A method for protecting data links of unmanned aerial vehicles from unauthorized access

Abstract

The present invention relates to the technical field of data transmission protection, and specifically to a method for protecting data links of drones from unauthorized access. The method comprises: obtaining control instructions during the cruise process of the drone; obtaining the cruise fixity of each control instruction by combining the difference in the sending time of each control instruction and the same control instruction with the closest sending time and the position difference of the drone; constructing the FP tree corresponding to each control instruction using the control instructions in the neighborhood of each control instruction, and then obtaining the control signal correlation of each control instruction; comprehensively considering the cruise fixity and the control signal correlation, selecting a noise signal and sending it. The present invention improves the security of the drone control signal and prevents unauthorized access.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission protection, and in particular to a method for protecting a data link of an unmanned aerial vehicle from unauthorized access. Background Art

[0002] With the rapid development of drone technology, its application in military reconnaissance, cargo transportation, environmental monitoring, agricultural spraying, media shooting and other fields is becoming more and more extensive. However, the popularity of drones has also brought a series of security issues, especially in the security of data links. Currently, most drone communications use wireless signal transmission. The simplicity and repetitiveness of control commands make them easy to be captured and cracked by malicious attackers, thus causing the risk of unauthorized access.

[0003] Existing UAV communication systems mostly use basic encryption methods, such as symmetric key encryption or asymmetric key encryption, to protect the security of data transmission. However, when a UAV is performing a cruise mission, the cruise route is fixed and the cruise routes are repeated, so the control signals between the UAV and the ground control system have a strong periodicity; in addition, since the control instructions of the UAV are relatively simple, the use of simple encryption methods has a weak communication protection level for the UAV, which is easy to cause the UAV's communication information to be leaked, resulting in unauthorized access to the cruise UAV. Summary of the invention

[0004] In order to solve the problem of unauthorized access to existing drones during cruise communication, the present invention aims to provide a method for protecting the data link of drones from unauthorized access. The technical solution adopted is as follows:

[0005] The present invention provides a method for protecting a data link of an unmanned aerial vehicle from unauthorized access, the method comprising the following steps:

[0006] Obtain the control instructions, the sending time of the control instructions and the location of the drone during the cruise process;

[0007] The cruise fixity of each control instruction is obtained by combining the difference in the sending time of each control instruction and the same control instruction that is sent closest to it and the difference in the position of the UAV;

[0008] The FP tree corresponding to each control instruction is constructed by using the control instructions within the time neighborhood of each control instruction; the control signal correlation degree of each control instruction is obtained according to the access conditions of the nodes on the path in the FP tree and the number of each control instruction; the noise distribution probability of each control instruction is evaluated by combining the cruise fixity and the control signal correlation degree;

[0009] A noise signal is determined based on the noise distribution probability and sent.

[0010] Preferably, the cruise fixity of each control instruction is obtained by combining the difference in sending time between each control instruction and the same control instruction sent closest to it and the difference in the position of the drone, including:

[0011] According to the difference in sending time between each control instruction in the candidate instructions and the same control instruction with the closest sending time during each cruise of the drone, and the difference in position of the drone when each control instruction in the candidate instructions and the same control instruction with the closest sending time during each cruise of the drone, the cruise fixity of the candidate instructions is obtained, and the difference in sending time and the difference in position are both negatively correlated with the cruise fixity;

[0012] The candidate instruction is any control instruction.

[0013] Preferably, constructing the FP tree corresponding to each control instruction by using the control instructions within the time neighborhood of each control instruction of each control instruction comprises:

[0014] According to the control instructions in the time neighborhood of each control instruction in the candidate instructions during all the cruising processes of the UAV, the front FP tree and the back FP tree corresponding to the candidate instructions are respectively constructed;

[0015] The FP tree corresponding to the candidate instruction includes a preceding FP tree corresponding to the candidate instruction and a succeeding FP tree corresponding to the candidate instruction.

[0016] Preferably, the method of constructing a pre-FP tree and a post-FP tree corresponding to the candidate instructions respectively according to the control instructions in the time neighborhood of each control instruction in the candidate instructions during all the cruising processes of the drone includes:

[0017] The preset number of control instructions before each control instruction in the candidate instructions of all the cruising processes of the UAV are recorded as the preceding control instructions of the candidate instructions; the preceding FP tree corresponding to the candidate instructions is constructed using all the preceding control instructions of the candidate instructions;

[0018] The preset number of control instructions following each control instruction in the candidate instructions during all the cruising processes of the UAV are recorded as the follow-up control instructions of the candidate instructions; and the post-FP tree corresponding to the candidate instructions is constructed using all the follow-up control instructions of the candidate instructions.

[0019] Preferably, obtaining the control signal correlation of each control instruction according to the access status of the nodes on the path in the FP tree and the number of each control instruction includes:

[0020] Analyze the number of accesses to nodes on each path in the preceding FP tree corresponding to the candidate instruction and the number of control instructions in the candidate instruction to obtain a first degree of association corresponding to the candidate instruction;

[0021] Analyze the number of accesses to the nodes on each path in the post-FP tree corresponding to the candidate instruction and the number of instructions in the candidate instruction to obtain a second degree of association corresponding to the candidate instruction;

[0022] A control signal correlation degree of the candidate instruction is obtained based on the first correlation degree and the second correlation degree.

[0023] Preferably, the analyzing the number of accesses to the nodes on each path in the preceding FP tree corresponding to the candidate instruction and the number of control instructions in the candidate instruction to obtain the first degree of association corresponding to the candidate instruction includes:

[0024] Calculate the average number of visits to all nodes on all paths in the preceding FP tree corresponding to the candidate instruction;

[0025] The first correlation degree corresponding to the candidate instructions is obtained by combining the average value and the number of control instructions in the candidate instructions, wherein the average value is positively correlated with the first correlation degree, and the number of control instructions in the candidate instructions is negatively correlated with the first correlation degree.

[0026] Preferably, the obtaining the control signal correlation of the candidate instruction based on the first correlation and the second correlation includes:

[0027] An average value of the first correlation degree and the second correlation degree is used as the control signal correlation degree of the candidate instruction.

[0028] Preferably, the comprehensive cruise fixity and control signal correlation to evaluate the noise distribution probability of each control instruction includes:

[0029] The product of the cruise fixity of the candidate instruction and the control signal correlation of the candidate instruction is used as the regularity of the candidate instruction;

[0030] Based on the proportion of the regularity of the candidate instruction to the regularity of all control instructions, the noise distribution probability of the candidate instruction is obtained.

[0031] Preferably, obtaining the noise distribution probability of the candidate instruction based on the proportion of the regularity of the candidate instruction to the regularity of all control instructions includes:

[0032] Calculate the sum of the regularity levels of all control instructions;

[0033] The ratio of the regularity of the candidate instruction to the sum value is used as the noise distribution probability of the candidate instruction.

[0034] Preferably, determining the noise signal based on the noise distribution probability and sending it comprises:

[0035] Generate a corresponding random number according to the noise distribution probability of each control instruction;

[0036] Noise is selected and sent according to the random number and the noise distribution probability of each control instruction.

[0037] The present invention has at least the following beneficial effects:

[0038] The present invention takes into account that the signal regularity caused by the high repeatability and high signal dependence of the control instructions of the UAV when performing the cruise mission is strong, and the communication information of the UAV is easily accessed by unauthorized access. The present invention analyzes the control instruction information sent in combination with the sending time of the control instructions during the cruise of the UAV and the position of the UAV. Since the route of the UAV is often fixed during the cruise, the control instructions sent are relatively simple, and the sent instructions have certain similarities, that is, the location and time of sending the same control instruction during the cruise are relatively fixed. Therefore, firstly, the cruise fixity of each control instruction is evaluated in combination with the difference in the sending time of each control instruction and the same control instruction with the closest sending time and the difference in the position of the UAV. Then, the FP tree corresponding to each control instruction is constructed using the control instructions in the time neighborhood of each control instruction of each control instruction. The FP tree can reflect the dependency relationship between multiple control instructions. Further, the noise distribution probability of the control instruction is determined according to the access situation of the nodes on the path in the FP tree. Finally, the noise signal is randomly selected and sent based on the noise distribution probability. The method provided by the present invention sends the selected noise signal to cover the regularity of the original real signal, thereby improving the security of the UAV control signal and avoiding the signal of the UAV from being cracked and causing unauthorized access. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A flowchart of a method for protecting a data link of a drone from unauthorized access provided by an embodiment of the present invention;

[0041] Figure 2 A flowchart of a method for obtaining noise distribution probability provided by an embodiment of the present invention;

[0042] Figure 3 A structural block diagram of a protection system for unauthorized access to a data link of an unmanned aerial vehicle provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, a method for protecting a data link from unauthorized access for a drone proposed in accordance with the present invention is described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0044] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0045] The following is a detailed description of a method for protecting a data link of a drone from unauthorized access provided by the present invention with reference to the accompanying drawings.

[0046] An embodiment of a method for protecting a drone from unauthorized access to its data link:

[0047] The specific scenario targeted by this embodiment is: the existing UAV communication system mostly uses basic encryption methods, such as symmetric key encryption or asymmetric key encryption, when the ground control system encrypts the control instructions of the UAV to protect the security of data transmission. However, when the UAV is performing a cruise mission, since the cruise route is often fixed and the routes of multiple cruises are repeated, the control signals between the UAV and the ground control system have a strong periodicity; in addition, since the control instructions of the UAV are relatively simple, the communication protection level of the UAV using a simple encryption method is relatively weak, which is easy to cause the communication information of the UAV to be leaked, thereby causing the cruise UAV to be unauthorizedly accessed. This embodiment will analyze the control instruction information of the UAV during the cruise process, determine the noise distribution probability of each control instruction, and then select the appropriate noise for sending, that is, add random noise to the sent control instructions to prevent the communication information of the UAV from being leaked.

[0048] This embodiment proposes a method for protecting the data link of a drone from unauthorized access. Figure 1 As shown, a method for protecting a data link of a drone from unauthorized access in this embodiment includes the following steps:

[0049] Step S1, obtaining the control instructions, the sending time of the control instructions and the position of the drone during the cruise process.

[0050] First, the communication log between the ground control system and the UAV is used to collect the historical communication records between the ground control system and the UAV within a preset time period, which includes multiple cruise processes, each cruise process includes multiple control instructions, and the log includes the sending time of each control instruction. The timestamp of the first instruction (take-off instruction) of each cruise process is used as the time starting point, and the time difference between the timestamp of each communication in the cruise process and the time starting point is used as the cruise time of each communication instruction. Among them, the preset time period is a set of all historical moments whose time interval with the current moment is less than or equal to the preset time length. In this embodiment, the preset time length is 1 month. In specific applications, the implementer can set it according to specific circumstances.

[0051] During the cruising process of the UAV, the ground control system can understand the position of the UAV in real time based on the UAV's GPS module and its own GPS module, and the GPS position of the UAV during historical cruising will also be saved, so the position of the UAV can be obtained when the UAV sends each control command.

[0052] At this point, the control instructions, the sending time of the control instructions, and the location information of the drone during the cruise within the preset time period are obtained.

[0053] Step S2, combining the difference in sending time between each control instruction and the same control instruction with the closest sending time and the difference in the position of the UAV, obtains the cruise fixity of each control instruction.

[0054] When the ground control system and the UAV communicate, the operation of the UAV is directly controlled by the UAV control signal, and the control command of the UAV is relatively simple, so the control signal of the UAV is at great risk of being cracked. In order to prevent the control command from being cracked, this embodiment will cover up the real control command of the UAV by sending a noise signal when the control command communication is not carried out between the ground control system and the UAV, thereby reducing the possibility of the UAV communication being obtained and cracked.

[0055] Since the control instructions sent by the drone during the cruise process have certain similarities, that is, the location and time of sending the same control instruction during the cruise process are relatively fixed, the difference in the sending time of each control instruction and the same control instruction sent most recently and the difference in the location of the drone can reflect the cruise fixation of each control instruction. This embodiment will evaluate the cruise fixation of each control instruction in combination with the difference in the sending time of each control instruction and the same control instruction sent most recently and the difference in the location of the drone.

[0056] A control instruction is used as an example for description below. Other types of control instructions can be processed using the method provided in this embodiment.

[0057] Specifically, any control instruction is recorded as a candidate instruction, and the cruise fixity of the candidate instruction is obtained according to the difference in sending time between each control instruction in the candidate instruction and the same control instruction with the closest sending time during each cruise of the UAV, and the difference in position of the UAV when each control instruction in the candidate instruction and the same control instruction with the closest sending time during each cruise of the UAV, and the difference in sending time and the position difference are both negatively correlated with the cruise fixity.

[0058] Among them, the negative correlation relationship means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by practical applications.

[0059] In this embodiment, a specific calculation formula for the cruise fixity is given, and the specific calculation formula for the cruise fixity of the k-th control instruction is:

[0060]

[0061] in, represents the cruise fixity of the kth control instruction, U represents the number of cruises of the UAV within the preset time period, V represents the number of control instructions in the kth control instruction sent by the UAV during the cruise process within the preset time period, It indicates the sending time of the vth control instruction in the kth control instruction during the uth cruise of the UAV. It represents the sending time of the same control instruction that is closest to the sending time of the vth control instruction in the kth control instruction during the uth cruise of the UAV. It represents the position of the UAV when the vth control instruction in the kth control instruction is sent during the uth cruise of the UAV. It represents the position of the UAV during the u-th cruise when the same control instruction is sent as the v-th control instruction in the k-th control instruction. express and position difference.

[0062] It represents the time difference between the sending time of the vth control instruction in the kth control instruction during the uth cruise and the sending time of the same control instruction that is closest to it. The larger the value, the greater the time difference between the two. and The specific method for obtaining the position difference is: and The Euclidean distance between the position coordinates of and The larger the value, the farther the distance between the drones is when the two control instructions are sent; the method for obtaining the Euclidean distance is a prior art and will not be described in detail here. It should be noted that all control instructions in the same control instruction are the same.

[0063] The smaller the difference in sending time between each control instruction in the kth control instruction and the same control instruction that is sent most recently, and the smaller the difference in position of the UAV between each control instruction in the kth control instruction and the same control instruction that is sent most recently, it means that the time and place of sending the kth control instruction are more fixed during the UAV cruising process, that is, the cruising fixity of the kth control instruction is greater.

[0064] By adopting the above method, the cruise fixity of each control instruction can be obtained.

[0065] Step S3, constructing an FP tree corresponding to each control instruction using the control instructions within the time neighborhood of each control instruction; obtaining the control signal correlation of each control instruction according to the access conditions of the nodes on the path in the FP tree and the number of each control instruction; and evaluating the noise distribution probability of each control instruction by combining the cruise fixity and the control signal correlation.

[0066] When a UAV is performing a cruise mission, its flight control usually consists of two control signals: a cruise route control signal and a real-time obstacle avoidance control signal.

[0067] Since the UAV cruise route is highly repetitive, the cruise route control signal that controls the UAV to fly along the cruise path is also highly repetitive during multiple cruises. The cruise route control signal has a strong regularity during multiple cruises and requires a higher degree of protection.

[0068] The real-time obstacle avoidance control signal is a real-time control made by the ground control system when it detects obstacles around the drone or other factors that affect the cruise. Therefore, the real-time obstacle avoidance control signal does not have a strong periodic regularity during multiple cruises. However, since the obstacle avoidance actions are usually similar, there may be a strong correlation between multiple similar control instructions. At this time, the correlation between the control instructions is strong, and the required protection level is also high.

[0069] Based on this, the control instructions within the time neighborhood of each control instruction are analyzed, and then the noise distribution probability of each control instruction is evaluated in combination with the cruise fixity of each control instruction.

[0070] Step S31 , constructing a pre-FP tree and a post-FP tree corresponding to each control instruction by using the control instructions within the time neighborhood of each control instruction.

[0071] This embodiment is described below by still taking candidate instructions as an example, and other types of control instructions can be processed by the method provided in this embodiment.

[0072] Specifically, a preset number of control instructions before each control instruction in the candidate instructions during all the cruising processes of the drone within a preset time period are recorded as the preceding control instructions of the candidate instructions; all the preceding control instructions of the candidate instructions are used to construct the preceding FP tree corresponding to the candidate instructions. It should be noted that the dependency relationship of the preceding FP tree is a reverse time relationship. A preset number of control instructions after each control instruction in the candidate instructions during all the cruising processes of the drone within a preset time period are recorded as the following control instructions of the candidate instructions; all the following control instructions of the candidate instructions are used to construct the following FP tree corresponding to the candidate instructions. In this embodiment, the preset number is 5. In specific applications, the implementer can set it according to the specific situation. The preceding control instructions and the following control instructions are the control instructions within the time neighborhood of the candidate instructions.

[0073] By adopting the above method, the pre-FP tree and post-FP tree corresponding to each control instruction can be obtained.

[0074] Step S32, obtaining the control signal association degree of each control instruction according to the access status of the nodes on the path in the FP tree and the number of each control instruction.

[0075] The FP tree can reflect the dependency between multiple control instructions, that is, the order of control instructions. Therefore, the more paths in the FP tree, the more times each node on the path is visited, indicating that the dependency between the control instruction and other control instructions is stronger and the dependency pattern is more concentrated. Based on this, the control signal correlation degree of each control instruction is obtained according to the visit status of the nodes on the path in the preceding FP tree and the following FP tree corresponding to the candidate instruction and the number of each control instruction.

[0076] Specifically, the average number of accesses to all nodes on all paths in the preceding FP tree corresponding to the candidate instruction is calculated; the average number is combined with the number of control instructions in the candidate instruction to obtain a first degree of association corresponding to the candidate instruction, the average number of accesses to all nodes on all paths in the preceding FP tree is positively correlated with the first degree of association, and the number of control instructions in the candidate instruction is negatively correlated with the first degree of association. The average number of accesses to all nodes on all paths in the following FP tree corresponding to the candidate instruction is calculated; the average number is combined with the number of control instructions in the candidate instruction to obtain a second degree of association corresponding to the candidate instruction, the average number of accesses to all nodes on all paths in the following FP tree is positively correlated with the second degree of association, and the number of control instructions in the candidate instruction is negatively correlated with the second degree of association.

[0077] Among them, a positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. The specific relationship can be a multiplication relationship, an addition relationship, or the power of an exponential function; a negative correlation means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by actual application.

[0078] In this embodiment, specific calculation formulas for the first correlation and the second correlation are given, and the specific calculation formulas for the first correlation and the second correlation of the k-th control instruction are respectively:

[0079]

[0080] in, represents the first association degree of the k-th control instruction, R represents the number of paths on the preceding FP tree corresponding to the k-th control instruction, represents the number of nodes on the rth path of the preceding FP tree corresponding to the kth control instruction, represents the number of visits to the p-th node on the r-th path on the preceding FP tree corresponding to the k-th control instruction, represents the number of control instructions in the kth control instruction, represents the second association degree of the k-th control instruction, S represents the number of paths on the post-FP tree corresponding to the k-th control instruction, represents the number of nodes on the sth path of the post-FP tree corresponding to the kth control instruction, Indicates the number of visits to the qth node on the sth path on the post-FP tree corresponding to the kth control instruction.

[0081] It is used to represent the average number of visits to all nodes on all paths in the preceding FP tree corresponding to the kth control instruction. It is used to represent the average number of visits to all nodes on all paths in the post-FP tree corresponding to the k-th control instruction. The more times the nodes in the FP tree are visited, the more concentrated the rules of the control instructions are, and the stronger the correlation is; the more the total number of node visits on the path in the FP tree corresponding to the k-th control instruction is, and the more control instructions in the k-th control instruction are, the higher the repetition of the path is, the more obvious the signal dependency is, and the stronger the corresponding correlation is.

[0082] By adopting the above method, the first correlation degree and the second correlation degree of each control instruction can be obtained. Next, the control signal correlation degree of each control instruction is determined by combining the first correlation degree and the second correlation degree. Specifically, for any control instruction, the average value of the first correlation degree of the control instruction and the second correlation degree of the control instruction is taken as the control signal correlation degree of the control instruction.

[0083] At this point, the above method can be used to obtain the control signal correlation of each control instruction during all cruise processes of the drone within a preset time period.

[0084] Step S33, comprehensively considering the cruise fixity and the control signal correlation, and evaluating the noise distribution probability of each control instruction.

[0085] Considering that the cruise fixity of control instructions and the correlation of control signals reflect the statistical laws of control instructions, this statistical law is not conducive to the protection and confidentiality of UAV control signals. The laws of these signals can be concealed by sending noise signals. Since the noise signal is replaced by each historical control signal, the stronger the regularity of each control signal, the higher the probability of the control signal appearing in the noise signal should be, so that the true law of the control signal can be better concealed. Therefore, the cruise fixity of control instructions and the correlation of control signals are combined to evaluate the noise distribution probability of each control instruction.

[0086] Next, we will still use the candidate instruction as an example to explain. Specifically, the product of the cruise fixity of the candidate instruction and the control signal correlation of the candidate instruction is used as the regularity of the candidate instruction. The larger the cruise fixity and the larger the control signal correlation, the stronger the regularity of the candidate instruction. By using this method, the regularity of each control instruction can be obtained, and each control instruction corresponds to a regularity. The sum of the regularity of all control instructions is calculated; the ratio of the regularity of the candidate instruction to the sum is used as the noise distribution probability of the candidate instruction.

[0087] Using the above method, the noise distribution probability of each control instruction can be obtained, such as Figure 2 As shown, the figure is a flow chart of the method for obtaining noise distribution probability.

[0088] Step S4: determine a noise signal based on the noise distribution probability and send it.

[0089] In the above steps, the noise distribution probability of each control instruction is obtained. Next, a noise signal will be selected and sent based on the noise distribution probability to cover up the real control instructions of the drone and prevent the real control instructions of the drone from being cracked during the cruising process.

[0090] During control communication between the ground control system and the UAV, when no control command is sent, a random signal is sent according to the noise distribution probability calculated above.

[0091] The noise distribution probability of the control instruction is [0, 1]. A corresponding random number is generated according to the noise distribution probability of each control instruction, and the random number has a value of [0, 1]. Noise is selected according to the random number and the range corresponding to different noises, and then the noise instruction is sent.

[0092] It is known that the UAV ground control system and the control instructions of the UAV are usually 32-byte control signals, of which the first 31 bytes are status bits and the last byte is a CRC check code. The CRC check code of the transmitted noise signal is inverted, and the noise is identified by the error matching of the CRC check code to avoid the influence of the noise signal.

[0093] At this point, the above method is used to complete the selection of random noise and send it to cover up the real control instructions of the drone and prevent the real control instructions of the drone from being accessed without authorization during the cruise process.

[0094] In this embodiment, the signal regularity is strong due to the high repeatability and high signal dependence of the control instructions of the UAV when performing the cruise mission, and the communication information of the UAV is easy to be accessed without authorization. In this embodiment, the control instruction information sent is analyzed in combination with the sending time of the control instructions during the cruise of the UAV and the position of the UAV. Since the route of the UAV is often fixed during the cruise, the control instructions sent are relatively simple, and the instructions sent have certain similarities, that is, the location and time of sending the same control instructions during the cruise are relatively fixed. Therefore, the difference in sending time of each control instruction and the same control instruction closest to its sending time and the unauthorized access are first combined. According to the difference in the positions of humans and machines, the cruise fixity of each control instruction is evaluated, and then the FP tree corresponding to each control instruction is constructed by using the control instructions within the time neighborhood of each control instruction. The FP tree can reflect the dependency relationship between multiple control instructions, and further determine the noise distribution probability of the control instruction according to the access situation of the nodes on the path in the FP tree. Finally, based on the noise distribution probability, a noise signal is randomly selected and sent. The method provided in this embodiment sends the selected noise signal to cover the regularity of the original real signal, thereby improving the security of the drone control signal and avoiding the drone signal from being cracked, resulting in unauthorized access.

[0095] An embodiment of a protection system for unauthorized access to a data link of a drone:

[0096] See also Figure 3 , which shows a structural block diagram of a protection system for unauthorized access to the data link of a drone provided by an embodiment of the present invention. The system may include a data acquisition module, a cruise fixity acquisition module, a noise distribution probability acquisition module and a noise signal sending module.

[0097] Among them, the data acquisition module is used to obtain the control instructions, the sending time of the control instructions and the location of the drone during the cruise process;

[0098] A cruise fixity acquisition module, used to obtain the cruise fixity of each control instruction by combining the difference in sending time between each control instruction and the same control instruction that is sent closest to it and the difference in the position of the UAV;

[0099] A noise distribution probability acquisition module is used to construct an FP tree corresponding to each control instruction using control instructions within a time neighborhood of each control instruction of each control instruction; obtain a control signal correlation degree of each control instruction according to the access status of nodes on the path in the FP tree and the number of each control instruction; and evaluate the noise distribution probability of each control instruction by combining the cruise fixity and the control signal correlation degree;

[0100] The noise signal sending module is used to determine the noise signal based on the noise distribution probability and send the noise signal.

[0101] It should be understood that Figure 3 The structural block diagram of a protection system for unauthorized access to the data link of a drone and its modules shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art will understand that the above methods and systems can be implemented using computer executable instructions and / or included in processor control codes, such as such codes provided on carrier media such as disks, CDs or DVD-ROMs, programmable memories such as read-only memories (firmware), or data carriers such as optical or electronic signal carriers. The system and its modules of this specification can be implemented not only by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software implemented by various types of processors, and can also be implemented by a combination of the above hardware circuits and software (e.g., firmware).

[0102] For more details about the above modules, please refer to other places in this manual (for example Figure 1 , Figure 2 part and its related description), which will not be repeated here.

[0103] In other embodiments, a device is also provided, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the above-mentioned method for protecting the data link of a drone from unauthorized access. The device can be specifically a chip, a component or a module, and the chip may include a connected processor and a memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the method for protecting the data link of a drone from unauthorized access provided in the above embodiment.

[0104] In other embodiments, a computer program product is also provided. When the computer program product is run on a computer, the computer executes the above-mentioned related steps to implement a method for protecting the data link of a drone from unauthorized access provided in the above-mentioned embodiment.

[0105] In other embodiments, a computer-readable storage medium is also provided, in which a computer program code is stored. When the computer program code is executed on a computer, the computer executes the above-mentioned related method steps to implement a method for protecting unauthorized access to a data link of a drone provided in the above embodiment.

[0106] Among them, the provided systems, devices, computer program products, and computer-readable storage media are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above and will not be repeated here.

[0107] It should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for protecting a drone's data link from unauthorized access, characterized in that: The method comprises the following steps: Obtain the control instructions, the sending time of the control instructions and the location of the drone during the cruise process; The cruise fixity of each control instruction is obtained by combining the difference in the sending time of each control instruction and the same control instruction that is sent closest to it and the difference in the position of the UAV; The FP tree corresponding to each control instruction is constructed by using the control instructions within the time neighborhood of each control instruction; the control signal correlation degree of each control instruction is obtained according to the access conditions of the nodes on the path in the FP tree and the number of each control instruction; the noise distribution probability of each control instruction is evaluated by combining the cruise fixity and the control signal correlation degree; Determine a noise signal based on the noise distribution probability and send it; The determining a noise signal based on the noise distribution probability and sending the noise signal comprises: Generate a corresponding random number according to the noise distribution probability of each control instruction; Noise is selected according to the random number and the noise distribution probability of each control instruction, and the selected noise is added to the control instruction to be sent, and then sent.

2. A method for protecting a drone's data link from unauthorized access according to claim 1, characterized in that: The cruise fixity of each control instruction is obtained by combining the difference between the sending time of each control instruction and the same control instruction that is sent closest to it and the difference in the position of the UAV, including: According to the difference in sending time between each control instruction in the candidate instructions and the same control instruction with the closest sending time during each cruise of the drone, and the difference in position of the drone when each control instruction in the candidate instructions and the same control instruction with the closest sending time during each cruise of the drone, the cruise fixity of the candidate instructions is obtained, and the difference in sending time and the difference in position are both negatively correlated with the cruise fixity; The candidate instruction is any control instruction.

3. A method for protecting a drone's data link from unauthorized access according to claim 2, characterized in that: The constructing the FP tree corresponding to each control instruction by using the control instructions within the time neighborhood of each control instruction of each control instruction includes: According to the control instructions in the time neighborhood of each control instruction in the candidate instructions during all the cruising processes of the UAV, the front FP tree and the back FP tree corresponding to the candidate instructions are respectively constructed; The FP tree corresponding to the candidate instruction includes a preceding FP tree corresponding to the candidate instruction and a succeeding FP tree corresponding to the candidate instruction.

4. A method for protecting a drone's data link from unauthorized access according to claim 3, characterized in that: The method of constructing a pre-FP tree and a post-FP tree corresponding to each control instruction in the candidate instructions in all the cruising processes of the drone according to the control instructions in the time neighborhood of each control instruction, respectively, includes: The preset number of control instructions before each control instruction in the candidate instructions of all the cruising processes of the UAV are recorded as the preceding control instructions of the candidate instructions; the preceding FP tree corresponding to the candidate instructions is constructed using all the preceding control instructions of the candidate instructions; The preset number of control instructions following each control instruction in the candidate instructions during all the cruising processes of the UAV are recorded as the follow-up control instructions of the candidate instructions; and the post-FP tree corresponding to the candidate instructions is constructed using all the follow-up control instructions of the candidate instructions.

5. A method for protecting a drone's data link from unauthorized access according to claim 3, characterized in that: The obtaining, according to the access conditions of the nodes on the path in the FP tree and the quantity of each control instruction, the control signal association degree of each control instruction comprises: Analyze the number of accesses to nodes on each path in the preceding FP tree corresponding to the candidate instruction and the number of control instructions in the candidate instruction to obtain a first degree of association corresponding to the candidate instruction; Analyze the number of accesses to the nodes on each path in the post-FP tree corresponding to the candidate instruction and the number of instructions in the candidate instruction to obtain a second degree of association corresponding to the candidate instruction; A control signal correlation degree of the candidate instruction is obtained based on the first correlation degree and the second correlation degree.

6. A method for protecting a drone's data link from unauthorized access according to claim 5, characterized in that: The analyzing the number of accesses to the nodes on each path in the preceding FP tree corresponding to the candidate instruction and the number of control instructions in the candidate instruction to obtain the first correlation corresponding to the candidate instruction includes: Calculate the average number of visits to all nodes on all paths in the preceding FP tree corresponding to the candidate instruction; The first correlation degree corresponding to the candidate instructions is obtained by combining the average value and the number of control instructions in the candidate instructions, wherein the average value is positively correlated with the first correlation degree, and the number of control instructions in the candidate instructions is negatively correlated with the first correlation degree.

7. A method for protecting a drone's data link from unauthorized access according to claim 5, characterized in that: The obtaining the control signal correlation of the candidate instruction based on the first correlation and the second correlation comprises: An average value of the first correlation degree and the second correlation degree is used as the control signal correlation degree of the candidate instruction.

8. A method for protecting a drone's data link from unauthorized access according to claim 2, characterized in that: The step of comprehensively evaluating the cruise fixity and the control signal correlation to determine the noise distribution probability of each control instruction includes: The product of the cruise fixity of the candidate instruction and the control signal correlation of the candidate instruction is used as the regularity of the candidate instruction; Based on the proportion of the regularity of the candidate instruction to the regularity of all control instructions, the noise distribution probability of the candidate instruction is obtained.

9. A method for protecting a drone's data link from unauthorized access according to claim 8, characterized in that: The obtaining of the noise distribution probability of the candidate instruction based on the proportion of the regularity of the candidate instruction to the regularity of all control instructions includes: Calculate the sum of the regularity levels of all control instructions; The ratio of the regularity of the candidate instruction to the sum value is used as the noise distribution probability of the candidate instruction.

Images