A method, system, and storage medium for out-of-order device identification

Abstract

The application provides a device identification disorder conversion method, system and storage medium, which comprises the following contents: obtaining an original device identification data set A to be converted by a target device; obtaining a deduplicated device identification data set B based on A; if the data amount in B reaches a certain scale, generating a corresponding intermediate device identification data set N according to B, and finally dividing N into p sub device identification data sets; taking each sub device identification data set as the target input data of first disorder processing respectively to obtain a first target device identification data set C. By setting the initial generation time stamp of data in the original device identification data and disordering the generated intermediate device identification data set before outputting, the target data can be protected by using the expiration mechanism in the use process, and the conversion rule between the device identifications cannot be identified by the way of checking one by one, so that the security of the target data is improved.

Description

Technical Field

[0001] This application relates to the field of data processing, and specifically to a method, system, and storage medium for unordered conversion of device identifiers. Background Technology

[0002] In existing technologies, to improve the user's terminal experience, unique identification information is typically used to directly or indirectly obtain user attribute data, thereby building a personal profile of the user to facilitate targeted business promotion and improve user experience. However, if such identification information is stolen, it may cause losses to the user. Therefore, how to improve the security of user or user terminal identification information is a pressing technical problem that needs to be solved. Summary of the Invention

[0003] To address the aforementioned technical problems, the technical solution adopted in this application is: a method for unordered conversion of device identifiers, comprising the following steps:

[0004] S100, Obtain the original device identifier dataset A = (A1, A2, ..., A...) of the target device. i ,…,A n1 ), the i-th original device identification data A i It consists of at least two parts: the initial generation timestamp of the device identifier and the device identifier, i = 1, 2, ..., n1, where n1 is the total number of original device identifier data;

[0005] S200, perform deduplication processing on the original device identifier dataset A to obtain a deduplicated device identifier dataset B = (B1, B2, ..., B...). j ,...,B n2 ), j = 1, 2, ..., n2, n2 ≤ n1, n2 is the total number of original device identifier data contained in the deduplicated device identifier dataset B;

[0006] S300, if the deduplicated device identifier dataset B conforms to the first preset rule, then generate an intermediate device identifier dataset N = (N1, N2, ..., N) according to the preset identifier conversion rule. m ,...,N n3 ), where an expired original device identifier data in B uniquely generates an intermediate device identifier data in N according to a preset identifier conversion rule, and different original device identifier data generate different intermediate device identifier data according to the preset identifier conversion rule, m=1,2,...,n3, n3 is the total number of intermediate device identifier data included in N, n3≤n2;

[0007] S400, divide the intermediate device identifier dataset N into p sub-device identifier datasets NC1, NC2, ..., NCk ,...,NC p Each sub-device identifier dataset is used as the target input data for the first unordered processing to obtain the first target device identifier dataset C = (C1, C2, ..., C...). k ,...,C p ), C k By NC k The data is processed as the target input data for the first unordered processing.

[0008] The first disorder processing includes the following steps:

[0009] S1, Based on the target input data, obtain the first position data group S = [S1, S2, ..., S...]. h ,...,S q ], where q is the total number of intermediate device identifier data contained in the target input data, and S h S is used to indicate the position of the h-th intermediate device identifier data in the target input data. h =h, h = 1, 2, ..., q;

[0010] S2, use a preset unordered algorithm to swap the positions of the data in the first position data group S to obtain the second position data group E = [E1, E2, ..., E...]. h ,...,E q ];

[0011] S3, Based on the second position data E, obtain the target output data U = [U1, U2, ..., U...]. h ,...,U q ], where U h For the target input data, the Eth h Data points.

[0012] A device identifier out-of-order conversion system includes a processor and a non-transitory computer-readable storage medium for storing at least one instruction or at least one program, wherein the processor loads and executes the at least one instruction or at least one program to implement the aforementioned device identifier out-of-order conversion method.

[0013] A computer-readable storage medium storing a program or instructions that causes a computer to perform an out-of-order conversion method for a device identifier as described above.

[0014] As described above, this application first targets the original device identifier dataset A to be converted; then, it performs deduplication processing on the original device identifier dataset A to obtain a deduplicated device identifier dataset B; if the amount of data in the deduplicated device identifier dataset B and the proportion of expired original device identifier data are both greater than the corresponding thresholds, then an intermediate device identifier dataset N is generated based on the deduplicated device identifier dataset B, and finally, N is divided into p sub-device identifier datasets; each sub-device identifier dataset is used as the target input data for the first unordered processing to obtain the first target device identifier dataset C. In summary, this application sets an initial generation timestamp in the original device identifier data. This initial generation timestamp can be used to control the validity of device identifiers during use, initially ensuring the security of user data or device data; subsequently, this application outputs the generated large-scale intermediate device identifier dataset in an unordered manner. That is, by shuffling the output order of device identifiers, this application makes it impossible to identify the conversion rules between device identifiers through individual checks, thereby avoiding the possibility of arbitrarily obtaining user data or device data through device identifiers and improving the security of user data or device data. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart of a method for unordered conversion of device identifiers provided in an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] This application provides a method for unordered conversion of device identifiers, such as... Figure 1 As shown, it includes the following steps:

[0019] S100, Obtain the original device identifier dataset A = (A1, A2, ..., A...) of the target device. i ,…,A n1 ), the i-th original device identification data A iIt consists of at least two parts: the initial generation timestamp of the device identifier and the device identifier, i = 1, 2, ..., n1, where n1 is the total number of original device identifier data.

[0020] In this application, the initial generation timestamp represents the time interval, measured in seconds, between the time when the device is first assigned a corresponding device identifier and a preset timing start point. The preset timing start point can be a timing start point commonly used in the art, or it can be a custom timing start point defined according to actual conditions. This application does not impose any restrictions on the timing start point. The device identifier can be a device ID, such as a Zhuoxin ID, used to uniquely identify a device, and different devices have different device identifiers. To better maintain the device identification information, in one embodiment, the server maintains a device terminal identifier list. Each piece of data in this device terminal list includes at least the device identifier, device location, device model, initial generation timestamp of the device identifier, expiration rules of the device identifier, and historical conversion identifiers of the device identifier.

[0021] In one embodiment of this application, device identifier data for each target device in the target device group is obtained to obtain a raw device identifier dataset A to be converted for the target devices. In a preferred embodiment, the raw device identifier data may further include a device identifier version number, a device identifier category number, device attribute parameters, and a preset expiration judgment rule. Preferably, when the current device identifier of a device is obtained and device data is obtained based on the current device identifier, the preset expiration judgment rule is automatically activated, automatically determining whether the current device identifier has expired based on the initial generation timestamp in the current device identifier. If it has expired, the acquisition of device data is refused. This protects the security of the target data.

[0022] S200, perform deduplication processing on the original device identifier dataset A to obtain a deduplicated device identifier dataset B = (B1, B2, ..., B...). j ,...,B n2 ), j = 1, 2, ..., n2, n2 ≤ n1, where n2 is the total number of original device identifier data contained in the deduplicated device identifier dataset B. Those skilled in the art will know that since B is obtained by deduplicating A, therefore, B j ∈A.

[0023] In one embodiment of this application, the deduplication process includes:

[0024] If any two original device identification data sets have the same initial generation timestamp and device identification components, then delete either one of the data sets.

[0025] By deduplication, duplicate data in the original device identification data can be removed. This reduces subsequent computation and saves system resources. Furthermore, it avoids the risk of repeatedly testing and reversing the identification rules by copying multiple identical data entries, which could compromise the security of user or device data.

[0026] S300, if the deduplicated device identifier dataset B conforms to the first preset rule, then generate an intermediate device identifier dataset N = (N1, N2, ..., N) according to the preset identifier conversion rule. m ,...,N n3 In this context, an expired original device identifier data in B is used to uniquely generate an intermediate device identifier data in N according to a preset identifier conversion rule. Different original device identifier data will generate different intermediate device identifier data according to the preset identifier conversion rule. m = 1, 2, ..., n3, where n3 is the total number of intermediate device identifier data included in N, and n3 ≤ n2.

[0027] In this application, the first preset rule is a custom rule. To avoid reverse identification of the preset identifier conversion rule, the first preset rule sets the total number of valid original device identifier data in the original device identifier data. Preferably, the first preset rule is: 1000≤n2≤100000, and the number of expired original device identifier data entries in B is ≥g*n2. Whether the original device identifier data is expired is determined based on the initial generation timestamp of the device identifier included in the original device identifier data and the preset expiration judgment rule. g is a preset proportional coefficient; the value range of g is [0.98, 1], and g is preferably 0.99, which facilitates batch processing of data.

[0028] S400, divide the intermediate device identifier dataset N into p sub-device identifier datasets NC1, NC2, ..., NC k ,...,NC p Each sub-device identifier dataset is used as the target input data for the first unordered processing to obtain the first target device identifier dataset C = (C1, C2, ..., C...). k ,...,C p ), C k By NC k The data is processed as the target input data for the first unordered processing. In this application, the data is preferably divided into p sub-device identifier datasets of equal size, that is, each sub-device identifier dataset contains the same number of data entries. Other partitioning methods are also possible, and this application does not impose specific restrictions on them.

[0029] The first disorder processing includes the following steps:

[0030] S1, Based on the target input data, obtain the first position data group S = [S1, S2, ..., S...]. h ,...,S q ], where q is the total number of intermediate device identifier data contained in the target input data, and S h S is used to indicate the position of the h-th intermediate device identifier data in the target input data. h =h, h = 1, 2, ..., q.

[0031] S2, use a preset unordered algorithm to swap the positions of the data in the first position data group S to obtain the second position data group E = [E1, E2, ..., E...]. h ,...,E q ].

[0032] S3, Based on the second position data E, obtain the target output data U = [U1, U2, ..., U...]. h ,...,U q ], where U h For the target input data, the Eth h Each piece of data. Those skilled in the art will understand that each piece of data in the target input data is related to U1, U2, ..., U... h ,...,U q The correspondence between them can be stored in any form, such as a database, an Excel spreadsheet, etc., or it can be maintained on the server side.

[0033] Furthermore, in a preferred embodiment of this application, S3 specifically includes:

[0034] S301, sequentially from back to front, E1, E2, ..., E h ,...,E q The data at each position is swapped with the data at any position preceding it, until the data at the (q-1)th position from the end has been swapped, resulting in the first output sequence V1, V2, ..., V. h ,...,V q ;

[0035] S302, based on the first output sequence V1,V2,...,V h ,...,V q Obtain the target output data U = [U1, U2, ..., U h ,...,U q ], where U h For the Vth element in the target input data hThis embodiment enhances the disorder of the data by further reordering the already disordered data, thus ensuring the security of the output data.

[0036] In summary, this application first targets the original device identifier dataset A to be converted; then, it performs deduplication on the original device identifier dataset A to obtain a deduplicated device identifier dataset B; if the amount of data in the deduplicated device identifier dataset B and the proportion of expired original device identifier data are both greater than the corresponding thresholds, then an intermediate device identifier dataset N is generated based on the deduplicated device identifier dataset B, and finally, N is divided into p sub-device identifier datasets; each sub-device identifier dataset is used as the target input data for the first unordered processing to obtain the first target device identifier dataset C. In conclusion, this application sets an initial generation timestamp in the original device identifier data, which can be used to control the validity of device identifiers during use, initially ensuring the security of user data or device data; subsequently, this application outputs the generated large-scale intermediate device identifier dataset in an unordered manner, that is, by shuffling the output order of device identifiers, this application makes it impossible to identify the conversion rules between device identifiers through individual checks, thereby avoiding the possibility of arbitrarily obtaining user data or device data through device identifiers and improving the security of user data or device data.

[0037] Preferably, in S301, swapping the data at the current position to be swapped with the data at any position preceding the current position to be swapped includes:

[0038] S3011, Obtain the last x bits of the initial generation timestamp of the intermediate device identifier data corresponding to the data at the current location to be exchanged in the target input data. Where w-1 is the number of positions before the current position to be swapped, and lg is a logarithmic function with base 10. This is the preset floor function;

[0039] S3013, swap the data at the current position to be swapped with the data at the u-th position preceding the current position, where u is a natural number generated based on the last x bits of data. Those skilled in the art will understand that when the initial timestamp is represented by a natural number, the last x bits can be directly obtained as u.

[0040] In one embodiment of this application, a preset unordered algorithm is used to swap the positions of each data point in the first position data group S to obtain the second position data group E = [E1, E2, ..., E...]. h ,...,E q ],include:

[0041] S201, obtain the jump parameter r = rand(1, R), where rand(1, R) is used to generate a random natural number between [1, R], and R is the number of preset unordered algorithms included in the preset unordered algorithm sequence, and any two preset unordered algorithms are different. Those skilled in the art will understand that the R preset unordered algorithms can be customized. This application does not limit the specific content of the R preset unordered algorithms, as long as they can be used to sort the data according to specific rules.

[0042] S202, according to the jump parameter r, obtain the r-th preset unordered algorithm in the preset unordered algorithm sequence, and based on the r-th preset unordered algorithm, swap the positions of each data in the first position data group S to obtain the second position data group E.

[0043] In a preferred embodiment of this application, a preset unordered algorithm is used to swap the positions of each data point in the first position data group S to obtain the second position data group E = [E1, E2, ..., E...]. h ,...,E q ],include:

[0044] S203, iterate through S and get S h The corresponding jump parameter r h = rand(1, R), where rand(1, R) is used to generate a random natural number between [1, R], where R is the number of preset data processing algorithms included in the preset data processing algorithm sequence, and any two preset data processing algorithms are different. The R preset data processing algorithms are used to generate a new integer based on the input data.

[0045] S204, based on jump parameter r h Obtain the r-th element in the data processing algorithm sequence. h A preset data processing algorithm, and based on the r-th... h A preset data processing algorithm for S h Processing yields E h .

[0046] S205, if E h If the first h-1 data points in the second position data group E are all different, then append E. h If the value is not found, return to the h-th position of E; otherwise, return S203, where the initial value of E is empty.

[0047] That is, for any S h If the second position data group E does not exist, h The corresponding data will be ordered as follows: E hThe data is placed into the second position data group E. If it exists, S203 is executed again to obtain the new jump parameters, and then it is checked whether the second position data group E exists. h The corresponding data continues until the second position data group E does not contain E. h Then for E h The next object E h+1 Perform steps S203-S205 as described above. This embodiment further improves the unordered nature of the data output by selecting different sorting output methods for data at different locations.

[0048] In another embodiment of this application, S400 is followed by S500:

[0049] The first target device identifier dataset C is used as the target input data for the first unordered processing to obtain the second target device identifier dataset D = (D1, D2, ..., D...). k ,...,D p In this step, C is... k Consider C as a whole data set to obtain the second target device identifier dataset D.

[0050] At this point, the first disordered processing includes the following steps:

[0051] S10, Based on the target input data, obtain the first position data group S = [S1, S2, ..., S...]. k ,...,S p ], where p is the number of first target device identifier data contained in the target input data, used to represent D k S at the position in the target input data k =k, k = 1, 2, ..., p. At this point, since the input is the first target device identifier dataset C, therefore, q = p.

[0052] S20, Use a preset unordered algorithm to swap the positions of the data in the first position data group S to obtain the second position data group E = [E1, E2, ..., E...]. k ,...,E p ], where different data in S are output in different positions in E after being processed by a preset unordered algorithm.

[0053] S30, Obtain target output data U = [U1, U2, ..., U...] based on the second position data E. k ,...,U p ], where U k For the target input data, the Eth k The first target device identification data.

[0054] In yet another embodiment of this application, the k-th process is used to transfer NC k The target input data is processed as the first unordered data to obtain the first target device identification data C. k In this process, p processes execute in parallel, thereby improving the timeliness of data processing.

[0055] This application also provides a device identifier out-of-order conversion system, which includes a processor and a non-transitory computer-readable storage medium for storing at least one instruction or at least one program, wherein the processor loads and executes the at least one instruction or at least one program in accordance with the device identifier out-of-order conversion method disclosed in any of the foregoing embodiments.

[0056] Another embodiment of this application discloses a computer-readable storage medium that stores a program or instructions that cause a computer to perform the methods provided in the above embodiments.

[0057] Embodiments of this application also provide an electronic device, including a processor and the aforementioned non-transitory computer-readable storage medium.

[0058] Embodiments of this application also provide a computer program product including program code, which, when the program product is run on an electronic device, causes the electronic device to perform the steps of the methods described above according to various exemplary embodiments of this application.

[0059] While specific embodiments of this application have been described in detail by way of examples, those skilled in the art should understand that the examples are for illustrative purposes only and not intended to limit the scope of this application. Those skilled in the art should also understand that various modifications can be made to the embodiments without departing from the scope and spirit of this application. The scope of this application is defined by the appended claims.

Claims

1. A method for unordered conversion of device identifiers, characterized in that, Includes the following steps: S100, Obtain the original device identifier dataset A = (A1, A2, ..., A...) of the target device. i ,…,A n1 ), the i-th original device identification data A i It consists of at least two parts: the initial generation timestamp of the device identifier and the device identifier, i = 1, 2, ..., n1, where n1 is the total number of original device identifier data; S200, perform deduplication processing on the original device identifier dataset A to obtain a deduplicated device identifier dataset B = (B1, B2, ..., B...). j ,...,B n2 ), j = 1, 2, ..., n2, n2 ≤ n1, n2 is the total number of original device identifier data contained in the deduplicated device identifier dataset B; S300, if the deduplicated device identifier dataset B conforms to the first preset rule, then generate an intermediate device identifier dataset N = (N1, N2, ..., N) according to the preset identifier conversion rule. m ,...,N n3 ), where an expired original device identifier data in B uniquely generates an intermediate device identifier data in N according to a preset identifier conversion rule, and different original device identifier data generate different intermediate device identifier data according to the preset identifier conversion rule, m=1,2,...,n3, n3 is the total number of intermediate device identifier data included in N, n3≤n2; S400, divide the intermediate device identifier dataset N into p sub-device identifier datasets NC1, NC2, ..., NC k ,...,NC p Each sub-device identifier dataset is used as the target input data for the first unordered processing to obtain the first target device identifier dataset C = (C1, C2, ..., C...). k ,...,C p ), C k By NC k The data is processed as the target input data for the first unordered processing. The first disorder processing includes the following steps: S1, Based on the target input data, obtain the first position data group S = [S1, S2, ..., S...]. h ,...,S q ], where q is the total number of intermediate device identifier data contained in the target input data, and S h S is used to indicate the position of the h-th intermediate device identifier data in the target input data. h =h, h = 1, 2, ..., q; S2, use a preset unordered algorithm to swap the positions of the data in the first position data group S to obtain the second position data group E = [E1, E2, ..., E...]. h ,...,E q ]; S3, Based on the second position data E, obtain the target output data U = [U1, U2, ..., U...]. h ,...,U q ], where U h For the target input data, the Eth h Data points.

2. The method for unordered conversion of device identifiers according to claim 1, characterized in that, S3 specifically includes: S301, sequentially from back to front, E1, E2, ..., E h ,...,E q The data at each position is swapped with the data at any position preceding it, until the data at the (q-1)th position from the end has been swapped, resulting in the first output sequence V1, V2, ..., V. h ,...,V q ; S302, based on the first output sequence V1,V2,...,V h ,...,V q Obtain the target output data U = [U1, U2, ..., U h ,...,U q ], where U h For the Vth element in the target input data h Data points.

3. The method for disordered conversion of device identifiers according to claim 1 or 2, characterized in that, S400 is followed by S500: The first target device identifier dataset C is used as the target input data for the first unordered processing to obtain the second target device identifier dataset D = (D1, D2, ..., D...). k ,...,D p ).

4. The method for unordered conversion of device identifiers according to claim 1, characterized in that, The deduplication process is as follows: If any two original device identification data sets have the same initial generation timestamp and device identification components, then delete either one of the data sets.

5. The method for unordered conversion of device identifiers according to claim 1, characterized in that, The first preset rule is: 1000≤n2≤100000, and the number of expired original device identification data entries in B is ≥g*n2. Whether the original device identification data is expired is based on the initial generation timestamp of the device identification included in the original device identification data and the preset expiration judgment rule. g is a preset proportional coefficient; the value range of g is [0.98, 1].

6. The method for unordered conversion of device identifiers according to claim 2, characterized in that, In S301, the data at the current position to be swapped is exchanged with the data at any position preceding the current position to be swapped, including: S3011, Obtain the last x bits of the initial generation timestamp of the intermediate device identifier data corresponding to the data at the current location to be exchanged in the target input data. Where w-1 is the number of positions before the current position to be swapped, and lg is a logarithmic function with base 10. This is the preset floor function; S3013, swap the data at the current position to be swapped with the data at the u-th position before the current position to be swapped, where u is a natural number generated based on the last x bits of data.

7. The method for unordered conversion of device identifiers according to claim 1, characterized in that, A pre-defined disordered algorithm is used to swap the positions of each data point in the first position data set S to obtain the second position data set E = [E1, E2, ..., E...]. h ,...,E q ],include: S201, obtain the jump parameter r = rand(1, R), where rand(1, R) is used to generate a random natural number between [1, R], where R is the number of preset unordered algorithms included in the preset unordered algorithm sequence, and any two preset unordered algorithms are different; S202, according to the jump parameter r, obtain the r-th preset unordered algorithm in the preset unordered algorithm sequence, and based on the r-th preset unordered algorithm, swap the positions of each data in the first position data group S to obtain the second position data group E.

8. The method for unordered conversion of device identifiers according to claim 1, characterized in that, The k-th process is used to transfer NC k The target input data is processed as the first unordered data to obtain the first target device identification data C. k , where p processes execute in parallel.

9. A device identifier out-of-order conversion system, the system comprising a processor and a non-transitory computer-readable storage medium for storing at least one instruction or at least one program segment, characterized in that, The processor loads and executes the at least one instruction or at least one program segment to implement the unordered conversion method of the device identifier according to any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program or instructions that cause a computer to perform an out-of-order conversion method for a device identifier as described in any one of claims 1 to 8.

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