A method for intelligent management of trajectory calculation data

Abstract

The present invention relates to the technical field of data encryption processing, and in particular to a method for intelligent management of trajectory calculation data, the method comprising: obtaining data before and after calculation by trajectory software as original data to be managed; selecting data from the original data as initial data; obtaining a character combination sequence and a temporary index table of the initial data, and counting the frequency of occurrence of each character combination in the character combination sequence in the original data as the influence degree of the corresponding character combination; obtaining new characters in the original data, and obtaining an updated character combination based on the new characters and the influence degree of each character combination; disassembling the updated character combination to obtain at least two decomposed character combinations, and obtaining a secondary index sequence of the updated character combination in combination with the original data to obtain an optimized index table; encoding and encrypting the original data according to the optimized index table to obtain ciphertext data for management, thereby improving the data encryption effect and information hiding, and ensuring data security.

Description

Technical Field

[0001] The present invention relates to the technical field of data encryption processing, and in particular to a method for intelligent management of trajectory calculation data. Background Art

[0002] A ballistic calculator, also known as a ballistic application, solver, or engine, converts environmental data and target information into trajectory corrections. Snipers use these calculations to provide accurate long-range shooting parameters. Therefore, ballistic calculations significantly impact the actual use of sniper rifles, leading to the development of ballistic calculations for each country. These calculations contain actual combat parameters for sniper rifles, reflecting the country's sniper rifle parameters and performance. Therefore, ballistic calculation data management requires encryption to prevent malicious access and prevent the leakage of national defense secrets due to the disclosure of sniper rifle parameters.

[0003] The encryption measures for data mainly hide the original data information through data overwriting or data conversion. The commonly used methods are data confusion and data replacement. For example, common data encoding is a data encryption process. However, existing data encoding technologies such as LZW encoding set the correspondence between characters and encodings through original statistical information, so that the encoding sequence contains statistical information corresponding to the plaintext data, resulting in poor hiding effect of the encoding technology on the original data information and poor encryption security. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a method for intelligent management of trajectory calculation data. The technical solutions adopted are as follows:

[0005] An embodiment of the present invention provides a method for intelligent management of trajectory calculation data, the method comprising the following steps:

[0006] Acquire data before and after calculation by the ballistic software as raw data to be managed; select data from the raw data as initial data;

[0007] Acquire a character combination sequence and a temporary index table based on the initial data, and count the occurrence frequency of each character combination in the character combination sequence in the original data as the influence degree of the corresponding character combination;

[0008] Obtaining a new character in the original data, obtaining an updated character combination of the corresponding character combination based on the new character and the influence degree of each character combination in the initial data, and replacing the corresponding character combination with the updated character combination;

[0009] Decomposing the updated character combination to obtain at least two decomposed character combinations, obtaining a secondary index sequence of the updated character combination based on the distribution of each decomposed character combination in the original data, and updating the temporary index table based on the secondary index sequence of each updated character combination to obtain an optimized index table;

[0010] The original data is encoded and encrypted according to the optimized index table to obtain ciphertext data, and the ciphertext data is stored and managed.

[0011] Preferably, the step of selecting data from the original data as initial data includes:

[0012] A preset ratio is set, and data is sequentially selected from the original data according to the preset ratio to obtain initial data.

[0013] Preferably, the step of counting the frequency of occurrence of each character combination in the character combination sequence in the original data as the influence degree of the corresponding character combination includes:

[0014] Constructing partial character combinations of different lengths based on the data characters in the original data, wherein the lengths are changed by incrementing the data characters one by one; determining whether each partial character combination has a corresponding character combination in the character combination sequence, and if not, recording the partial character combination preceding the current partial character combination that has a corresponding character combination in the character combination sequence as the first character combination;

[0015] Obtain all first character combinations in the original data, and obtain the frequency of occurrence of each first character combination based on all first character combinations to obtain the occurrence probability of each first character combination. The occurrence probability of the first character combination is the degree of influence of the first character combination on the corresponding character combination in the character combination sequence.

[0016] Preferably, the step of obtaining the new character in the original data includes:

[0017] The new characters in the original data are character data that do not exist in the initial data.

[0018] Preferably, the step of obtaining an updated character combination corresponding to the character combination based on the new character and the influence degree of each character combination in the initial data comprises:

[0019] Obtain adjacent character combinations adjacent to the new character in the original data, where the adjacent character combinations exist in the character combinations of the initial data; select the adjacent character combination with the greatest influence as the character combination to be merged, and merge the character combination to be merged with the new character to obtain an updated character combination of the character combination to be merged.

[0020] Preferably, the step of obtaining an updated character combination corresponding to the character combination based on the new character and the influence degree of each character combination in the initial data further includes:

[0021] If there are at least two consecutive new characters, first obtain the character combination to be merged of the first new character, and obtain the first updated character combination based on the character combination to be merged of the first new character;

[0022] Taking the first updated character combination as the existing character combination, select the adjacent character combination of the second new character, and the adjacent character combination of the second new character includes the first updated character combination; select the character combination to be merged of the second new character according to the influence degree of the adjacent character combination of the second new character to obtain the second updated character combination; and so on, merge all the consecutive new characters in sequence to obtain the final updated character combination.

[0023] Preferably, the step of disassembling the updated character combination to obtain at least two decomposed character combinations includes:

[0024] The decomposition is performed based on the character combination in the temporary index table, and the decomposed character combination at least includes a new character before the merging of the updated character combination and a character combination to be merged.

[0025] Preferably, the step of obtaining the secondary index sequence of the updated character combination based on the distribution of each decomposed character combination in the original data includes:

[0026] Each of the decomposed character combinations is numbered, the occurrence position of each of the decomposed character combinations in the original data is counted, and the occurrence position is marked with the number of the character combination. The numbers of all marked character combinations in the original data are arranged in sequence to form a secondary index sequence.

[0027] Preferably, the step of encoding and encrypting the original data according to the optimized index table to obtain ciphertext data includes:

[0028] The original data is encoded based on the temporary index table to obtain a coding sequence; the coding corresponding to the decomposed character combination corresponding to each updated character combination in the optimized index table is obtained in the coding sequence, and data encryption is implemented according to the coding of all character combinations to obtain ciphertext data.

[0029] Preferably, the key of the ciphertext data is the optimized index table and the secondary index sequence.

[0030] The present invention has the following beneficial effects: the embodiment of the present invention selects part of the original data to be managed for preliminary analysis, constructs a character combination sequence and a temporary index table based on the initial data, avoids the exposure of information of the index table constructed by all the original data, obtains the influence degree of each character combination through the temporary index table constructed by the initial data, and is used to quantify the influence of the character combination on other character combinations in the original data; then analyzes other data in the original data to obtain new characters in the original data, and merges the new characters with the existing character combinations in the temporary index table corresponding to the initial data to obtain an updated character combination, and the merging process is based on the characters with the greatest influence adjacent to the new character combination. The update character combination is carried out to ensure the influence of the updated character combination in the original data and improve the encryption effect of subsequent encryption; further, since the updated character combination is merged, the updated character combination is disassembled to obtain the decomposed character combination, and the secondary index sequence of each updated character combination is obtained according to the distribution of the decomposed character combination in the original data, and the optimized index table for optimizing the update of the temporary index table is obtained from the secondary index sequence of all updated character combinations, which avoids the situation where the information reflected by a single index is intuitive, and the optimized index table obtained by using the secondary index has a better effect on hiding information; therefore, the encryption effect of encrypting the original data by optimizing the index table is better, which ensures the security of the ciphertext data in the data management process. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. 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 any creative work.

[0032] Figure 1 A flow chart of a method for intelligent management of trajectory calculation data provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0033] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a method for intelligently managing trajectory calculation data according to the present invention. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0034] 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.

[0035] The present application is applicable to the encryption processing of ballistic calculation data. Since the data encryption process mainly involves the hidden relationship between ciphertext data and plaintext data, the embodiment of the present invention, based on the traditional LZW encoding technology, uses the index table and secondary index to cover the relationship between multiple character combinations, thereby realizing the hiding of the relationship between character combinations and encodings, so as to improve the effect of data encryption.

[0036] The specific scheme of the intelligent management method of trajectory calculation data provided by the present invention is described in detail below with reference to the accompanying drawings.

[0037] See also Figure 1 , which shows a flow chart of a method for intelligent management of trajectory calculation data provided by one embodiment of the present invention, the method comprising the following steps:

[0038] Step S100: obtaining data before and after calculation by the ballistic software as raw data to be managed; and selecting data from the raw data as initial data.

[0039] Setting gun parameters through ballistic calculation data is national defense confidential data, so data encryption is required in the ballistic calculation data, and data encryption mainly involves the hidden relationship between ciphertext data and plaintext data; in the parameter setting of sniper guns, a large number of ballistic calculations are required to obtain accurate parameters. Generally, ballistic software can obtain the ballistic table closest to the shooting conditions at this time based on the input of different parameters, such as temperature, distance, humidity, wind direction, wind speed, air pressure, and muzzle velocity. The result calculated by the ballistic software is the ballistic table or the aiming point on the scope. All input parameters in the ballistic software and the data included in the output results corresponding to the parameters are data that need to be encrypted and managed. All input parameters and output result data in the ballistic software are marked as raw data to be managed; build a data management platform and transfer all raw data to the data management platform for subsequent data management.

[0040] Since ballistic calculation data mainly involves the calculation of various parameters and the results of the calculation output, such as temperature, humidity and other parameters, it is inevitable that data characters will be repeated in the original data. Therefore, it is necessary to consider the repeated characters in the original data during encryption. The commonly used encryption coding technology is generally LZW coding technology, so it is necessary to build an index table based on all character combinations in the original data. However, since there are many repeated character combinations in the original data, in order to improve the applicability and reliability of LZW coding technology in this implementation scenario, first select part of the data in the original data as the initial data for processing, and perform subsequent step analysis based on the processing of the initial data.

[0041] A preset ratio is set, and data is sequentially selected from the original data at the preset ratio to obtain initial data. As a preferred example, in an embodiment of the present invention, the initial data selected from the original data is the first 10% of the data in the original data. In other embodiments, the implementer can adjust the amount of data in the initial data. The initial data includes multiple parameters and calculation results corresponding to different parameters. The selected initial data is subsequently analyzed.

[0042] Step S200 , obtaining a character combination sequence and a temporary index table based on the initial data, and counting the occurrence frequency of each character combination in the character combination sequence in the original data as the influence degree of the corresponding character combination.

[0043] Conventional LZW encoding technology mainly uses characters and character combinations to establish an index table and encode data by looking up the table. However, in the characters corresponding to the actual data, the character combination is directly obtained by combining the characters in the order in which they appear. Then, indexes are established for all character combinations. The index establishment rules are fixed, which will result in a more obvious relationship between the final code and the characters and poor security. Therefore, the embodiment of the present invention constructs a preliminary index table for the character combinations in the initial data, and then updates the index table according to all character combinations in the original data.

[0044] Because there are many repeated characters in the original data, the characters selected in the initial data can reflect the characters and character combinations of the entire original data to a certain extent. First, an LZW-encoded index table is established based on the initial data, and a corresponding character combination sequence can be obtained. The character combination sequence includes multiple character combinations, and the index table corresponds to the character combination sequence, that is, the index table contains indexes of multiple character combinations; the technology of LZW encoding to obtain character combinations and indexes is an existing public technology and will not be repeated here; since the character combinations appearing in the index table corresponding to the initial data can reflect the way the characters are combined in the original data to a certain extent, the index table corresponding to the initial data is used as a temporary index table for the entire original data, and then the character combinations and indexes in the temporary index table are adjusted and updated according to other data in the original data.

[0045] Since the temporary index table at this time includes the character combinations in the initial data, and other data in the original data may be different from the characters in the initial data, it is necessary to obtain the influence degree of each character combination based on all the data in the original data, and use the influence degree of different character combinations as the basis for updating and adjusting the character combinations in the temporary index table; construct local character combinations of different lengths based on the data characters in the original data, and the length is changed by increasing the data characters one by one; determine whether each local character combination has a corresponding character combination in the character combination sequence, if not, record the local character combination that has a corresponding character combination in the character combination sequence before the current local character combination as the first character combination; obtain all first character combinations in the original data, and obtain the frequency of occurrence of each first character combination based on all first character combinations to obtain the probability of occurrence of each first character combination, and the probability of occurrence of the first character combination is the influence degree of the character combination corresponding to the first character combination in the character combination sequence.

[0046] Specifically, the method for obtaining the influence degree of each character combination is as follows:

[0047] Since the character combinations in the character combination sequence correspond to the character combinations in the temporary index table, the frequency of each character combination in the temporary index table appearing in the original data is counted, that is, starting from the first data character in the original data, the length of the characters is increased successively to form different local character combinations, and it is determined whether the different local character combinations formed in the original data appear in the temporary index table. If the local character combination constructed by increasing the first data character one by one in the original data is not consistent with the character combination already existing in the temporary index table, the increase in character length is stopped, and the previous local character combination of the currently stopped local character combination is used as the first character combination.

[0048] Then, the character length is increased again with the characters after the current first character combination to form different local character combinations again. Similarly, it is determined whether each local character combination obtained at this time appears in the temporary index table; and so on, based on all the characters in the original data, all the first character combinations that are the same as the character combinations in the temporary index table can be obtained.

[0049] Finally, the frequency of each first character combination appearing in the original data is counted. The frequency of occurrence of each first character combination can be calculated based on the frequency of occurrence of all first character combinations in the original data. Since each first character combination corresponds to the same character combination in the temporary index table, the frequency of occurrence of each first character combination is the influence degree of the corresponding character combination in the temporary index table.

[0050] It should be noted that, for characters or character combinations in the original data that do not exist in the temporary index table, there is no need to calculate the impact degree.

[0051] As a preferred example, assume that the character combinations included in the temporary index table at this time are as follows: A, B, C, AB, BC, ABC, CA; the data character sequence corresponding to the original data is: ABCABDABCEBC; then taking the first character data A in the data character sequence as the starting point, continuously increase the length to construct different local character combinations to obtain AB and ABC in turn. When the local character combination is increased again to become ABCA, there is no corresponding character combination in the temporary index table, so ABC is the first character combination currently constructed, and then A after ABC is used as the starting point to construct the local character combination again, and AB and ABD are obtained. At this time, the local character combination ABD is not in the character combination of the temporary index table, so the second first character combination constructed is AB, and so on. Taking the data character D after the first character combination AB at this time as the starting point, the local character combination is constructed again, and it is judged whether the local character combination has a corresponding character combination in the temporary index table. Finally, multiple first character combinations of the data character sequence corresponding to the original data are obtained, namely: ABC, AB, ABC, BC.

[0052] The frequency of occurrence of each first character combination is further counted, the frequency of occurrence of ABC is 2, the frequency of occurrence of AB is 1, and the frequency of occurrence of BC is 1; finally, the corresponding occurrence frequency is obtained based on the frequency of occurrence of each first character combination, and then the corresponding influence degree of each character combination in the temporary index table is obtained; that is, the influence degree of character combination ABC is 1 / 2, the influence degree of character combination AB is 1 / 4, and the influence degree of character combination BC is 1 / 4; since data character D and data character E are not in the temporary index table, they are not involved in the statistics of occurrence frequency and the calculation of influence degree.

[0053] The greater the degree of influence of a character combination, the more data the character combination can affect in the original data. Therefore, the character combination is updated based on the degree of influence of the character combination to facilitate subsequent encryption processing.

[0054] Step S300: obtaining a new character in the original data, obtaining an updated character combination of the corresponding character combination based on the new character and the influence degree of each character combination in the initial data, and replacing the corresponding character combination with the updated character combination.

[0055] Since the character combinations in the temporary index table are obtained based on the initial data, for all data characters in the original data, there must be a new character combination that makes the character combination different from each character combination in the temporary index table. Therefore, it is necessary to obtain the new characters in the original data. The new characters in the original data are character data that do not exist in the initial data; the character combination composed of the new characters is recorded as a new character combination. In order to be able to encode and encrypt all the original data according to the temporary index table, the new character combination needs to be merged with the existing character combination in the temporary index table to obtain the index relationship corresponding to the new character combination.

[0056] The influence degree corresponding to each character combination in the temporary index table is obtained by step S200. The character combination with a greater influence degree indicates that its frequency of occurrence in the original data is greater. Since the merging of new character combinations will affect the existing character combinations, and the influence degree of the merging of new character combinations with existing character combinations depends on the frequency of occurrence of the new character combination in the original data, the greater the frequency of occurrence, the greater the influence of the new character combination on all characters. In order to make the new character combination have a greater influence on other character combinations, it is necessary to merge the new character combination with its adjacent character combination with the greatest influence degree to obtain the merged updated character combination.

[0057] Obtain adjacent character combinations adjacent to the new character in the original data, where the adjacent character combinations exist in the character combinations of the initial data; select the adjacent character combination with the greatest influence as the character combination to be merged, and merge the character combination to be merged with the new character to obtain an updated character combination of the character combination to be merged.

[0058] As a preferred example, assume that the character combinations existing in the temporary index table composed of the initial data are: AB, ABC, BC; the corresponding influence degrees of each character combination are: 5 / 16, 1 / 2, 3 / 8 respectively; the data character sequence corresponding to the original data is: ABCHABABC; when constructing the first character combination based on the data character sequence, it can be obviously determined that H is a character that does not exist in the initial data, so H is a new character.

[0059] When merging a new character H with an existing character combination, it is first necessary to obtain the adjacent character combination adjacent to the new character H, and the adjacent character combination is the character combination existing in the temporary index table. Therefore, according to the original data, the adjacent character combinations of the new character H are ABC, BC and AB, and the adjacent character combination with the greatest influence is selected for merging. According to the influence degree of each character combination in the temporary index table, it can be known that the adjacent character combination corresponding to the new character H has the greatest influence of ABC, and its corresponding influence degree is 1 / 2. The adjacent character combination with the greatest influence is used as the character combination to be merged; then the new character H and its corresponding selected character combination to be merged ABC are merged to obtain the updated character combination ABCH.

[0060] It should be noted that the updated character combination obtained in the embodiment of the present invention is used to update the corresponding character combination to be merged in the temporary index table, that is, after obtaining the updated character combination ABCH, all character combinations ABC in the original data that are the same as the character combination to be merged need to be updated to the updated character combination ABCH. Then, based on the sequence of data characters ABCHABABC in the original data, the corresponding new character combinations can be obtained as: ABCH, AB, ABCH respectively.

[0061] Furthermore, considering that there are many data characters in the data to be managed, continuous new character combinations often appear. For the continuous new character combinations that appear, they need to be merged step by step according to the order of the new character combinations in the sequence corresponding to the data to be managed, and the updated character combination obtained by the previous merging step can also be used as the merging object of the remaining new character combinations. If there are at least two new characters in a row, first obtain the character combination to be merged of the first new character, and obtain the first updated character combination based on the character combination to be merged of the first new character; use the first updated character combination as the existing character combination, select the adjacent character combination of the second new character, and the adjacent character combination of the second new character includes the first updated character combination; select the character combination to be merged of the second new character according to the influence of the adjacent character combination of the second new character to obtain the second updated character combination; and so on, merge all the continuous new characters in sequence to obtain the final updated character combination.

[0062] As a preferred example, assume that the character combinations existing in the temporary index table are: AB, ABC, BC; the corresponding influence degrees of each character combination are: 5 / 16, 1 / 2, 3 / 8 respectively; the data character sequence corresponding to the original data is: ABCHGABABC; then the new characters existing in the original data at this time are the new character H and the new character G respectively. First, the new character H is analyzed to obtain the character combination to be merged as ABC, so the first updated character combination is ABCH, that is, based on the data character sequence, the first new character combination obtained is: ABCH, G, AB, ABCH; taking the first updated character combination as the existing character combination, when analyzing the second new character G, the adjacent character combinations of the new character G are: ABCH and AB respectively; at this time, the adjacent character combination with a greater influence degree is ABCH, so the adjacent character combination ABCH is the character combination to be merged of the new character G, then the second updated character combination obtained is ABCHG, that is, the second new character combination obtained is: ABCHG, AB, ABCHG.

[0063] The first new character combination is obtained by merging the new character H with its adjacent character ABC, which has a greater degree of influence, and then the character combinations of ABCH, G, AB, and ABCH will appear; therefore, when obtaining the second new character combination, it is obtained based on the first new character combination, so the new character combination G should be merged with its adjacent character ABCH, which has the greatest degree of influence, and then the character combinations of ABCHG, AB, and ABCHG will be obtained.

[0064] By analogy, the data characters in the original data are merged with the existing character combinations to obtain different updated character combinations; the corresponding character combinations in the temporary index table are updated according to the corresponding influence levels of the character combinations, the character combination of the initial data is changed, and the character combination with a large influence level is selected to be merged with the new characters. This will improve the hiding of the updated character combination from the original data and be more conducive to encryption analysis of the data.

[0065] Step S400: decompose the updated character combination to obtain at least two decomposed character combinations, obtain a secondary index sequence of the updated character combination based on the distribution of each decomposed character combination in the original data, and update the temporary index table based on the secondary index sequence of each updated character combination to obtain an optimized index table.

[0066] The method in step S300 completes the update of the character combination. At this time, the updated character combination may include multiple character combination information. Therefore, it is necessary to update the temporary index table based on the differences in the character combination information contained in the updated character combination to achieve the correspondence between the character combination and the index.

[0067] The temporary index table is updated primarily based on the index information of the updated character combination in the temporary index table. Since the updated character combination, when merged, includes at least the new character before the merge and a character combination to be merged, different character combinations included in the same updated character combination are distinguished. Decomposition is performed based on the character combination in the temporary index table, with the decomposed character combination including at least the new character before the merge and a character combination to be merged. In other words, each updated character combination is decomposed to obtain multiple decomposed character combinations, each of which includes at least one new character and one character combination to be merged.

[0068] As a preferred example, assuming that the character combination in the temporary index table includes ABC, and the updated character combination after the update based on the new character merger is ABCHG, then for the updated character combination ABCHG after the update, it includes three character combinations of ABC, ABCH and ABCHG. If the index corresponding to the character combination ABC in the temporary index table is Y1, and the updated character combination obtained based on the character combination ABC includes three character combinations, it is necessary to continue to perform secondary indexing on the index Y1 corresponding to the character combination ABC to obtain a secondary index sequence for distinguishing the three character combinations of ABC, ABCH and ABCHG corresponding to the updated character combination ABCGH; label each decomposed character combination, count the occurrence position of each decomposed character combination in the original data, and mark the occurrence position with the label of the character combination, and the labels of all marked character combinations in the original data are arranged in sequence to form a secondary index sequence.

[0069] As an example, the method for performing secondary indexing on ABCHG to obtain a secondary index sequence is:

[0070] Label each character combination in ABCHG, label the character combination ABC as 1, the character combination ABCH as 2, and the character combination ABCHG as 3. Obtain the corresponding secondary index sequence based on the order of each character combination in ABCHG in the data to be managed. If the sequence of data characters in the data to be managed is: ABCABCHABCABCHGBCABC; then the secondary index sequence corresponding to ABCHG is: 1, 2, 1, 3, 1.

[0071] By analogy, all updated character combinations are secondary indexed to obtain a secondary index sequence, and the temporary index table is updated according to the secondary index sequence of each updated character combination to obtain an optimized index table; the updated index corresponding to the updated character combination is continued to be established, that is, the secondary index, which can ensure that the different character combinations included in the updated character combination have their own unique determination relationship, which is convenient for subsequent encoding, encryption and decryption, and different character combinations are directly reflected by the secondary index of the updated character combination, which can sensitively reflect the original character combination, and facilitate the use of secondary indexes to encrypt different character combinations.

[0072] Step S500: Encode and encrypt the original data according to the optimized index table to obtain ciphertext data, and store and manage the ciphertext data.

[0073] After obtaining the optimized index table in step S400, the original data is encoded and encrypted according to the optimized index table; first, the temporary index table is used to encode the original data to obtain the encoding sequence B j , the encoding method is a well-known technology and will not be described in detail; for different character combinations corresponding to the updated character combination, the same character combination in the temporary index table has the same encoding method, so the secondary index sequence of the different character combinations corresponding to the updated character combination in the original data is statistically updated to reflect the encoding sequence B j Different character combinations corresponding to the same encoding.

[0074] As an example, if the secondary index sequence corresponding to the updated character combination is: Z1, Z3, Z3, Z1, Z2, Z1, where Z1, Z2, and Z3 represent the labels of different character combinations, then in the encoding sequence B j The character combination is represented in the index order Z1, Z3, Z3, Z1, Z2, Z1 according to the appearance of the label of the corresponding character combination and the corresponding encoding is obtained. All character combinations corresponding to the updated character combination are hidden in the same encoding, and then the correspondence between each character combination and the encoding can be realized to realize the encryption of the original data.

[0075] The original data is encoded according to the optimized index table and the character combination in the optimized index table. The character combination is updated so that a variety of character combinations can be accommodated in one updated character combination, thereby hiding different combinations in the same updated character combination, that is, hiding the correspondence between characters and codes, thereby improving security. In addition, during the encoding process, the specific content reflected by the code corresponding to the same updated character combination depends only on its corresponding secondary index sequence. The secondary index sequence of the updated character combination is used as the key, reflecting the sensitivity of the current encryption process to the key. In this way, the encryption of all data characters in the original data is completed to obtain ciphertext data, and the encoding sequence B of the ciphertext data is obtained. j ,The keys corresponding to the ciphertext data are the optimized index table and the secondary index sequence.

[0076] After the original data obtained from the ballistic calculation is encrypted, the ciphertext data is obtained, that is, the ciphertext data of the ballistic calculation is obtained on the data management platform. At this time, different key permissions can be granted to managers according to different management needs. After obtaining the key permissions, the managers can obtain the data to be managed on the data management platform.

[0077] Furthermore, after completing the encryption processing of the original data, in order to ensure the practicality of the encryption process, the encrypted data needs to be decrypted and verified. The specific process is: in the obtained coding sequence, the correspondence between the character combination and the coding is obtained using the optimized index table, and then the secondary index of the different character combination methods corresponding to the same updated character combination is obtained according to the secondary index sequence of the character combination, and the different character combination methods reflected in the ciphertext data corresponding to the same character combination are obtained, thereby obtaining the data character sequence of the original data.

[0078] In summary, in the embodiment of the present invention, data before and after calculation by ballistic software is obtained as raw data to be managed; data is selected from the raw data as initial data; a character combination sequence and a temporary index table are obtained based on the initial data, and the frequency of occurrence of each character combination in the character combination sequence in the raw data is counted as the influence degree of the corresponding character combination; a new character in the raw data is obtained, and based on the new character and the influence degree of each character combination in the initial data, an updated character combination of the corresponding character combination is obtained, and the corresponding character combination is replaced with the updated character combination; the updated character combination is disassembled to obtain at least two decomposed character combinations, and a secondary index sequence of the updated character combination is obtained based on the distribution of each decomposed character combination in the raw data, and a temporary index table is updated based on the secondary index sequence of each updated character combination to obtain an optimized index table; the raw data is encoded and encrypted according to the optimized index table to obtain ciphertext data, and the ciphertext data is stored and managed. The security of encrypting the ballistic calculation data is improved, making the management based on the more secure ciphertext data more reliable.

[0079] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0080] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0081] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for intelligent management of trajectory calculation data, characterized in that: The method comprises the following steps: Acquire data before and after calculation by the ballistic software as raw data to be managed; select data from the raw data as initial data; Acquire a character combination sequence and a temporary index table based on the initial data, and count the occurrence frequency of each character combination in the character combination sequence in the original data as the influence degree of the corresponding character combination; Obtaining a new character in the original data, obtaining an updated character combination of the corresponding character combination based on the new character and the influence degree of each character combination in the initial data, and replacing the corresponding character combination with the updated character combination; Decomposing the updated character combination to obtain at least two decomposed character combinations, obtaining a secondary index sequence of the updated character combination based on the distribution of each decomposed character combination in the original data, and updating the temporary index table based on the secondary index sequence of each updated character combination to obtain an optimized index table; The original data is encoded and encrypted according to the optimized index table to obtain ciphertext data, and the ciphertext data is stored and managed.

2. The method for intelligent management of trajectory calculation data according to claim 1, characterized in that: The step of selecting data from the original data as initial data includes: A preset ratio is set, and data is sequentially selected from the original data according to the preset ratio to obtain initial data.

3. The method for intelligent management of trajectory calculation data according to claim 1, characterized in that: The step of counting the occurrence frequency of each character combination in the character combination sequence in the original data as the influence degree of the corresponding character combination includes: Constructing partial character combinations of different lengths based on the data characters in the original data, wherein the lengths are changed by incrementing the data characters one by one; determining whether each partial character combination has a corresponding character combination in the character combination sequence, and if not, recording the partial character combination preceding the current partial character combination that has a corresponding character combination in the character combination sequence as the first character combination; Obtain all first character combinations in the original data, and obtain the frequency of occurrence of each first character combination based on all first character combinations to obtain the occurrence probability of each first character combination. The occurrence probability of the first character combination is the degree of influence of the first character combination on the corresponding character combination in the character combination sequence.

4. The method for intelligent management of trajectory calculation data according to claim 1, characterized in that: The step of obtaining the new character in the original data includes: The new characters in the original data are character data that do not exist in the initial data.

5. The method for intelligent management of trajectory calculation data according to claim 1, characterized in that: The step of obtaining an updated character combination corresponding to the character combination based on the new character and the influence degree of each character combination in the initial data comprises: Obtain adjacent character combinations adjacent to the new character in the original data, where the adjacent character combinations exist in the character combinations of the initial data; select the adjacent character combination with the greatest influence as the character combination to be merged, and merge the character combination to be merged with the new character to obtain an updated character combination of the character combination to be merged.

6. The method for intelligent management of trajectory calculation data according to claim 5, characterized in that: The step of obtaining an updated character combination corresponding to the character combination based on the new character and the influence degree of each character combination in the initial data further includes: If there are at least two consecutive new characters, first obtain the character combination to be merged of the first new character, and obtain the first updated character combination based on the character combination to be merged of the first new character; Taking the first updated character combination as the existing character combination, select the adjacent character combination of the second new character, and the adjacent character combination of the second new character includes the first updated character combination; select the character combination to be merged of the second new character according to the influence degree of the adjacent character combination of the second new character to obtain the second updated character combination; and so on, merge all the consecutive new characters in sequence to obtain the final updated character combination.

7. The method for intelligent management of trajectory calculation data according to claim 5, characterized in that: The step of disassembling the updated character combination to obtain at least two decomposed character combinations includes: The decomposition is performed based on the character combination in the temporary index table, and the decomposed character combination at least includes a new character before the merging of the updated character combination and a character combination to be merged.

8. The method for intelligent management of trajectory calculation data according to claim 7, characterized in that: The step of obtaining the secondary index sequence of the updated character combination based on the distribution of each decomposed character combination in the original data comprises: Each of the decomposed character combinations is numbered, the occurrence position of each of the decomposed character combinations in the original data is counted, and the occurrence position is marked with the number of the character combination. The numbers of all marked character combinations in the original data are arranged in sequence to form a secondary index sequence.

9. The method for intelligent management of trajectory calculation data according to claim 8, characterized in that: The step of encoding and encrypting the original data according to the optimized index table to obtain ciphertext data includes: The original data is encoded based on the temporary index table to obtain a coding sequence; the coding corresponding to the decomposed character combination corresponding to each updated character combination in the optimized index table is obtained in the coding sequence, and data encryption is implemented according to the coding of all character combinations to obtain ciphertext data.

10. The method for intelligent management of trajectory calculation data according to claim 1, characterized in that: The keys of the ciphertext data are the optimized index table and the secondary index sequence.

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