the objective function of the multi-constraint coupled communication security optimization model.

[0125] The objective function solving module 404 iteratively solves the objective function based on an external approximation algorithm.

[0126] See Figure 5 The diagram shown illustrates the hardware structure of an electronic device according to an embodiment of the present invention, including a processor 501 and a memory 502. The memory 502 stores computer execution instructions, and the processor 501 executes the computer execution instructions stored in the memory to implement the various steps performed by the electronic device in the above embodiment. For details, please refer to the relevant descriptions in the foregoing method embodiments.

[0127] Alternatively, the memory 502 can be either standalone or integrated with the processor 501.

[0128] When the memory 502 is set up independently, the electronic device also includes a bus 503 for connecting the memory 502 and the processor 501.

[0129] This invention also provides a computer storage medium storing computer execution instructions, which, when executed by a processor, implement the method described above.

[0130] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0131] In the embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0132] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0133] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0134] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0135] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0136] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0137] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0138] The aforementioned storage medium can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium accessible to general-purpose or special-purpose computers.

[0139] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. Both the processor and the storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic device or host device.

[0140] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A network security communication method for multi-hop unmanned aerial vehicles (UAVs) under a hybrid attack of jamming and eavesdropping, characterized in that, Includes the following steps: Sensing the environmental situation, including the status of legitimate drones and attackers, the distance between legitimate drones and attackers, and channel gain; Construct a communication security optimization model with multiple constraints and coupling; For the aforementioned multi-constraint coupled communication security optimization model, reconstruct the objective function; The objective function is solved iteratively based on an external approximation algorithm.

2. The method for network security communication of multi-hop UAVs under a hybrid attack of interference and eavesdropping as described in claim 1, characterized in that, The status of the legitimate drone and the attacker is obtained through the following steps: Introducing friendly interference decision variables ,in, Indicating legal drones In idle state Indicating legal drones Acting as a friendly jammer to perform friendly interference against attackers, with a friendly jamming power of [value missing]. ; Consider legal drones and ground controller ,node and nodes The communication status between them introduces routing decision variables. ,in, Represents a node and nodes They do not communicate with each other. Represents a node Give nodes Sending service data, with a transmission power of The nodes include legitimate drones and ground controllers; Introducing decision variables To represent the attacker's drone The state in which, Indicates attacker drone Launch an eavesdropping attack. Indicates attacker drone Initiate a jamming attack with a jamming power of .

3. The network security communication method for multi-hop UAVs under a hybrid attack of interference and eavesdropping as described in claim 1, characterized in that, The distance between the legitimate drone and the attacker is obtained through the following steps: Establish a three-dimensional Cartesian coordinate system and a ground controller. The horizontal coordinate is legal drones The horizontal coordinate is Fixed flight altitude is attacker drone The horizontal coordinate is Fixed flight altitude is ; Determine the ground controller With legal drones Distance between Ground controller With attacker drones Distance between legal drones and legal drones Distance between legal drones and attacker drones Distance between .

4. The network security communication method for multi-hop UAVs under a hybrid attack of interference and eavesdropping as described in claim 1, characterized in that, The channel gain is obtained through the following steps: Assuming all devices in the scenario are equipped with only one omnidirectional antenna, and the antenna gain of the omnidirectional antenna is constant, a legal drone is defined. The antenna gain is attacker drone The antenna gain is Ground controller The antenna gain is Given the antenna gain and range, consider a legal unmanned aerial vehicle (UAV) in an air-to-air model. and attacker drones , can obtain nodes and nodes The channel gain between them is: ； in, It is the reference gain coefficient of the Loss channel. It is the path loss exponent of the Loss-Oriented (LoS) channel; In the ground-to-air model, the ground controller With nodes The channel gain between them is: ； in, According to the ground controller With nodes Angle of elevation between The baseline gain coefficient obtained after calculating the Loss probability. For ground controller With nodes Angle of elevation between The path loss exponent is obtained after calculating the Loss of Path (LoS) probability.

5. The method for network security communication of multi-hop UAVs under a hybrid attack of interference and eavesdropping as described in claim 1, characterized in that, The construction of a multi-constraint coupled communication security optimization model includes the following steps: In the safe path, if Then the routing node and routing nodes The communication channel capacity between them is: ； ； in, It is the bandwidth of the communication channel. It is environmental noise; If there are attackers in the environment During an eavesdropping attack, the routing node and eavesdropping drones The eavesdropping channel capacity between them is: ； ； If multiple attackers launch eavesdropping attacks simultaneously in an environment, the maximum eavesdropping channel capacity in the environment is defined as: ； Finally define the routing node and routing nodes The confidentiality rate of the communication process is: ； Extending single-hop communication into multi-hop communication, the objective function is expressed as: ； in, The solution set for the final selection of routing nodes. To ultimately select the solution set of the friendly jammer, The set of interference power solutions for each friendly jammer. Send the power solution set to the routing node.

6. The method for network security communication of multi-hop UAVs under a hybrid attack of interference and eavesdropping as described in claim 1, characterized in that, The multi-constraint coupled communication security optimization model reconstructs the objective function, including the following steps: For the Max-Min problem, by introducing an auxiliary variable Add a constraint, represented as: ； in, This represents the minimum confidentiality rate in the path. It is a constant; The objective function is equivalently replaced with: ； The optimization problem is further restructured because... ,when At that time, the constraint becomes: ； when At that time, the constraint becomes: ； Therefore, it is directly omitted. ; for Introduce an auxiliary variable Indicates in Send business data to The maximum eavesdropping capacity in the environment during the process is represented by the following constraint: ； Through auxiliary variables Reconstruct the objective function: ； in, This is the set of maximum eavesdropping channel capacities across all single-hop paths.

7. The method for network security communication of multi-hop UAVs under a hybrid attack of interference and eavesdropping as described in claim 1, characterized in that, The iterative solution of the objective function based on the external approximation algorithm includes the following steps: Initialization parameters, including the upper bound The lower realm Precision threshold and maximum number of iterations Define a set of integer solutions that satisfy the constraints. Substitute this into the subproblem, solve the subproblem to obtain a set of solutions. This indicates that after selecting the path and the friendly jammer, optimization was achieved to obtain a jamming power of [value missing]. The transmission power is At that time, it can maximize the minimum confidentiality rate along the entire path. And the maximum eavesdropping channel capacity in the environment is Update the Nether ; Based on the solutions to the subproblems, a linear approximation of the nonlinear constraints is constructed using Taylor expansion, and this approximation is added to the main problem for solution, yielding the fixed integer variables of the subproblems in the next iteration. and continuous variables Update the upper boundary ; calculate The value, if or the number of iterations is greater than If the condition is met, the iteration stops; otherwise, the iteration continues to solve the subproblem and the main problem until the iteration termination condition is met. The final solution is the path with the minimum confidentiality rate that is maximized.

8. A network security communication system for multi-hop unmanned aerial vehicles (UAVs) under a hybrid attack of jamming and eavesdropping, characterized in that, include: The environmental perception module senses the environmental situation, including the status of legitimate drones and attackers, the distance between legitimate drones and attackers, and the channel gain. The model building module constructs a communication security optimization model with multiple constraints and coupling. The objective function reconstruction module reconstructs the objective function of the multi-constraint coupled communication security optimization model. The objective function solving module iteratively solves the objective function based on an external approximation algorithm.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-7.

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