A data space connector related apparatus

Abstract

The application discloses a kind of data space connector related devices, belong to data processing technical field, break through the technical barrier in traditional data circulation by identity authentication, heterogeneous data source access, data product packaging etc., then based on double-channel interactive interface, the data space of different organizations, industry can be seamlessly docked, form cross-domain data resource pool, data circulation efficiency is improved;Then through to shared data resource pool and data product custom access rule, can effectively improve data management efficiency and reduce cross-domain cooperation trust cost;Finally, data interaction is encrypted, and the security of data in cross-domain interaction process is guaranteed in all aspects.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of data processing, and particularly relates to a data space connector related device. BACKGROUND

[0002] With the deepening of digital transformation, data has become a key production factor. However, data is usually scattered in different organizations, industries and even regions, forming many "data islands". How to safely and efficiently break these islands and realize the interconnection and value mining of cross-domain data has become a problem to be solved. The existing data integration and sharing scheme often has problems such as different standards, high security risks, complex management, lack of effective governance mechanism, etc., and it is difficult to meet the growing cross-domain data circulation demand. Therefore, a new type of connector device is needed, which can serve as a core hub to integrate data access, management, sharing, security and governance functions, and build a trusted data circulation environment. SUMMARY

[0003] The application provides a data space connector related device to solve the problem of low data island and data circulation efficiency in the prior art.

[0004] A data space connector related device comprises a plurality of data space connection units, a first data space interaction interface, a second data space interaction interface, a digital contract management unit and a data encryption transmission unit.

[0005] The data space connection unit comprises an identity management module, a data resource management module and a data product management module.

[0006] The identity management module is configured to perform identity verification on a user and determine an identity verification result, wherein the identity verification result comprises user identity verification pass or user identity verification fail, and is further configured to reject a data connection operation of the user when the identity verification result is different from the user identity verification pass.

[0007] The data resource management module is configured to support the user to input heterogeneous data in different formats and clean and convert the heterogeneous data from different sources to form a shared data resource pool when the identity verification result is the user identity verification pass.

[0008] The data product management module is configured to encapsulate raw data input by the user into a data product with a standardized form, and the data product is configured to circulate in different data spaces.

[0009] The first data space interaction interface is configured to allow the user to connect to the identity management module, the data resource management module and the data product management module to realize identity management, data sharing and product encapsulation.

[0010] The second data space interaction interface is configured to allow different data space connection units to communicate, so that different users can access the shared data resource pool and circulate the data products across data spaces.

[0011] The digital contract management unit is configured to allow a user to customize access rules for the shared data resource pool and the data products, and only allow other users to access within the access rules.

[0012] The data encryption transmission unit is configured to, when the access of a target user to the shared data resource pool and the data products meets the access rules, encrypt target data in the shared data resource pool and / or a target data product, obtain the target data and / or the target data product after encryption processing, and transmit the target data and / or the target data product after encryption processing to the target user through the second data space interaction interface.

[0013] The target user represents a user who is currently accessing data, and the target data and / or the target data product represent data and / or data products in the shared data resource pool accessed by the target user.

[0014] In a possible implementation, the identity verification of the user is performed, and the identity verification result is determined, including: verifying a digital certificate of the user or verifying a biological feature of the user, determining whether the user has been authorized, and if yes, determining that the identity verification result is that the user identity verification is passed, and if not, determining that the identity verification result is that the user identity verification is not passed.

[0015] In a possible implementation, the encryption processing of the target data and / or the target data product in the shared data resource pool to obtain the target data and / or the target data product after encryption processing includes:

[0016] A first round key of the AES algorithm is randomly generated, and the first round key is converted into a decimal number to obtain a target value corresponding to the first round key;

[0017] An iteration counter s is set to 1;

[0018] A plurality of different decimal numbers are randomly generated for the s-th round key to obtain a plurality of candidate values;

[0019] The target values corresponding to the first s-1 round keys are obtained to obtain the fitness of the candidate values;

[0020] The optimal candidate value is determined based on the fitness of the candidate values;

[0021] According to the optimal candidate value, the candidate value is subjected to multiple local randomization, global randomization and perturbation randomization to determine the candidate value after randomization;

[0022] According to the candidate value after randomization, the final s-th round key is determined;

[0023] It is judged whether the value of the iteration counter s is equal to the total number of keys required by the AES algorithm, if yes, the keys corresponding to all rounds are output, otherwise the value of the iteration counter t is increased by one, and the step of generating the candidate value is returned;

[0024] According to the keys corresponding to all rounds of the AES algorithm, the target data and / or target data product in the shared data resource pool are subjected to encryption processing to obtain the target data and / or target data product after encryption processing.

[0025] In a possible implementation, the fitness corresponding to the candidate value is obtained according to the target values corresponding to the first s-1 round keys, including: the Euclidean distance variance of the candidate value and the first s-1 round keys is determined according to the target values corresponding to the first s-1 round keys, to obtain the fitness corresponding to the candidate value; wherein the greater the fitness corresponding to the candidate value, the higher the randomness corresponding to the candidate value.

[0026] In a possible implementation, the local randomization is:

[0027] X i (t+1)=ω(t)*γe bl cos(2πl)+X best (t)

[0028] ω(t)=ω min +(ω max -ω min )exp(-(t / T) 2 )

[0029] γ=|LevyX best (t)-X i (t)|

[0030] Wherein, X i (t) represents the i-th candidate value in the t-th randomization process, i=1, 2, …, NP, NP represents the total number of candidate values, X i (t+1) represents the i-th candidate value after local randomization, X best (t) represents the optimal candidate value, ω(t) represents the local randomization range control factor, γ represents the information item, e represents the natural constant, b represents the constant term, l represents the local randomization trajectory control factor, π represents the circular constant, ω min represents the minimum value of the local randomization range control factor, ωmax represents the maximum value of the local randomization range control factor, exp represents the exponential function with the natural constant e as the base, T represents the total number of randomizations, Levy represents the random Levy flight factor.

[0031] In a possible implementation, the global randomization comprises:

[0032] X m (t+1)=X m (t)+α*(X R (t)-X m (t))*ln(1 / r1)

[0033]

[0034] wherein X m (t) represents the candidate value after the mth local randomization in the tth randomization process, m=1,2,…,NP, NP represents the total number of candidate values, X m (t+1) represents the mth candidate value after the global randomization, X R (t) represents the random candidate value, a represents the global randomization factor, r1 represents the first random number between 0 and 1, p represents the circular constant, and T represents the total number of randomizations.

[0035] In a possible implementation, the perturbation randomization comprises:

[0036] X n (t+1)=X n (t)*(1+Cauchy)

[0037] wherein X n (t) represents the candidate value after the nth global randomization in the tth randomization process, n=1,2,…,NP, NP represents the total number of candidate values, X n (t+1) represents the nth candidate value after the perturbation randomization, and Cauchy represents the Gaussian variation operator.

[0038] In a possible implementation, the network traffic monitoring unit is further included.

[0039] The network traffic monitoring unit is configured to collect and identify network traffic features in the data interaction process of the data space connection unit, and determine a network traffic monitoring result, wherein the network traffic monitoring result comprises an abnormal network access or no abnormal network access.

[0040] In a possible implementation, the network traffic features are collected and identified, and the network traffic monitoring result is determined, including: collecting the network traffic features, and identifying the network traffic features by using a pre-trained neural network model to determine the network traffic monitoring result.

[0041] In a possible implementation, after the network traffic monitoring result is determined, the method further includes:

[0042] In a case where the network traffic monitoring result includes an abnormal network access, the data interaction process of the user is terminated to ensure data interaction security.

[0043] The data space connector related device provided by the application breaks through the technical barriers in the traditional data circulation through identity authentication, heterogeneous data source access, data product packaging and other functions, and then based on a double-channel interactive interface, data spaces of different organizations and industries can be seamlessly connected to form a cross-domain data resource pool, and the data circulation efficiency is improved; then through the shared data resource pool and the data product customized access rules, the data management efficiency can be effectively improved and the cross-domain cooperation trust cost can be reduced; finally, the data interaction is encrypted, and the security of the data in the cross-domain interaction process is comprehensively ensured. BRIEF DESCRIPTION OF DRAWINGS

[0044] The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate embodiments consistent with the present application and, together with the description, further serve to explain the principles of the application.

[0045] Figure 1 A structural schematic diagram of a data space connector related device provided by an embodiment of the application.

[0046] The specific embodiments of the application have been shown and described in the foregoing drawings together with a preferred embodiment of the application. More detailed description will be given in the following. These drawings and detailed description are not intended to limit the scope of the inventive concept by any means, but to illustrate the inventive concept to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0047] The exemplary embodiments will be described in detail herein with reference to the attached drawings. Unless otherwise specified, the same numbers in different drawings indicate the same or similar elements. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the application as detailed in the appended claims.

[0048] The embodiments of the application will be described in detail below with reference to the accompanying drawings.

[0049] As Figure 1As shown, the embodiment of the present application provides a kind of data space connector related device, comprising: a plurality of data space connection unit, first data space interactive interface, second data space interactive interface, digital contract management unit and data encryption transmission unit;

[0050] The data space connection unit includes identity management module, data resource management module and data product management module;

[0051] The identity management module is used to authenticate the identity of the user, determine the identity authentication result;Wherein, the identity authentication result includes user identity authentication or user identity authentication does not pass;Also used to refuse the data connection operation of user in the case where identity authentication result is user identity authentication different;

[0052] Through strict identity authentication and authorization mechanism, only legal user can access and use data, further enhance the security of data access.

[0053] The data resource management module is used to support user to input different formats of heterogeneous data in the case where identity authentication result is user identity authentication pass, and different sources of heterogeneous data are cleaned and converted to form shared data resource pool;

[0054] The data product management module is used to encapsulate the original data input by user into data product with standardized form;The data product is used to circulate in different data spaces;

[0055] The first data space interactive interface is used to allow user to connect to identity management module, data resource management module and data product management module, realize identity management, data sharing and product packaging;

[0056] The second data space interactive interface is used to allow different data space connection units to communicate, so that different users can access shared data resource pool and circulate data product across data space;

[0057] The digital contract management unit is used for user to customize access rules for shared data resource pool and data product, and only allow other users to access within access rules;

[0058] Data delivery function can automatically complete data preprocessing, transmission and notarization according to digital contract requirements, reduce manual intervention, improve the efficiency and accuracy of data circulation.This efficient data circulation mechanism reduces the threshold and cost of data circulation, promotes the extensive sharing and utilization of data.

[0059] Data usage rules (such as access permissions and computational purposes) can be automatically converted into technical constraint parameters, and combined with blockchain notarization technology to achieve automated management of the entire contract lifecycle. Data providers and users can quickly complete contract negotiation, signing, and filing through connectors, reducing trust costs in cross-domain cooperation. For example, medical data providers can set contract terms of "research use only," and the system will automatically restrict the scope of data use to ensure compliance. Another example is the use of attribute-based encryption to encrypt data, allowing only users with specific attributes to access the data.

[0060] The data encryption transmission unit is used to encrypt the target data and / or target data products in the shared data resource pool when the target user's access to the shared data resource pool and data products meets the access rules, to obtain the encrypted target data and / or target data products, and to transmit the encrypted target data and / or target data products to the target user through the second data space interaction interface.

[0061] Here, the target user represents the user who is accessing data, and the target data and / or target data product represents the data and / or data product in the shared data resource pool accessed by the target user.

[0062] Optionally, in addition to encryption technology, it also supports data security protection using technologies such as anonymization and privacy-preserving computing to ensure data security during transmission and storage and reduce the risk of data leakage. It can also incorporate a compliance monitoring interface and log storage function to ensure the compliance of data circulation and usage. The compliance monitoring interface can monitor in real time whether data circulation and usage behavior complies with relevant laws, regulations, and policies, reducing compliance risks. Meanwhile, the log storage function records detailed logs of data circulation and usage and supports audit traceability, making data operation behavior verifiable and traceable, improving the transparency and credibility of data management.

[0063] Optionally, the data space connector-related devices may include log storage and auditing technologies, such as blockchain, to ensure the traceability and compliance of data circulation and usage. By adopting blockchain technology, the immutability and traceability of log information are achieved, providing strong protection for data security. Simultaneously, this technology also provides rich auditing interfaces and tools, supporting comprehensive auditing and traceability of the data circulation and usage process. This robust log storage and auditing capability reduces compliance risks and improves the transparency and credibility of data management.

[0064] This invention provides a data space connector-related device that supports data sharing and value co-creation among multiple parties within a trusted data space. As a bridge for data flow, this device promotes the participation of multiple parties and the sharing and exchange of data. By accessing the connector, data service providers can offer value-added services such as computing power, artificial intelligence, and data governance, accelerating the discovery and release of data value. Simultaneously, the device also supports cross-enterprise and cross-industry industrial data exchange and collaboration, as well as cross-domain and cross-disciplinary scientific data sharing and analysis, promoting the co-creation and collaborative development of multi-party data value.

[0065] In one possible implementation, user authentication and determination of authentication results include: verifying the user's digital certificate or verifying the user's biometrics, determining whether the user has authorized the authentication, and if so, determining the authentication result as successful; otherwise, determining the authentication result as unsuccessful.

[0066] The aforementioned identity authentication function allows users to access data using authorized devices or through real-time authentication.

[0067] In one possible implementation, the step of encrypting the target data and / or target data products in the shared data resource pool to obtain encrypted target data and / or target data products includes:

[0068] Randomly generate the first round key for the AES (Advanced Encryption Standard) algorithm, and convert the first round key into a decimal number to obtain the target value corresponding to the first round key;

[0069] Set the iteration counter s = 1;

[0070] For the s-th round key, multiple different decimal numbers are randomly generated to obtain multiple different candidate values. For the AES algorithm, the number of bytes in each round key is fixed. The binary number corresponding to a round key can be set to 1 to determine the upper limit of the candidate value, and then set to 0 to determine the lower limit of the candidate value. Thus, candidate values ​​can be randomly generated between the upper and lower limits of the candidate value.

[0071] Based on the target value corresponding to the key in the first s-1 rounds, the fitness corresponding to the candidate value is obtained;

[0072] Based on the fitness corresponding to the candidate values, the optimal candidate value is determined;

[0073] Based on the optimal candidate value, the candidate value is subjected to multiple local randomization, global randomization, and perturbation randomization to determine the randomized candidate value; for example, T local randomization, global randomization, and perturbation randomization are performed, and the candidate value can be rounded after each randomization so that the candidate value can be accurately converted into a binary number.

[0074] Based on the randomized candidate values, determine the final round s key;

[0075] Determine if the value of the iteration counter s is equal to the total number of key rounds required by the AES algorithm. If so, output the keys corresponding to all rounds. Otherwise, increment the value of the iteration counter t by one and return to the step of generating candidate values.

[0076] Based on the keys corresponding to all rounds of the AES algorithm, the target data and / or target data products in the shared data resource pool are encrypted to obtain the encrypted target data and / or target data products.

[0077] In existing AES algorithms, key generation for different rounds typically involves simple XOR operations. This can lead to similar keys and correlations between them, making AES keys vulnerable to cracking. Therefore, this invention provides a key generation algorithm that incorporates randomization to reduce the correlation and similarity between AES key rounds, comprehensively improving key randomness and thus ensuring encryption security.

[0078] In one possible implementation, the fitness of the candidate value is obtained based on the target value corresponding to the key in the previous s-1 rounds, including: determining the Euclidean distance variance between the candidate value and the key in the previous s-1 rounds based on the target value corresponding to the key in the previous s-1 rounds, and obtaining the fitness of the candidate value; wherein, the larger the fitness of the candidate value, the higher the randomness of the candidate value.

[0079] In one possible implementation, the local randomization is:

[0080] X i (t+1)=ω(t)*γe bl cos(2πl)+X best (t)

[0081] ω(t)=ω min +(ω max -ω min )exp(-(t / T) 2 )

[0082] γ=|LevyX best (t)-X i (t)|

[0083] Among them, X i X(t) represents the i-th candidate value in the t-th randomization process, where i = 1, 2, ..., NP, and NP represents the total number of candidate values. i (t+1) represents the i-th candidate value after local randomization, X best ω(t) represents the optimal candidate value, ω(t) represents the local randomization range control factor, γ represents the information term, e represents the natural constant, b represents the constant term, l represents the local randomization trajectory control factor, π represents pi, and ω min ω represents the minimum value of the local randomization range control factor. max represents the maximum value of the local randomization range control factor, exp represents the exponential function with the natural constant e as the base, T represents the total number of randomizations, and Levy represents the random Levy flight factor.

[0084] The optimal candidate value is the key that differs most from other existing keys. Therefore, a local randomization method can be used to search for values ​​around the optimal candidate value to find the candidate value with greater difference.

[0085] In one possible implementation, the global randomization includes:

[0086] X m (t+1)=X m (t)+α*(X R (t)-X m (t))*ln(1 / r1)

[0087]

[0088] Among them, X m (t) represents the candidate value after the m-th local randomization in the t-th randomization process, where m = 1, 2, ..., NP, and NP represents the total number of candidate values. m (t+1) represents the m-th candidate value after global randomization, X R (t) represents a random candidate value, α represents the global randomization factor, r1 represents the first random number between (0,1), π represents pi, and T represents the total number of randomizations.

[0089] While local randomization can search around the optimal candidate value, it is inefficient and prone to missing values. Therefore, global randomization can be used to improve the search for values ​​near the candidate value, thereby increasing the likelihood of discovering more differentiated candidate values.

[0090] In one possible implementation, the perturbation randomization includes:

[0091] Xn (t+1)=X n (t)*(1+Cauchy)

[0092] Among them, X n (t) represents the candidate value after the nth global randomization in the t-th randomization process, where n = 1, 2, ..., NP, and NP represents the total number of candidate values. n (t+1) represents the nth candidate value after perturbation randomization, and Cauchy represents the Gaussian mutation operator.

[0093] Since the candidate value range is large, perturbation randomization can be used to randomly perturb the candidate value in order to avoid getting stuck in a certain extreme value. This allows the candidate value to try other values ​​and thus find a more differentiated candidate value.

[0094] This invention combines encryption algorithms with intelligent optimization algorithms and designs a fitness function, thereby generating more differentiated AES keys, reducing the correlation and similarity of AES keys at the same time, and increasing the difficulty of cracking.

[0095] In one possible implementation, it further includes: a network traffic monitoring unit;

[0096] The network traffic monitoring unit is used to collect and identify network traffic characteristics during data interaction with the data space connection unit, and determine the network traffic monitoring result; wherein, the network traffic detection result includes whether there is abnormal network access or no abnormal network access.

[0097] In one possible implementation, collecting and identifying network traffic characteristics to determine network traffic monitoring results includes: collecting network traffic characteristics and using a pre-trained neural network model to identify the network traffic characteristics and determine network traffic monitoring results.

[0098] In one possible implementation, after determining the network traffic monitoring results, the process further includes:

[0099] If the network traffic detection results indicate abnormal network access, the user's data interaction process will be terminated to ensure data interaction security.

[0100] By setting up network traffic characteristic monitoring, network security can be effectively guaranteed, thereby preventing data space from being invaded by unauthorized individuals and further ensuring data security.

[0101] This invention provides a data space connector-related device that breaks down the technical barriers in traditional data circulation through functions such as identity authentication, heterogeneous data source access, and data product encapsulation. Then, based on a dual-channel interactive interface, it enables seamless connection of data spaces from different organizations and industries, forming a cross-domain data resource pool and improving data circulation efficiency. Next, by defining custom access rules for the shared data resource pool and data products, it can effectively improve data management efficiency and reduce the trust costs of cross-domain cooperation. Finally, it encrypts data interactions, ensuring the security of data during cross-domain interactions in all aspects.

[0102] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0106] Those skilled in the art will understand that all or part of the steps in the above facts and methods can be implemented by a program instructing related hardware. The program or the program described therein can be stored in a computer-readable storage medium. When the program is executed, it includes the following steps: at this time, the corresponding method steps are introduced. The storage medium can be ROM / RAM, magnetic disk, optical disk, etc.

[0107] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A data space connector related device, characterized in that, include: Multiple data space connection units, a first data space interaction interface, a second data space interaction interface, a digital contract management unit, and a data encryption transmission unit; The data space connection unit includes an identity management module, a data resource management module, and a data product management module; The identity management module is used to authenticate users and determine the authentication result; wherein, the authentication result includes whether the user authentication is successful or unsuccessful; it is also used to refuse the user's data connection operation when the authentication result is unsuccessful. The data resource management module is used to support users to input heterogeneous data in different formats when the authentication result is that the user authentication is successful, and to clean and transform heterogeneous data from different sources to form a shared data resource pool. The data product management module is used to encapsulate the raw data input by the user into data products with a standardized form; the data products are used to circulate in different data spaces. The first data space interaction interface is used to allow users to connect to the identity management module, data resource management module, and data product management module to realize identity management, data sharing, and product encapsulation; The second data space interaction interface is used to allow different data space connection units to communicate, thereby enabling different users to access shared data resource pools across data spaces and facilitate the circulation of data products; The digital contract management unit is used by users to customize access rules for the shared data resource pool and data products, and only allows other users to access them within the access rules; The data encryption transmission unit is used to encrypt the target data and / or target data products in the shared data resource pool when the target user's access to the shared data resource pool and data products meets the access rules, to obtain the encrypted target data and / or target data products, and to transmit the encrypted target data and / or target data products to the target user through the second data space interaction interface. Here, the target user represents the user who is accessing the data, and the target data and / or target data product represents the data and / or data product in the shared data resource pool accessed by the target user. The step of encrypting the target data and / or target data products in the shared data resource pool to obtain encrypted target data and / or target data products includes: Randomly generate the first round key for the AES algorithm, and convert the first round key into a decimal number to obtain the target value corresponding to the first round key; Set the iteration counter s=1; For the key in the s-th round, multiple different decimal numbers are randomly generated, resulting in multiple different candidate values; Based on the target value corresponding to the key in the first s-1 rounds, the fitness corresponding to the candidate value is obtained; Based on the fitness corresponding to the candidate values, the optimal candidate value is determined; Based on the optimal candidate value, the candidate value is subjected to multiple local randomization, global randomization and perturbation randomization to determine the randomized candidate value. Based on the randomized candidate values, determine the final round s key; Determine if the value of the iteration counter s is equal to the total number of key rounds required by the AES algorithm. If so, output the keys corresponding to all rounds. Otherwise, increment the value of the iteration counter t by one and return to the step of generating candidate values. Based on the keys corresponding to all rounds of the AES algorithm, the target data and / or target data products in the shared data resource pool are encrypted to obtain the encrypted target data and / or target data products. The fitness of the candidate value is obtained based on the target value corresponding to the key in the previous s-1 rounds, including: determining the Euclidean distance variance between the candidate value and the key in the previous s-1 rounds based on the target value corresponding to the key in the previous s-1 rounds, and obtaining the fitness of the candidate value; wherein, the larger the fitness of the candidate value, the higher the randomness of the candidate value. The local randomization is as follows: in, Indicates the first t The first randomization process i One candidate value, i =1,2,…,NP, where NP represents the total number of candidate values. Represents the first step after local randomization. i One candidate value, Indicates the optimal candidate value. This represents the local randomization range control factor. Indicates information item, Represents the natural constant. b Represents a constant term. l This represents the local randomization trajectory control factor. Represents pi (π). This represents the minimum value of the local randomization range control factor. This represents the maximum value of the local randomization range control factor. This represents an exponential function with base e. Indicates the total number of randomizations. Represents the random Lévy flight factor; The global randomization includes: in, Indicates the first t The first randomization process m Candidate values ​​after local randomization m =1,2,…,NP, where NP represents the total number of candidate values. Represents the th after global randomization m One candidate value, Represents random candidate values. Represents the global randomization factor. Represents the first random number between (0,1). Represents pi (π). Indicates the total number of randomizations; The perturbation randomization includes: in, Indicates the first t The first randomization process n The candidate values ​​after global randomization n =1,2,…,NP, where NP represents the total number of candidate values. Indicates the first randomized perturbation. n One candidate value, This represents the Gaussian mutation operator.

2. The data space connector related device according to claim 1, characterized in that, The process involves authenticating the user and determining the authentication result, including verifying the user's digital certificate or biometrics to determine whether the user has authorized the process. If so, the authentication result is determined to be successful; otherwise, the authentication result is determined to be unsuccessful.

3. The data space connector related device according to claim 1, characterized in that, Also includes: Network traffic monitoring unit; The network traffic monitoring unit is used to collect and identify network traffic characteristics during data interaction with the data space connection unit, and determine the network traffic monitoring results; wherein, the network traffic monitoring results include the presence or absence of abnormal network access.

4. The data space connector related device according to claim 3, characterized in that, The process of collecting and identifying network traffic characteristics to determine network traffic monitoring results includes: collecting network traffic characteristics and using a pre-trained neural network model to identify these characteristics and determine the network traffic monitoring results.

5. The data space connector related device according to claim 3, characterized in that, After determining the network traffic monitoring results, the following is also included: If the network traffic detection results indicate abnormal network access, the user's data interaction process will be terminated to ensure data interaction security.

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