A method for encrypted transmission of satellite positioning data of a marine vessel

Abstract

The present application relates to the technical field of ship data encryption, and particularly relates to a kind of encryption transmission method of offshore ship satellite positioning data.The present application determines the optimum time delay based on the correlation degree of standard power load data and standard motion state data in monitoring period, and uses it to reconstruct the phase of standard power load data and standard motion state data, determines the fluid power confidence of monitoring period based on the trajectory feature formed by the reconstructed data;Determine the transmission key based on the cycle serial number of each monitoring period and the fluid power confidence of its last monitoring period;Transmission message of monitoring period is constructed based on the data transmission mode determined by fluid power confidence, and it is encrypted and transmitted using transmission key.The fluid power confidence determined based on the input-output lag effect of fluid medium resists GNSS spoofing attack from the source, and the dynamically balanced supervision effectiveness and communication cost can be realized by the transmission message and transmission key adaptively generated.

Description

Technical Field

[0001] This invention relates to the field of ship data encryption technology, specifically to a method for encrypted transmission of satellite positioning data of ships at sea. Background Technology

[0002] The navigation safety and shore-based management of modern ocean-going vessels heavily rely on maritime satellite communication networks. Ships transmit Global Navigation Satellite System (GNSS) positioning data back to shore monitoring centers via onboard terminals to enable trajectory tracking, energy consumption management, and compliance review. However, existing ship positioning data transmission mechanisms face two interrelated technical challenges.

[0003] First, the physical layer vulnerability of GNSS signals and the threat of advanced deception. The publicly available structure and weak power of civilian GNSS signals allow attackers to carry out deception attacks using low-cost software-defined radio devices. In particular, advanced GNSS simulators can generate false radio frequency signals that perfectly conform to ship kinematics (such as continuous and smooth changes in speed, heading, and turning radius), inducing shipborne receivers to output incorrect but "reasonable" coordinates. Traditional defense methods, such as receiver autonomous integrity monitoring or verification relying on inertial navigation systems, may fail when receiver firmware is hijacked or subjected to physical bypass injection attacks, making it impossible for monitoring centers to verify whether the data originates from real physical motion processes. Second, the contradiction between the bandwidth limitations of maritime satellite communications and the need for continuous monitoring. Maritime satellite link bandwidth is scarce and expensive. To control costs, ships generally adopt a low-frequency intermittent reporting strategy, which creates significant monitoring blind spots on the timeline, providing a window of opportunity for trajectory tampering or violations. If all data is uploaded to increase monitoring density, communication costs will increase dramatically, making it difficult to meet the requirements of commercial operation.

[0004] The existing patent document CN119521208A discloses a ship monitoring method based on BeiDou satellite and AIS data. Specifically, it acquires AIS data from the ship itself and surrounding vessels, and uses a deep learning-based data encryption algorithm to encrypt the AIS data to identify and filter out invalid or irrelevant ship information. The encrypted AIS data packets are then sent to an AIS data center via a BeiDou satellite communication array for decoding and analysis to obtain the ship's position, speed, heading, and other AIS data. However, existing technologies assume that the received AIS or GNSS data is inherently authentic and reliable. Their security mechanisms focus solely on protecting the transmission link, lacking the ability to verify the physical authenticity of the data source. They cannot verify whether the positioning data originates from actual ship movement, thus rendering them ineffective against advanced signal spoofing attacks. Furthermore, their data compression methods are unrelated to the ship's real-time physical safety status, failing to achieve an optimal dynamic balance between monitoring effectiveness and communication costs. Summary of the Invention

[0005] To address the technical problem of effectively identifying spurious ship positioning data conforming to kinematic laws under low-bandwidth communication constraints, the present invention aims to provide an encrypted transmission method for marine ship satellite positioning data. The specific technical solution adopted is as follows: One embodiment of the present invention provides a method for encrypted transmission of satellite positioning data of ships at sea, the method comprising: The system acquires ship power load data and ship motion status data at each moment within each monitoring cycle, and preprocesses the two types of data to obtain standard power load data and standard motion status data. The optimal time delay is determined based on the correlation between standard power load data and standard motion state data within each monitoring cycle; The optimal time delay is used to reconstruct the phase of the standard dynamic load data and standard motion state data at each moment in each monitoring cycle. Based on the trajectory characteristics formed by the reconstructed data pairs, the hydrodynamic confidence level of each monitoring cycle is determined. A transmission key is determined based on the cycle number of each monitoring cycle and the hydrodynamic confidence level of the previous monitoring cycle; a transmission message for each monitoring cycle is constructed based on the data transmission mode determined by the hydrodynamic confidence level; and the transmission message is encrypted and transmitted using the transmission key.

[0006] Furthermore, determining the optimal time delay includes: The standard power load data and standard motion state data at each moment in each monitoring cycle are arranged in time sequence to obtain the standard power load data sequence and the standard motion state data sequence. Calculate the cross-correlation function values ​​of the standard power load data sequence and the standard motion state data sequence under each delay value within the preset time delay search range, and select the delay value corresponding to the largest cross-correlation function value as the optimal time delay for each monitoring cycle.

[0007] Further, determining the hydrodynamic confidence level for each monitoring cycle includes: The ratio of the optimal time delay to the time interval between two adjacent moments is rounded to obtain the number of lag sampling points for each monitoring cycle; The standard power load data at time i within each monitoring cycle and the data at time i... The standard motion state data at each moment constitute a data pair; where the value of i ranges from 1 to 1. d is the number of delayed sampling points for each monitoring period, and N is the total number of time points within each monitoring period; A two-dimensional coordinate system is constructed with standard power load data as the horizontal axis and standard motion state data as the vertical axis. The standard power load data and standard motion state data of all data pairs in each monitoring cycle are marked in the two-dimensional coordinate system to obtain the coordinate points of the corresponding data pairs. Connect the coordinate points in the two-dimensional coordinate system sequentially according to the time sequence of the corresponding data pairs, and connect the data pairs at the two endpoints with straight lines to form a closed trajectory; Calculate the area of ​​the closed trajectory and determine whether the area is greater than zero. If it is, use the area as the effective hysteresis feature for each monitoring cycle; otherwise, set the effective hysteresis feature for each monitoring cycle to zero. The effective hysteresis characteristic is normalized to obtain the hydrodynamic confidence level for each monitoring cycle.

[0008] Further, determining the transmission key includes: The confidence scores of the fluid dynamics in the previous monitoring period are multiplied and rounded to obtain the confidence seed for each monitoring period. Using the confidence seed as the salt value and combining it with the period number of each monitoring period, the transmission key for the corresponding monitoring period is obtained using the key derivation function.

[0009] Furthermore, the construction of the transmission message for each monitoring cycle includes: If the hydrodynamic confidence level for each monitoring cycle is greater than or equal to a preset confidence threshold, a transmission message is constructed from the ship motion state data and the hydrodynamic confidence level for the corresponding monitoring cycle. If the hydrodynamic confidence level for each monitoring cycle is less than a preset confidence threshold, a transmission message is constructed from the ship motion status data, standard power load data, standard motion status data, and hydrodynamic confidence level for the corresponding monitoring cycle.

[0010] Furthermore, before preprocessing the two types of data, the following steps are also included: Calculate the fluctuation intensity index of ship motion status data at all times within each monitoring cycle; Determine whether the fluctuation intensity index is less than a preset quiescent threshold. If so, set the hydrodynamic confidence level of each monitoring cycle to a preset default high confidence level, where the preset default high confidence level is greater than the preset confidence threshold. If not, the ship's power load data and ship motion status data at each moment within each monitoring cycle are preprocessed.

[0011] Furthermore, the method for encrypted transmission also includes: When the receiving end detects that the number of consecutive decryption failures exceeds a preset limit, or that the transmission key for each monitoring period cannot be recovered through the backtracking algorithm, a handshake reset process is triggered. In the handshake reset process, an initial random number seed is generated by negotiating using an asymmetric encryption channel, and the hydrodynamic confidence of the previous monitoring period is updated using the initial random number seed to generate the transmission key for each monitoring period.

[0012] Furthermore, the absolute difference between two adjacent delay values ​​within the preset time delay search range is the time interval between two adjacent moments within the monitoring period.

[0013] Furthermore, the wave intensity index is the standard deviation of the ship motion state data at all times within each monitoring period.

[0014] Furthermore, the preset upper limit is 3 times.

[0015] The present invention has the following beneficial effects: Firstly, by utilizing the unique input-output hysteresis effect of fluid media as a physical fingerprint, and extracting the physical hysteresis characteristics between standard dynamic load data and standard motion state data, a fluid dynamic confidence level reflecting dissipation and nonlinearity is obtained. This introduces a fluid dynamic verification dimension that is difficult to be faked by GNSS simulators, thereby effectively identifying false positioning data that only conforms to kinematic laws but lacks real physical interaction characteristics. This helps to defend against advanced GNSS spoofing attacks that can generate perfect motion trajectories from the physical source.

[0016] Secondly, the data transmission mode is constructed based on the adaptive determination of hydrodynamic confidence, which enables satellite bandwidth resources to be prioritized for suspicious or high-risk periods. This ensures the authenticity of all-time supervision while achieving the optimal dynamic balance between supervision effectiveness and communication costs.

[0017] Thirdly, by fusing the time-unique periodic sequence number with the physically unclonable hydrodynamic confidence level, a dynamic transmission key is generated. This key is then used to encrypt the transmitted message, ensuring not only the time-series security and anti-replay capability of the transmitted message, but also preventing attackers from deceiving the system by simply cracking the algorithm or replaying historical data. This creates a closed-loop enhanced protection for physical layer verification at the communication layer. Attached Figure Description

[0018] To more clearly illustrate the technical solutions and advantages 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating the steps of an encrypted transmission method for satellite positioning data of a ship at sea, provided in one embodiment of the present invention; Figure 2 A system structure diagram of an encrypted transmission system for satellite positioning data of ships at sea, provided in one embodiment of the present invention; Figure 3 This is a schematic diagram of a computer device for encrypted transmission of satellite positioning data of a ship at sea, provided as an embodiment of the present invention. Detailed Implementation

[0020] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method for encrypted transmission of satellite positioning data of ships at sea proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0021] Unless otherwise defined, 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 pertains.

[0022] The following description, in conjunction with the accompanying drawings, details a specific scheme for an encrypted transmission method of satellite positioning data for maritime vessels provided by the present invention.

[0023] Example 1: This invention proposes an encrypted transmission method for satellite positioning data of ships at sea. Please refer to [link / reference]. Figure 1 The diagram illustrates a flowchart of the steps in an embodiment of the present invention for an encrypted transmission method of satellite positioning data for maritime vessels, the method comprising: Step S1: Obtain the ship's power load data and ship motion status data at each moment in each monitoring cycle, and preprocess the two types of data to obtain standard power load data and standard motion status data.

[0024] The entire operating period of the ship's edge equipment, from power-on startup and initialization to power-off shutdown or restart, is evenly divided into multiple monitoring cycles. Each monitoring cycle includes at least one or more complete ship dynamic motion processes (such as minor acceleration / deceleration adjustments or wave disturbance responses). In this embodiment of the invention, the duration of the monitoring cycle is set to 60 seconds, but the implementer can set it according to specific circumstances.

[0025] The ship's power load data is read at the first sampling time of each monitoring cycle by connecting to the ship's engine control system or main engine monitoring and alarm system via a hardwired connection. This power load data characterizes the source of the ship's motion and typically includes propeller speed, main engine output power percentage, or throttle command value. The ship's motion state data at the second sampling time of each monitoring cycle is obtained by connecting to the ship's onboard global navigation satellite system receiver (such as a GPS or BeiDou receiver) via a serial interface using NMEA-0183 format messages. This data represents the ship's actual motion after being excited and experiencing water damping and inertia, and typically includes satellite positioning speed measurement, ground speed, accelerometer readings, and Doppler log readings. In this embodiment, propeller speed is selected as the ship's power load data, and ground speed is selected as the ship's motion state data.

[0026] It should be noted that the sampling rate of ship power load data is limited by the industrial bus bandwidth and polling mechanism of the engine control system, and is usually lower than that of GNSS motion status data serving the high-precision real-time navigation requirements. In this embodiment of the invention, the sampling rate of ship power load data is set to 0.5 Hz, and the sampling rate of ship motion status data is 1 Hz. Implementers can set these rates according to specific circumstances.

[0027] GNSS receivers provide high-precision, high-stability, and globally unified satellite time synchronization, and they themselves possess a second-pulse hard synchronization signal. However, the engine system may experience local clock drift or bus transmission jitter. Therefore, using the second sampling time of the ship's motion state data as a reference, a linear interpolation algorithm is used to resample the ship's power load data at each of the first sampling times within each monitoring cycle, obtaining the ship's power load data at each second sampling time, thus achieving strict alignment of the two data sets in the time domain. In the following text, the second sampling time will be referred to as a "time".

[0028] In this embodiment of the invention, the fluctuation intensity index of the ship motion state data at all times within each monitoring cycle is calculated; it is determined whether the fluctuation intensity index is less than a preset silent threshold. If so, the hydrodynamic confidence level of each monitoring cycle is set to a preset default high confidence level, which is greater than a preset confidence threshold. If not, the ship power load data sequence and the ship motion state data sequence are preprocessed.

[0029] It should be noted that, in this embodiment of the invention, the standard deviation of the ship's motion state data at all times within each monitoring cycle is used as the fluctuation intensity index. When the fluctuation intensity index is less than a preset silence threshold, it indicates that the ship is in a near-stationary drifting or extremely stable constant-speed navigation state. The microscopic hydrodynamic characteristics excited by the water environment may be submerged by sensor noise and environmental background noise. To avoid calculating incorrect hydrodynamic confidence based on noise, the hydrodynamic confidence is set to a preset default high confidence level greater than the preset confidence threshold, thereby ensuring that the ship automatically enters an efficient lightweight transmission mode during most normal and stable navigation periods. When the fluctuation intensity index is greater than or equal to the preset silence threshold, it indicates that the ship is currently experiencing sufficiently strong dynamic excitation or environmental disturbance. Its dynamic load and motion state data contain significant and extractable hydrodynamic characteristics. A preprocessing method for both types of data is required, as detailed below: Ship power load data and ship motion state data are recorded as analytical data. For each type of analytical data, the average of the analytical data from the M time points preceding each time point within the monitoring period is calculated to obtain the trend data for each time point. The difference between the analytical data and the trend data at each time point within the monitoring period is used as fluctuation data, thereby achieving detrending. Since ship power load data and ship motion state data have different physical dimensions, and the fluctuation amplitude varies greatly under different sea states, Z-score standardization is used to standardize the analytical data at each time point within the monitoring period based on the analytical data from each time point within the working period to obtain standard data. The standard data corresponding to ship power load data and ship motion state data are recorded as standard power load data and standard motion state data, respectively. Here, M is set to 5, and the implementer can set it according to the specific situation. The trend data for the first M time points within the first monitoring period is set to be the same as that for the (M+1)th time point.

[0030] In this embodiment of the invention, ship motion state data are collected at various times within multiple monitoring cycles when the ship is in a stable cruising or drifting state. The fluctuation intensity index of these monitoring cycles is calculated, and the characteristic high quantile (e.g., 95th percentile) of these fluctuation intensity indices is used as a preset silence threshold. The method for obtaining the fluctuation intensity index of these monitoring cycles is the same as that used during working hours. Multiple ships of the same type as the ship to be monitored are selected, and under a safe environment confirmed to be free from deception interference, a sample set of ship power load data and ship motion state data covering stationary, cruising, maneuvering, and different sea state levels is collected. Using the same calculation method as the hydrodynamic confidence level in this scheme, the hydrodynamic confidence level for each monitoring cycle in the sample set is obtained. The probability density distribution curve of the hydrodynamic confidence level for all samples is plotted. On the probability density distribution curve, the quantile value corresponding to a preset cumulative probability (e.g., 5%) is selected as the preset confidence threshold. In this embodiment, the preset confidence threshold is preferably set to 0.8 to ensure a high detection rate while ensuring that the ship can remain stably in a lightweight transmission mode during most normal navigation periods.

[0031] Step S2: Determine the optimal time delay based on the correlation between standard power load data and standard motion state data within each monitoring cycle.

[0032] Because the propulsion system's motion is influenced by the large inertia and viscous damping of the fluid medium, there is a significant physical delay between the two on the time axis. Without first identifying and compensating for this physical delay, directly comparing data at the same moment will lead to causal misalignment, making it impossible to extract effective physical coupling characteristics. The correlation between standard power load data and standard motion state data reveals the similarity between the power load waveform and the motion state waveform under different delay conditions. This allows us to determine the true response time difference between the propulsion system and the hull motion under the current sea state and navigation conditions—the optimal time delay. This ensures that the subsequently constructed spatial trajectory accurately reflects the nonlinear characteristics of the hydrodynamic system, thus providing a solid physical basis for distinguishing between true and false data.

[0033] Step S3: Use the optimal time delay to perform phase reconstruction on the standard dynamic load data and standard motion state data at each moment in each monitoring cycle. Based on the trajectory characteristics formed by the reconstructed data pairs, determine the hydrodynamic confidence level for each monitoring cycle.

[0034] To compensate for the motion state lag caused by the inertia of the fluid medium, phase reconstruction is performed on standard dynamic load data and standard motion state data using an optimal time delay. This logically re-pairs the misaligned excitation and response data on the time axis, thereby restoring the physical causal relationship between the system input and output. The trajectory characteristics formed by the reconstructed data pairs can quantify the essential hydrodynamic properties of energy dissipation, yielding a hydrodynamic confidence score. Essentially, the hydrodynamic confidence score utilizes the unique "input-output" nonlinear hysteresis effect of the fluid medium as a physical fingerprint for identifying GNSS spoofing, effectively distinguishing between physically consistent ship motion data and spurious simulation data that only fits trajectories at the kinematic level.

[0035] Step S4: Determine the transmission key based on the cycle number of each monitoring cycle and the hydrodynamic confidence level of the previous monitoring cycle; construct the transmission message for each monitoring cycle based on the data transmission mode determined by the hydrodynamic confidence level; encrypt the transmission message using the transmission key.

[0036] This scheme employs a dynamic key generation mechanism that integrates periodicity and hydrodynamic confidence, aiming to achieve dual security guarantees of temporal uniqueness and physical non-cloning. Periodicity imbues the key with time-varying properties, ensuring forward security; hydrodynamic confidence forces attackers to possess the ability to forge messages based on real-time simulations of complex fluid physical states, thus achieving anti-replay and anti-tampering at the encryption level. The dynamic key constructed by integrating these two mechanisms prevents attackers from predicting future keys by cracking algorithmic patterns or deceiving the system by replaying historical messages, completely blocking the data injection path of simulator attacks. Simultaneously, the adaptive determination of the transmission mode based on hydrodynamic confidence maximizes the use of limited satellite bandwidth resources while ensuring the authenticity of the data source, achieving an optimal dynamic balance between regulatory effectiveness and communication costs. Finally, the transmission key is used to encrypt the transmitted messages, completing a closed-loop protection from underlying physical feature verification to secure data transmission at the application layer.

[0037] In this embodiment of the invention, based on each transmission key, the AES-GCM (Advanced Encryption Standard-Galois / Counter Mode) algorithm is used to encrypt the transmission messages for that period. Upon receiving the encrypted data packet, the receiving end uses the same transmission key and the corresponding decryption algorithm to authenticate and decrypt the received data packet.

[0038] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the optimal time delay includes: arranging the standard power load data and standard motion state data at each moment in each monitoring cycle according to the time sequence to obtain the standard power load data sequence and the standard motion state data sequence; calculating the cross-correlation function values ​​of the standard power load data sequence and the standard motion state data sequence under each delay value within a preset time delay search range, and selecting the delay value corresponding to the largest cross-correlation function value as the optimal time delay for each monitoring cycle.

[0039] It should be noted that a larger cross-correlation function value indicates a greater similarity in the fluctuations of the standard power load data sequence and the standard motion state data sequence, given the time lag between the power load data and motion state data. This also suggests a higher probability that changes in the power load data are the cause of changes in the motion state data. The optimal time delay represents the true response time difference between the ship's propulsion system and hull motion under the current sea state and navigation conditions.

[0040] In one implementation of this invention, the preset time delay search range is: The upper limit of this search range Pre-settings are required based on the ship's tonnage and the physical response characteristics of its propulsion system. For smaller ships with lower inertia, It can be set to 15 seconds; however, for large oil tankers or container ships with enormous inertia, the physical delay between a change in propeller output power and a significant change in ship speed is relatively long. It can be set to 40 seconds or even longer to ensure coverage of the actual delay range. Starting from the lower limit of the preset time delay search range, it iterates sequentially with a preset step size until the upper limit of the preset time delay search range is reached, obtaining multiple delay values. The preset step size is the time interval between two adjacent moments within the monitoring period.

[0041] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the hydrodynamic confidence level includes: rounding the ratio of the optimal time delay to the time interval between two adjacent moments to obtain the number of hysteresis sampling points for each monitoring cycle; and using the standard dynamic load data at the i-th moment in each monitoring cycle and the... The standard motion state data at each moment constitute a data pair; where the value of i ranges from 1 to 1. d represents the number of lag sampling points for each monitoring cycle, and N represents the total number of time points within each monitoring cycle. A two-dimensional coordinate system is constructed with standard dynamic load data as the horizontal axis and standard motion state data as the vertical axis. Standard dynamic load data and standard motion state data for all data pairs within each monitoring cycle are labeled in the two-dimensional coordinate system to obtain the coordinate points of the corresponding data pairs. The coordinate points in the two-dimensional coordinate system are connected sequentially according to the time sequence of the corresponding data pairs, and the data pairs at two endpoints are connected by straight lines to form a closed trajectory. The area of ​​the closed trajectory is calculated, and it is determined whether the area is greater than zero. If it is, the area is used as the effective lag feature quantity for each monitoring cycle; otherwise, the effective lag feature quantity for each monitoring cycle is set to zero. The effective lag feature quantity is normalized to obtain the hydrodynamic confidence level for each monitoring cycle. The rounding operation is a rounding operation to the nearest integer.

[0042] It should be noted that in a real fluid environment, there is an objective time delay between the change in dynamic load and the change in the ship's motion state due to overcoming the inertia and resistance of the water. Furthermore, the dynamic load is the excitation source, and the motion state is the response result. To eliminate the influence of this delay, an optimal time delay is introduced for phase shifting, comparing the standard dynamic load data at time i with the data at time j. The standard motion state data at each moment are realigned, and the trajectory purely reflects the lag characteristics. However, within a finite time period, the ship's acceleration and deceleration process is often incomplete, resulting in a trajectory obtained by sequentially connecting coordinate points that is usually an open curve segment. To rigorously quantify the degree of lag enclosed by this curve, the last coordinate point of the trajectory is connected to the first coordinate point with a straight line, forcibly forming a closed trajectory. In a specific implementation of this invention, the area of ​​the closed trajectory for each monitoring cycle is calculated using the Discrete Green's Theorem. This can be expressed as a formula:

[0043] In the formula, M is the total number of data pairs participating in the construction of the closed trajectory for each monitoring period, and Where N is the total number of time points in each monitoring period, and d is the number of lag sampling points in each monitoring period; The x-coordinate of the first data pair in each monitoring cycle; The x-coordinate of the coordinate point of the nth data pair within each monitoring cycle; The x-coordinate of the coordinate point of the (n+1)th data pair in each monitoring cycle; The x-coordinate of the coordinate point of the Mth data pair within each monitoring cycle; The ordinate of the coordinate point of the first data pair in each monitoring cycle; The ordinate of the coordinate point of the nth data pair within each monitoring cycle; The ordinate of the coordinate point of the (n+1)th data pair in each monitoring cycle; The ordinate of the coordinate point of the Mth data pair within each monitoring cycle.

[0044] In a ship's propulsion system, changes in power load are the cause, and changes in motion state are the result. Furthermore, changes in power load necessarily precede changes in motion state in time, causing the closed trajectory to follow a clockwise rotation direction, resulting in a positive area of ​​the closed trajectory. When the area of ​​the closed trajectory is negative, it indicates that the data does not conform to physical causality (possibly random noise generated by the simulator), and the effective hysteresis characteristic is set to zero. In one implementation of this invention, the formula for calculating the hydrodynamic confidence level is as follows:

[0045] In the formula, Fluid dynamic confidence level for each monitoring cycle; The effective hysteresis characteristic for each monitoring period; exp is an exponential function with the natural constant as the base. This is the preset sensitivity; the larger the value, the more sensitive the confidence level is to changes in the effective hysteresis feature. This represents the threshold offset. It should be noted that the effective hysteresis characteristics of the monitored vessel are collected when it is navigating normally in a deception-free environment, and the mean of all effective hysteresis characteristics is calculated. Set threshold offset That is, 30% of the normal level is used as the 0.5 dividing line; Ensure the function is in Approaching 0 When it is close to 0 Approximately equal to hour Close to 1. The hydrodynamic confidence score, ranging from 0 to 1, represents the confidence level that the data source conforms to the laws of hydrodynamics. A higher hydrodynamic confidence score indicates that the data has significant fluid characteristics, and the greater the likelihood that the motion state data is real navigation data; conversely, a lower score indicates that the data characteristics are weak or chaotic, and may originate from a simulator or be in an abnormal state.

[0046] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the transmission key includes: performing multiplication amplification and rounding operations on the hydrodynamic confidence of the previous monitoring cycle for each monitoring cycle to obtain the confidence seed for each monitoring cycle; using the confidence seed as the salt value, combined with the cycle number of each monitoring cycle, and using the key derivation function to obtain the transmission key for the corresponding monitoring cycle.

[0047] It should be noted that ship-based edge devices and shore-based servers may use different hardware architectures or floating-point standards. Directly using floating-point numbers as input to the hash function will result in completely different hash values, creating a cascading effect and causing key negotiation failure. Before calculating the transmission key, a truncation threshold (e.g., retaining 4 decimal places) is pre-defined. After calculating the hydrodynamic confidence score, both the ship-based and shore-based devices first convert it to string form and truncate the first N significant digits, or multiply it by a preset factor (e.g., 10000) and then force it to convert to a long integer. This serves as a unified input benchmark before subsequent multiplication and rounding operations are performed. Specifically, the hydrodynamic confidence score is multiplied by a large preset integer factor (e.g., ...). The algorithm performs a floor function to convert the floating-point feature value into a deterministic integer confidence seed, thus solving the aforementioned problem. Introducing the confidence seed gives the key space high-entropy randomness, effectively preventing replay attacks and data tampering. Combined with a periodicity number, it ensures the time-varying nature of the key. Even if the key is leaked at a certain moment, the change in the periodicity number prevents attackers from using the old key to decrypt subsequent new messages, ensuring continuous communication security.

[0048] It is important to note that for the first monitoring cycle after system startup, since there is no previous cycle, a transmission key is generated using the master key pre-installed in the device's security chip and the cycle number of the first monitoring cycle, thereby completing the cold start initialization of the trust chain. The master key is a high-strength random number pre-stored in the secure unit or encrypted storage area inside the device via an offline secure channel (such as a physical serial port) during the factory configuration or security initialization phase of the encrypted transmission terminal device. It is agreed upon and shared by both the sender and receiver, and is used to provide the initial root of trust during system cold start or key chain reset, ensuring the secure encrypted transmission of the first data.

[0049] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the transmission message includes: if the hydrodynamic confidence level of each monitoring period is greater than or equal to a preset confidence threshold, then the transmission message is constructed from the ship motion state data of the corresponding monitoring period and the hydrodynamic confidence level; if the hydrodynamic confidence level of each monitoring period is less than the preset confidence threshold, then the transmission message is constructed from the ship motion state data, standard power load data, standard motion state data and hydrodynamic confidence level of the corresponding monitoring period.

[0050] It should be noted that if the hydrodynamic confidence level is greater than or equal to the preset confidence threshold, it indicates that the data has significant fluid characteristics and the motion state data is genuine navigation data. In this case, no additional verification is required. Prioritizing cost savings, only ship motion state data with practical business value is selected to construct the message, eliminating redundant verification data, which greatly reduces satellite bandwidth consumption under routine operation. Conversely, if the hydrodynamic confidence level is less than the preset confidence threshold, it means that the physical characteristics exhibited by the data are weak or chaotic, and the possibility of GNSS spoofing attacks or sensor malfunctions cannot be ruled out. In this case, the ship motion state data may be questionable. Prioritizing the security and non-repudiation of supervision, the ship motion state data is packaged and uploaded together with standard power load data and standard motion state data as "verification evidence," so that the shore-based end can conduct in-depth secondary verification and evidence collection based on the full amount of raw data, ensuring the rigor of supervision.

[0051] Key spatiotemporal information (such as longitude, latitude, UTC, speed and heading) is extracted from the ship motion status data at each moment within the monitoring period. This information is then serialized and encoded according to a preset communication protocol format (such as binary structure or JS key-value pair data), and necessary message headers (such as period number, device identification number (ID)) and check bits are added to assemble the transmission message for that monitoring period.

[0052] In this embodiment of the invention, the method for setting the preset confidence threshold includes: selecting multiple ships of the same type as the ship to be monitored, and collecting a sample set of ship power load data and ship motion state data covering stationary, cruising, maneuvering and different sea state levels under a safe environment where there is no deception interference; using the same calculation method as the hydrodynamic confidence of this scheme, obtaining the hydrodynamic confidence of each monitoring period in the sample set; plotting the probability density distribution curve of the hydrodynamic confidence of all samples; and selecting the quantile value corresponding to the preset cumulative probability (e.g., 5%) on the probability density distribution curve as the preset confidence threshold.

[0053] In this embodiment of the invention, when the receiving end detects that the number of consecutive decryption failures exceeds a preset limit, or when it is unable to recover the transmission key for each monitoring period through a backtracking algorithm, a handshake reset process is triggered. In the handshake reset process, an initial random number seed is generated by negotiating using an asymmetric encryption channel, and the hydrodynamic confidence of the previous monitoring period is updated using the initial random number seed to generate the transmission key for each monitoring period.

[0054] It should be noted that, considering the potential for unstable packet loss or system restarts leading to key chain breakage in maritime satellite communication links, this embodiment employs a self-healing mechanism based on handshake reset. The receiving end (i.e., the shore-based monitoring center) verifies the integrity and authenticity of received messages in real time. If the receiving end detects decryption failure—meaning the transmission message for the monitoring period cannot be correctly decrypted using the transmission key—and attempts to recover the transmission key for the current monitoring period fail via a backtracking algorithm, or if the number of consecutive decryption failures exceeds a preset limit (set to 3 times in this embodiment), then the current chain-based key trust system is deemed invalid. In this case, the receiving end proactively initiates a handshake reset request to the sending end (i.e., the ship). During the handshake reset process, both parties interact using a pre-configured asymmetric encryption channel (such as a secure channel established using the RSA encryption algorithm) to negotiate and generate a new initial random number seed. This seed is a temporarily generated one-time random number, its purpose being to forcibly replace the hydrodynamic confidence level of the previous monitoring period, which cannot be obtained or verified, as the new salt value for the HKDF algorithm, thereby generating the transmission key for the current monitoring period. Normal chain-based encrypted transmission is restored after both parties re-synchronize.

[0055] The failure to recover the transmission key for the current monitoring period using the backtracking algorithm includes the following steps: The receiver searches for the latest seed in its local cache, assuming its corresponding sequence number is Tk, where T is the cycle number of the current monitoring period and k is the number of cycles in which message loss occurred. The receiver then uses the HKDF algorithm, starting with the seed (hydrodynamic confidence level) of these Tk monitoring cycles, and combines it with the known incremental cycle number logic to perform k consecutive forward iterative deduction operations to attempt to calculate the transmission key to be used in the Tth monitoring cycle. If the key for decrypting the transmission message of the current monitoring period can be successfully deduced within the maximum number of iterations allowed by the system, the backtracking is successful; if a match cannot be found after exceeding the maximum number of iterations or the local cache has expired, the transmission key for the current monitoring period cannot be recovered using the backtracking algorithm.

[0056] It should be noted that after updating the hydrodynamic confidence level of the previous monitoring period using the initial random number seed, the same method used to generate the transmission key for each monitoring period is adopted to generate the transmission key based on the hydrodynamic confidence level of the previous monitoring period.

[0057] This invention is now complete.

[0058] Example 2: This invention proposes an encrypted transmission system for satellite positioning data of ships at sea. Please refer to [link / reference]. Figure 2 The diagram illustrates a system architecture of an encrypted transmission system for satellite positioning data of ships at sea, according to an embodiment of the present invention. The system includes: The data acquisition module 510 is used to acquire the ship's power load data and ship motion status data at each moment in each monitoring cycle, and to preprocess the two types of data to obtain standard power load data and standard motion status data. The delay determination module 520 is used to determine the optimal time delay based on the correlation between standard power load data and standard motion state data within each monitoring cycle; The confidence determination module 530 is used to perform phase reconstruction on the standard dynamic load data and standard motion state data at each moment in each monitoring cycle using the optimal time delay, and to determine the hydrodynamic confidence of each monitoring cycle based on the trajectory characteristics formed by the reconstructed data pairs. The encryption module 540 is used to determine the transmission key based on the cycle number of each monitoring cycle and the hydrodynamic confidence level of the previous monitoring cycle; construct the transmission message for each monitoring cycle based on the data transmission mode determined by the hydrodynamic confidence level; and encrypt the transmission message using the transmission key.

[0059] It should be noted that the devices provided in the above embodiments are only illustrative examples of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. In addition, the encrypted transmission system for satellite positioning data of marine vessels and the encrypted transmission method for satellite positioning data of marine vessels provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0060] Example 3: Figure 3 This is a schematic diagram of a computer device for encrypted transmission of satellite positioning data of a maritime vessel, provided as an embodiment of the present invention. Exemplary examples include... Figure 3 As shown, the computer device includes: a memory 601, a processor 602, and a computer program 603 stored in the memory 601 and running on the processor 602, wherein when the processor 602 executes the computer program 603, the computer device can execute any of the encrypted transmission methods for maritime ship satellite positioning data described above.

[0061] Furthermore, embodiments of this application also protect an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform an encrypted transmission method for satellite positioning data of marine vessels provided in embodiments of this application.

[0062] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0063] It should be understood that the apparatus provided in this embodiment is used to execute the above-described method for encrypted transmission of satellite positioning data of ships at sea, and therefore can achieve the same effect as the above-described implementation method.

[0064] When using integrated units, the device may include a processing module and a storage module. When applied to a workpiece, the processing module can be used to control and manage the workpiece's operations. The storage module can be used to support the execution of program code by the workpiece.

[0065] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits contained in conjunction with the disclosure of this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory.

[0066] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0067] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0068] 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 within the protection scope of the present invention.

Claims

1. A method for encrypted transmission of satellite positioning data of ships at sea, characterized in that, The method includes: The system acquires ship power load data and ship motion status data at each moment within each monitoring cycle, preprocesses the two types of data to obtain standard power load data and standard motion status data; the ship motion status data includes satellite positioning data output by the shipborne global navigation satellite system (GNSS) receiver, and the satellite positioning data includes satellite positioning speed measurement data and / or ground speed data; The optimal time delay is determined based on the correlation between standard power load data and standard motion state data within each monitoring cycle; The optimal time delay is used to reconstruct the phase of the standard dynamic load data and standard motion state data at each moment in each monitoring cycle. Based on the trajectory characteristics formed by the reconstructed data pairs, the hydrodynamic confidence level of each monitoring cycle is determined. Based on the cycle number of each monitoring cycle and the hydrodynamic confidence level of the previous monitoring cycle, a transmission key is determined; a transmission message for each monitoring cycle is constructed based on the data transmission mode determined by the hydrodynamic confidence level; and the transmission message is encrypted and transmitted using the transmission key. Determining the hydrodynamic confidence level for each monitoring cycle includes: The ratio of the optimal time delay to the time interval between two adjacent moments is rounded to obtain the number of lag sampling points for each monitoring cycle; The standard power load data at time i within each monitoring cycle and the data at time i... The standard motion state data at each moment constitute a data pair; where the value of i ranges from 1 to 1. d is the number of delayed sampling points for each monitoring period, and N is the total number of time points within each monitoring period; A two-dimensional coordinate system is constructed with standard power load data as the horizontal axis and standard motion state data as the vertical axis. The standard power load data and standard motion state data of all data pairs in each monitoring cycle are marked in the two-dimensional coordinate system to obtain the coordinate points of the corresponding data pairs. Connect the coordinate points in the two-dimensional coordinate system sequentially according to the time sequence of the corresponding data pairs, and connect the data pairs at the two endpoints with straight lines to form a closed trajectory; Calculate the area of ​​the closed trajectory and determine whether the area is greater than zero. If it is, use the area as the effective hysteresis feature for each monitoring cycle; otherwise, set the effective hysteresis feature for each monitoring cycle to zero. The effective hysteresis characteristic is normalized to obtain the hydrodynamic confidence level for each monitoring cycle.

2. The method for encrypted transmission of satellite positioning data of ships at sea according to claim 1, characterized in that, Determining the optimal time delay includes: The standard power load data and standard motion state data at each moment in each monitoring cycle are arranged in time sequence to obtain the standard power load data sequence and the standard motion state data sequence. Calculate the cross-correlation function values ​​of the standard power load data sequence and the standard motion state data sequence under each delay value within the preset time delay search range, and select the delay value corresponding to the largest cross-correlation function value as the optimal time delay for each monitoring cycle.

3. The encrypted transmission method for satellite positioning data of ships at sea according to claim 1, characterized in that, The determination of the transmission key includes: The confidence scores of the fluid dynamics in the previous monitoring period are multiplied and rounded to obtain the confidence seed for each monitoring period. Using the confidence seed as the salt value and combining it with the period number of each monitoring period, the transmission key for the corresponding monitoring period is obtained using the key derivation function.

4. The encrypted transmission method for satellite positioning data of ships at sea according to claim 1, characterized in that, The construction of the transmission message for each monitoring period includes: If the hydrodynamic confidence level for each monitoring cycle is greater than or equal to a preset confidence threshold, a transmission message is constructed from the ship motion status data for the corresponding monitoring cycle and the hydrodynamic confidence level. If the hydrodynamic confidence level for each monitoring cycle is less than a preset confidence threshold, a transmission message is constructed from the ship motion status data, standard power load data, standard motion status data, and the hydrodynamic confidence level for the corresponding monitoring cycle.

5. The encrypted transmission method for satellite positioning data of ships at sea according to claim 4, characterized in that, Before preprocessing the two types of data, the following steps are also included: Calculate the fluctuation intensity index of ship motion status data at all times within each monitoring cycle; Determine whether the fluctuation intensity index is less than a preset quiescent threshold. If so, set the hydrodynamic confidence level of each monitoring cycle to a preset default high confidence level, where the preset default high confidence level is greater than the preset confidence threshold. If not, the ship's power load data and ship motion status data at each moment within each monitoring cycle are preprocessed.

6. The encrypted transmission method for satellite positioning data of ships at sea according to claim 1, characterized in that, The method for encrypted transmission also includes: When the receiving end detects that the number of consecutive decryption failures exceeds a preset limit, or that the transmission key for each monitoring period cannot be recovered through the backtracking algorithm, a handshake reset process is triggered. In the handshake reset process, an initial random number seed is generated by negotiating using an asymmetric encryption channel, and the hydrodynamic confidence of the previous monitoring period is updated using the initial random number seed to generate the transmission key for each monitoring period.

7. The method for encrypted transmission of satellite positioning data of ships at sea according to claim 2, characterized in that, The absolute difference between two adjacent delay values ​​within the preset time delay search range is the time interval between two adjacent moments within the monitoring period.

8. The encrypted transmission method for satellite positioning data of ships at sea according to claim 5, characterized in that, The wave intensity index is the standard deviation of the ship motion state data at all times within each monitoring period.

9. A method for encrypted transmission of satellite positioning data of ships at sea according to claim 6, characterized in that, The preset upper limit is 3 times.

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