A method, system, and storage medium for detecting fake AIS ship trajectories based on time slot conflict detection.

Abstract

This invention provides a method, system, and storage medium for detecting fake AIS ship trajectories based on time slot conflict detection. The method includes: processing AIS data to be analyzed, filtering out AIS data related to the ship to be analyzed, and storing it in a database; organizing AIS data related to the ship to be analyzed according to the corresponding ship; calculating the number of time slot switching times and the specific time slots where time slot conflicts occur for the ship to be analyzed within the analysis period; simulating a specific environment and training correction parameters; statistically analyzing the occurrence of time slot conflicts in the actual broadcast AIS dynamic messages of the target ship, and analyzing the probability that the ship's trajectory is a fake trajectory. This invention addresses the problem that fake broadcasting stations cannot grasp the dynamic message information of other ships that the ship can actually receive during its navigation, i.e., they cannot perform correct SOTDMA time slot access. Through the fake AIS ship trajectory detection method based on time slot conflict detection, it effectively detects some perfectly disguised fake AIS ship trajectories, achieving the goal of accurately identifying illegal ships.

Description

Technical Field

[0001] This invention relates to the field of maritime communication technology, and more particularly to a method, system, and storage medium for detecting false AIS ship trajectories based on time slot conflict detection. Background Technology

[0002] Since the widespread adoption of the Automatic Identification System (AIS), all vessels at sea are required to be equipped with AIS systems. Law enforcement agencies deploy AIS base stations along the coast to monitor the real-time trajectory information of various vessels and detect violations. Therefore, some vessels, when engaging in illegal operations, will turn off their own AIS dynamic information broadcasting while simultaneously broadcasting false AIS vessel trajectories from the shore, fabricating complete vessel trajectories to evade real-time monitoring by AIS base stations. Figure 3 As shown, the dashed circles represent the AIS data reception range of each device; when the violating vessel arrives at point A, it shuts down the AIS dynamic message, and at the same time, the fake broadcasting station starts broadcasting the fake route. After completing the illegal operation, when it arrives at point B, it starts broadcasting the dynamic message, and at the same time, the fake broadcasting station stops broadcasting the fake route in order to create a complete route trajectory to evade big data analysis and inspection.

[0003] In response to the above situation, law enforcement agencies have used methods such as signal strength detection, off-site data reception detection, and rationality analysis of ship dynamic data (analyzing parameters such as sailing speed, sailing direction, number of receiving ships, and SOTDMA status) to detect fake AIS ship tracks. Although these methods can detect some fake AIS ship track broadcasting activities, some technically advanced fake broadcasting stations can also use methods such as dynamically changing the transmission power and multiple fake broadcasting stations broadcasting in the field to forge more realistic AIS dynamic messages and broadcast fake navigation tracks to evade detection. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method for detecting fake AIS vessel trajectories based on time slot conflict detection. This invention is based on AIS big data analysis. Fake broadcasting stations cannot access the dynamic message information of other vessels they actually receive during navigation, thus preventing correct SOTDMA time slot access. The fake AIS vessel trajectory detection method based on time slot conflict detection can effectively detect some disguised fake AIS vessel trajectories, achieving the goal of accurately identifying illegal vessels.

[0005] The technical means employed in this invention are as follows:

[0006] A method for detecting fake AIS ship trajectories based on time slot conflict detection includes:

[0007] Process the AIS data to be analyzed, filter out the AIS data related to the ship to be analyzed, and store it in the database;

[0008] Organize the AIS data related to the vessel to be analyzed according to the corresponding vessel;

[0009] Calculate the number of time slot switching times and the specific time slots where time slot conflicts occur for the ship to be analyzed during the analysis period;

[0010] Simulate the specific environment and correct the parameters at the training point;

[0011] The study statistically analyzes the occurrence of time slot conflicts when the target vessel actually broadcasts AIS dynamic messages, and analyzes the probability that the vessel's trajectory is a false trajectory.

[0012] Furthermore, the process of processing the AIS data to be analyzed, filtering out the AIS data related to the ship to be analyzed, and storing it in the database specifically includes:

[0013] Retrieve AIS data for the period to be analyzed from the data center;

[0014] The receiving range of the target vessel is determined based on the number of receiving vessels field in the SOTDMA status information of the AIS dynamic message.

[0015] Filter out ship data within the target ship's reception range during the SOTDMA timeout period;

[0016] The actual broadcast time slots used by the ships to be analyzed were compiled.

[0017] Furthermore, the step of organizing the AIS data related to the vessel to be analyzed according to the corresponding vessel specifically includes:

[0018] Ship data within the target ship's reception range is compiled and filtered according to the ship's MMSI number and the selected SOTDMA timeout period.

[0019] Furthermore, the calculation of the number of time slot switching times of the ship under analysis within the analysis period and the specific time slots where time slot conflicts occur specifically includes:

[0020] Based on the AIS data of the ship to be analyzed, the number of changes is counted, with each SOTDMA time slot timeout reduced to 0 as a unit.

[0021] Furthermore, the statistical analysis of time slot conflicts in the actual broadcast of AIS dynamic messages by the target vessel, and the probability that the vessel's trajectory is a false trajectory, specifically includes:

[0022] Let t be the number of times the ship to be analyzed selects a time slot during the analysis period, and record each SOTDMA timeout as 0. Let n be the number of ships that have time slot conflicts.

[0023] Let m be the number of times the ship and the ship to be analyzed have time slot conflicts, and let S1, S2, ..., S be the distances between the two ships at the time of each time slot conflict. m For each ship that has a time slot conflict with the ship being analyzed, the time slot conflict parameter P is calculated using the following formula:

[0024]

[0025] Where a and b are correction parameters, which are affected by base station layout, waterway distribution and channel load. The channel state of the period to be analyzed is simulated by channel load, base station layout and waterway distribution, and fake ships are generated to train the correction parameters and obtain the values ​​of the correction parameters.

[0026] Based on the formula for calculating the time slot conflict parameter P, the conflict parameters of all relevant ships are calculated and denoted as P1, P2, ..., P k ;

[0027] Based on the conflict parameters of all relevant vessels, the probability Q of the false vessel trajectory of the target vessel is calculated using the following formula:

[0028]

[0029] By calculating the probability Q of the false ship trajectory of the target ship, it is determined whether the ship's navigation trajectory is a false ship trajectory.

[0030] This invention also provides a fake AIS ship trajectory detection system based on time slot conflict detection, implemented using the aforementioned fake AIS ship trajectory detection method. The system includes: a big data processing unit, a ship list processing unit, a ship data processing unit, an environment simulation unit, and a conflict analysis unit, wherein:

[0031] The big data processing unit is used to process the AIS data to be analyzed, filter out the AIS data related to the ship to be analyzed, and store it in the database.

[0032] The vessel list processing unit is used to organize the AIS data related to the vessel to be analyzed according to the corresponding vessel;

[0033] The ship data processing unit to be analyzed is used to calculate the number of time slot switching times and the specific time slots where time slot conflicts occur for the ship to be analyzed during the analysis period.

[0034] The environment simulation unit is used to simulate a specific environment and train correction parameters;

[0035] The conflict analysis unit is used to statistically analyze the time slot conflicts that occur when the target ship actually broadcasts AIS dynamic messages, and to analyze the probability that the ship's trajectory is a false trajectory.

[0036] The present invention also provides a storage medium comprising a stored program, wherein, when the program is executed, the aforementioned method for detecting false AIS ship trajectories based on time slot conflict detection is performed.

[0037] Compared with the prior art, the present invention has the following advantages:

[0038] This invention provides a method for detecting fake AIS ship trajectories based on time slot conflict detection. Based on the SOTDMA time slot access algorithm used in AIS dynamic messages and the original AIS base station data that illegal ships cannot obtain, it can identify the behavior of illegal ships transmitting perfect data near the shore and creating fake ship navigation trajectories.

[0039] Based on the above reasons, this invention can be widely applied in fields such as maritime communication. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart of the method of the present invention.

[0042] Figure 2 This is a system framework diagram provided for an embodiment of the present invention.

[0043] Figure 3 An environmental example provided for an embodiment of the present invention. Detailed Implementation

[0044] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0046] like Figure 1 As shown, this invention provides a method for detecting fake AIS ship trajectories based on time slot conflict detection, including:

[0047] S1. Process the AIS data to be analyzed, filter out the AIS data related to the ship to be analyzed, and store it in the database;

[0048] S2. Organize the AIS data related to the vessel to be analyzed according to the corresponding vessel;

[0049] S3. Calculate the number of time slot switching times and the specific time slots where time slot conflicts occur for the ship to be analyzed during the analysis period;

[0050] S4. Simulate the specific environment and correct the parameters at the training point;

[0051] S5. Statistically analyze the time slot conflicts that occur when the target vessel actually broadcasts AIS dynamic messages, and analyze the probability that the vessel's trajectory is a false trajectory.

[0052] In a specific implementation, as a preferred embodiment of the present invention, step S1, processing the AIS data to be analyzed, filtering out the AIS data related to the ship to be analyzed, and storing it in a database, specifically includes:

[0053] S11. Obtain AIS data for the period to be analyzed from the data center;

[0054] S12. Determine the receiving range of the target vessel based on the number of receiving vessels field in the SOTDMA status information of the AIS dynamic message.

[0055] S13. Filter out the ship data within the target ship's reception range during the SOTDMA timeout period for use by the ship list processing unit;

[0056] S14. Compile the actual broadcast time slots used by the ships to be analyzed for use by the data processing unit of the ships to be analyzed.

[0057] In a specific implementation, as a preferred embodiment of the present invention, step S2 involves organizing the AIS data related to the vessel to be analyzed according to the corresponding vessel, specifically including:

[0058] Ship data within the target ship's reception range is compiled and filtered according to the ship's MMSI number and the selected SOTDMA timeout period.

[0059] In a specific implementation, as a preferred embodiment of the present invention, step S3, calculating the number of time slot switching times of the ship to be analyzed during the analysis period and the specific time slots where time slot conflicts occur, specifically includes:

[0060] Based on the AIS data of the ship to be analyzed, the number of changes is counted, with each SOTDMA time slot timeout reduced to 0 as a unit.

[0061] In a specific implementation, as a preferred embodiment of the present invention, step S4 involves statistically analyzing the time slot conflicts that occur when the target vessel actually broadcasts AIS dynamic messages, and analyzing the probability that the vessel's trajectory is a false trajectory. This specifically includes:

[0062] S41. Let t be the number of times the ship to be analyzed selects a time slot during the analysis period, and record each SOTDMA timeout as 0. Let n be the number of ships that have time slot conflicts.

[0063] S42. Let m be the number of times the ship and the ship to be analyzed have time slot conflicts, and let S1, S2, ..., S be the distances between the two ships at the time of each time slot conflict. m For each ship that has a time slot conflict with the ship being analyzed, the time slot conflict parameter P is calculated using the following formula:

[0064]

[0065] Where a and b are correction parameters, which are affected by base station layout, waterway distribution and channel load. The channel state of the period to be analyzed is simulated by channel load, base station layout and waterway distribution, and fake ships are generated to train the correction parameters (the training target is that the Q value obtained by the fake ships and the real ships are significantly different, and the Q value of the fake ships is above 60%), and the value of the correction parameters is obtained.

[0066] S43. Based on the formula for calculating the time slot conflict parameter P, calculate the conflict parameters of all relevant ships, denoted as P1, P2, ..., P k ;

[0067] S44. Based on the conflict parameters of all relevant vessels, calculate the probability Q of the false vessel trajectory of the target vessel. The calculation formula is as follows:

[0068]

[0069] By calculating the probability Q of the false ship trajectory of the target ship, it is determined whether the ship's navigation trajectory is a false ship trajectory.

[0070] like Figure 2 As shown, corresponding to the method for detecting fake AIS ship trajectories based on time slot conflict detection in this application, this application also provides a system for detecting fake AIS ship trajectories based on time slot conflict detection, including: a big data processing unit, a ship list processing unit, a ship data processing unit to be analyzed, an environment simulation unit, and a conflict analysis unit, wherein:

[0071] The big data processing unit is used to process the AIS data to be analyzed, filter out the AIS data related to the ship to be analyzed, and store it in the database.

[0072] The vessel list processing unit is used to organize the AIS data related to the vessel to be analyzed according to the corresponding vessel;

[0073] The ship data processing unit to be analyzed is used to calculate the number of time slot switching times and the specific time slots where time slot conflicts occur for the ship to be analyzed during the analysis period.

[0074] The environment simulation unit is used to simulate a specific environment and train correction parameters;

[0075] The conflict analysis unit is used to statistically analyze the time slot conflicts that occur when the target vessel actually broadcasts AIS dynamic messages, and to analyze the probability that the vessel's trajectory is a false trajectory. In this embodiment, the conflict analysis unit calculates for the user the probability that the navigation trajectory reported by the analyzed vessel during the analysis period is a false trajectory based on the results obtained from the above units.

[0076] The embodiments of the present invention are described simply because they correspond to those in the embodiments above. For any similarities, please refer to the descriptions in the embodiments above, which will not be elaborated here.

[0077] This application also discloses a computer-readable storage medium storing a computer instruction set, which, when executed by a processor, implements the method for detecting fake AIS ship trajectories based on time slot conflict detection as provided in any of the embodiments above.

[0078] Example

[0079] like Figure 3As shown, law enforcement has deployed three AIS base stations along the shore to cover the coastal area and receive AIS data. When the offending vessel enters position A, it deviates from its course and disables dynamic message broadcasting. Simultaneously, a fake broadcasting station on the shore begins broadcasting false AIS dynamic information to simulate the offending vessel's trajectory. Once the vessel completes its illegal activities and returns to position B, the fake broadcasting station is disabled, and the vessel's normal dynamic message broadcasting resumes. Law enforcement personnel now need to analyze the trajectory of the offending vessel (assuming MMSI number 999999999) from 00:00 to 12:00.

[0080] The big data processing unit retrieves AIS data from 0:00 to 12:00 from the data center and filters the AIS data as follows:

[0081] First, analyze the dynamic data of all ships with MMSI number 999999999. Based on the number of ships reported in the dynamic data, draw a circle with the latitude and longitude information reported in the dynamic data to cover the same number of ships. Then, pass the AIS data of all covered ships to the ship list processing unit and pass the data of the ship with MMSI number 999999999 to the ship data processing unit to be analyzed.

[0082] The vessel list processing unit organizes the relevant AIS data filtered by the big data processing unit according to the vessel MMSI number for use by the conflict analysis section. Here, it is assumed that there are 50 vessels, and each vessel has 4 time slot conflicts with the vessel to be analyzed. The distance between the two vessels at the time of each time slot conflict is 1 nautical mile, 3 nautical miles, 7 nautical miles, and 15 nautical miles.

[0083] The ship data processing unit to be analyzed organizes the AIS data with MMSI number 999999999, and counts the number of times the SOTDMA time slot timeout is reduced to 0 as a unit. Here, it is assumed to be 1000 times. Among these 1000 times, 200 times time slot conflicts occurred.

[0084] The environmental simulation unit simulates a specific environment and trains the correction parameters. Under this condition, the correction parameters trained through environmental simulation are: a = 0.05, b = 0.05.

[0085] The conflict analysis unit statistically analyzes the time slot conflicts that actually occur when the target vessel broadcasts AIS dynamic messages, and analyzes the probability that the vessel's trajectory is a false trajectory. The specific analysis process is as follows:

[0086] Let t = 1000 times the ships to be analyzed select time slots during the analysis period, and record each SOTDMA timeout as 0. Let n = 50 the number of ships that have time slot conflicts.

[0087] Calculate the time slot conflict parameter P for each ship that has a time slot conflict with the ship being analyzed:

[0088]

[0089] Based on the time slot conflict parameters P of all relevant ships, calculate the probability Q of the false ship trajectory of the target ship:

[0090] Q = 18.75 × 50 ÷ 1000 = 94%

[0091] The result was 60% higher than expected, which indicates that the ship's navigation trajectory was a false one, and law enforcement agencies should pay close attention to the vessel.

[0092] In summary, with the continuous improvement of technology, traditional signal-level methods for detecting fake AIS vessel trajectories can be concealed using technological means, and detection based on dynamic report content is gradually becoming ineffective as counter-reconnaissance methods are constantly upgraded. In this situation, this invention utilizes the SOTDMA channel access mechanism of AIS dynamic reporting and the asymmetry of information data to detect fake AIS vessel trajectories. Illegal vessels cannot hide through technical means and are thus exposed.

[0093] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0094] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0095] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0096] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0097] 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 method for detecting fake AIS ship trajectories based on time-slot conflict detection, characterized in that, include: Process the AIS data to be analyzed, filter out the AIS data related to the ship to be analyzed, and store it in the database; Organize the AIS data related to the vessel to be analyzed according to the corresponding vessel; Calculate the number of time slot switching times and the specific time slots where time slot conflicts occur for the ship to be analyzed during the analysis period; Simulate a specific environment to train the correction parameters; The study statistically analyzes the occurrence of time slot conflicts when the target vessel actually broadcasts AIS dynamic messages, and analyzes the probability that the vessel's trajectory is a false trajectory.

2. The method for detecting false AIS ship trajectories based on time slot conflict detection according to claim 1, characterized in that, The process of processing the AIS data to be analyzed, filtering out the AIS data related to the ship to be analyzed, and storing it in the database specifically includes: Retrieve AIS data for the period to be analyzed from the data center; The receiving range of the target vessel is determined based on the number of receiving vessels field in the SOTDMA status information of the AIS dynamic message; Filter out ship data within the target ship's reception range during the SOTDMA timeout period; The actual broadcast time slots used by the ships to be analyzed were compiled.

3. The method for detecting false AIS ship trajectories based on time slot conflict detection according to claim 1, characterized in that, The process of organizing AIS data related to the vessel to be analyzed, according to the corresponding vessel, specifically includes: Ship data within the target ship's reception range are sorted and selected based on the ship's MMSI number and the selected SOTDMA timeout period.

4. The method for detecting false AIS ship trajectories based on time slot conflict detection according to claim 1, characterized in that, The calculation of the number of time slot switching times of the ship under analysis during the analysis period and the specific time slots where time slot conflicts occur specifically includes: Based on the AIS data of the ship to be analyzed, the number of changes is counted, with each SOTDMA time slot timeout reduced to 0 as a unit.

5. The method for detecting false AIS ship trajectories based on time slot conflict detection according to claim 1, characterized in that, The statistics cover the occurrence of time slot conflicts in the actual broadcast of AIS dynamic messages by the target vessel, and analyze the probability that the vessel's trajectory is a false trajectory, specifically including: Let t be the number of times the ship to be analyzed selects a time slot during the analysis period, and record each SOTDMA timeout as 0. Let n be the number of ships that have time slot conflicts. Let m be the number of times the ship and the ship to be analyzed have time slot conflicts, and let S1, S2, ..., S be the distances between the two ships at the time of each time slot conflict. m For each ship that has a time slot conflict with the ship being analyzed, the time slot conflict parameter P is calculated using the following formula: Where a and b are correction parameters, which are affected by base station layout, waterway distribution and channel load. The channel state of the period to be analyzed is simulated by channel load, base station layout and waterway distribution, and fake ships are generated to train the correction parameters and obtain the values ​​of the correction parameters. Based on the formula for calculating the time slot conflict parameter P, the conflict parameters of all relevant ships are calculated and denoted as P1, P2, ..., P k ; Based on the conflict parameters of all relevant vessels, the probability Q of the false vessel trajectory of the target vessel is calculated using the following formula: By calculating the probability Q of the false ship trajectory of the target ship, it is determined whether the ship's navigation trajectory is a false ship trajectory.

6. A false AIS ship trajectory detection system based on time slot conflict detection, implemented according to the false AIS ship trajectory detection method based on time slot conflict detection as described in any one of claims 1-5, characterized in that, include: The system includes a big data processing unit, a ship list processing unit, a ship data processing unit, an environmental simulation unit, and a conflict analysis unit, among which: The big data processing unit is used to process the AIS data to be analyzed, filter out the AIS data related to the ship to be analyzed, and store it in the database. The vessel list processing unit is used to organize the AIS data related to the vessel to be analyzed according to the corresponding vessel; The ship data processing unit to be analyzed is used to calculate the number of time slot switching times and the specific time slots where time slot conflicts occur for the ship to be analyzed during the analysis period. The environment simulation unit is used to simulate a specific environment and train correction parameters; The conflict analysis unit is used to statistically analyze the time slot conflicts that occur when the target ship actually broadcasts AIS dynamic messages, and to analyze the probability that the ship's trajectory is a false trajectory.

7. A storage medium, characterized in that, The storage medium includes a stored program, wherein when the program is executed, it performs the method for detecting false AIS ship trajectories based on time slot conflict detection as described in any one of claims 1 to 5.

Images