CN116028965B - Data protection method, server and storage medium in distributed LVC training environment - Google Patents
Data protection method, server and storage medium in distributed LVC training environment Download PDFInfo
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Abstract
The application discloses a data protection method, a server and a storage medium in a distributed LVC training environment, which belong to the field of data transmission protection and comprise the following steps: step 1: the method comprises the steps that a demand end sends a data request, and a cloud end receives the data request and selects a corresponding privacy protection strategy according to the service type of the data request; step 2: the sending end selects a corresponding encryption and decryption scheme to encrypt and send the private data according to the privacy protection strategy; step 3: and the cloud end or the demand end decrypts and applies the private data according to the corresponding encryption and decryption scheme. The centralized cloud platform management and control mode is beneficial to reducing links of privacy data staying in the test node, is not easy to be acquired by the test node management department, and is beneficial to permission use of the privacy data.
Description
Technical Field
The application belongs to the field of data transmission protection, and particularly relates to a data privacy protection method, a server and a storage medium in a distributed LVC training environment.
Background
When the activities such as equipment test, combat training and military scientific research are carried out, various physical, semi-physical and digital resources of various military arms, bases and scientific research departments are generally required to be used, a virtual-real combined test environment is built, and the requirements of test training and scientific research tasks are met.
In order to improve the fidelity and credibility of the training task execution process data and result data, high-quality basic data input which is as detailed and accurate as possible needs to be provided for the test environment. These basic data, such as models and key technical parameters of a certain type of equipment, certain important operation data of scientific research test stages, evaluation and identification conclusion of combat performance, etc., generally belong to private data, and need to strictly control the knowledge range. The management and control measures bring the defect of basic data supporting capability to the works of systematic test identification, high fidelity simulation of combat training and the like to be carried out.
Taking the present typical combined test environment of equipment systems as an example, the system is a cross-region and cross-army type LVC distributed simulation system, and the participants in the running state comprise army resource departments, combat command departments, test bases, laboratories, scientific research institutions and the like. In order to verify the actual effectiveness of the new equipment in the system operation, more detailed basic data is required to be used as far as possible within the supporting capacity of the physical environment of the software and the hardware, and the simulation granularity is refined. Particularly, a model of digital equipment, test data of a packaging device, scientific research data, analysis results and the like are distributed in different departments of different units, are managed according to different security levels, are difficult to share in departments needing to be used, and can not even be transmitted.
Therefore, expanding the basic data source of the combined test environment and enhancing the data supporting basic capability becomes a difficult problem to be solved in developing the combined test training task.
Disclosure of Invention
The application provides a data privacy protection method, a server and a storage medium in a distributed LVC training environment, which provide corresponding protection for various data according to security level requirements and known directions by establishing a systematic protection method strategy, and solve the problems that data sharing is difficult due to data privacy protection in the current training environment and important hidden danger is brought to important data of each participant due to lack of systematic technical protection means.
The technical effect to be achieved by the application is realized through the following scheme:
according to a first aspect of the present invention, there is provided a data protection method in a distributed LVC training environment, including the steps of:
step 1: the method comprises the steps that a demand end sends a data request, and a cloud end receives the data request and selects a corresponding privacy protection strategy according to the service type of the data request;
step 2: the sending end selects a corresponding encryption and decryption scheme to encrypt and send the private data according to the privacy protection strategy;
step 3: and the cloud end or the demand end decrypts and applies the private data according to the corresponding encryption and decryption scheme.
Preferably, the privacy protection policy includes:
when the point-to-point transmission is required, encrypting at a transmitting end and decrypting at a receiving end;
when the cloud calculates the demand, encrypting at a transmitting end, decrypting at a cloud end, calculating, and transmitting to a demand end for use;
and when the cloud computing class homomorphic calculates the requirement, encrypting at a transmitting end, and transmitting the encrypted cloud computing class homomorphic to a requirement end for decryption.
Preferably, the encryption and decryption scheme comprises an encryption and decryption type 1, an encryption and decryption type 2, an encryption and decryption type 3 and an encryption and decryption type 4; wherein the method comprises the steps of
The encryption and decryption type 1 is used for point-to-point data transmission, and the demand end receives encrypted private data sent by the sending end and uses the encrypted private data after decryption;
the encryption and decryption type 2 is used for decrypting the privacy data by the cloud end and then calculating the privacy data when the cloud end calculates, and the calculation result is directly used by the demand end;
when the encryption and decryption type 3 is used as a relay node, the cloud decrypts the private data and calculates the private data, the calculation result is encrypted again and transmitted to the demand end, and the demand end decrypts again and uses the private data;
the encryption and decryption type 4 is used for carrying out ciphertext domain operation by the cloud, and the operation result is directly decrypted for use or transmitted to the demand end for decryption processing by the demand end for use.
Preferably, encryption and decryption type 1 is selected when the point-to-point transmission is required, encryption and decryption type 2 is selected when the cloud computing is required, and encryption and decryption type 3 or encryption and decryption type 4 is selected when the cloud computing is homomorphic computing.
Preferably, the cloud receives a data request of a demand end, judges a required privacy protection policy according to the data request and the specific encryption and decryption category of the data request, marks the privacy protection policy, and distributes corresponding encryption and decryption schemes for a sending end, the cloud or the demand end respectively.
Preferably, in the encryption and decryption scheme, the encryption method specifically comprises the following steps: the private data is sent after digital signature and AES encryption; and when decrypting, after receiving the privacy data, verifying the digital signature correctly, and then decrypting.
Preferably, the method for digital signature is as follows:
generating an asymmetrically encrypted key pair and distributing a public key to a demand end;
carrying out hash operation on the original data by using a hash function, obtaining an original characteristic hash value after operation, and encrypting the hash value by using a private key to obtain a ciphertext;
sending the original data and the ciphertext to a demand end;
the digital signature verification method comprises the following steps:
the demand end receives the public key, the original data and the ciphertext;
carrying out hash operation on the original data by adopting the same hash function to obtain a new characteristic hash value;
and decrypting the ciphertext by using the public key, comparing the new characteristic hash value with the original characteristic hash value, and if the new characteristic hash value is the same as the original characteristic hash value, checking the digital signature to be correct.
Preferably, the homomorphism calculation mode is as follows: and (3) carrying out software encapsulation on the calculation process, isolating user interaction, and carrying out secret state calculation from a software layer.
According to a second aspect of the present invention, there is provided a server comprising: a memory and at least one processor;
the memory stores a computer program, and the at least one processor executes the computer program stored in the memory to implement the data protection method in the distributed LVC training environment.
According to a third aspect of the present invention, there is provided a computer readable storage medium having stored therein a computer program which when executed implements the method of data protection in a distributed LVC training environment as described above.
The method has the technical effects that the centralized cloud platform management and control mode is beneficial to reducing the links of the private data staying at the test node, is not easy to be acquired by the test node management department, and is beneficial to the permission of the private data;
the data is encrypted in the transmission process, so that the original data cannot be exposed even if the data is intercepted; in the calculation and storage processes of the data, the data are carried out in a ciphertext state, so that the exposure of a plaintext is avoided; in the using process, if the relevance logic between the new data and the old data is strong, continuing to protect and use the data, and if the front-back logic relevance randomness is strong, performing control of non-technical means and decrypting and then using the data.
Drawings
In order to more clearly illustrate the embodiments or prior art solutions of the present application, the drawings that are required for the description of the embodiments or prior art will be briefly described below, it being apparent that the drawings in the following description are only some of the embodiments described in the present application, and that other drawings may be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a flowchart of a method for protecting data privacy in a distributed LVC training environment according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a server according to an embodiment of the present application.
Detailed Description
For the purposes, technical solutions and advantages of the present application, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
As shown in fig. 1, the data protection method in the distributed LVC training environment in an embodiment of the present application includes the following steps:
s110: the method comprises the steps that a demand end sends a data request, and a cloud end receives the data request and selects a corresponding privacy protection strategy according to the service type of the data request;
in this step, in the distributed LVC test environment, the service activity and the information activity in the running state have a corresponding relationship, the information activity is a main basis for classifying the data transmission requirements, a series of data transmission requirements and transmission activities are generated in the information activity, and the privacy requirements can be defined according to the specific data transmitted in the information activity. Specific information activities, input/output data, and privacy degree relationships are shown in table 1:
table 1 transmission information of information campaigns
The information activities in the test implementation stage comprise command issuing, resource state reporting, measurement data reporting, data fusion, data processing, situation fusion, situation pushing, situation displaying, test scheduling, test data warehouse entry and the like. Such information presents a multi-link transmission characteristic, creating protection requirements at different network locations.
The information activity in the post-test evaluation stage comprises test data reading, test data analysis, test result evaluation and the like. The information is mainly concentrated on the computing and storage nodes of the management and control platform, and is mainly transmitted by an intranet, so that privacy protection is relatively convenient.
Therefore, aiming at the characteristics of the joint test system structure and the service, a strategy for protecting the data privacy is constructed by taking the data transmission and the use process as objects.
In the transmission link, the private data needs to be encrypted, so that even if a third party intercepts the private data, the bare data cannot be directly obtained. In the cloud computing link, there are two cases, one is that decryption is performed and then computation is performed, data isolation is needed in the cases, and decrypted data can only be stored in the cloud and cannot be transmitted to other nodes; the second is to perform homomorphic calculation in the encrypted state. In the using link, three conditions exist, one is data after cloud computing, and the data is directly used; the second is the data after homomorphic calculation, and the data is used after decryption; thirdly, after receiving the encrypted data, carrying out homomorphic calculation, wherein the calculation result can be used in a decrypting way.
According to the confidentiality requirements of transmission, cloud computing and use links, the following data privacy protection strategies are given:
1. when the point-to-point transmission is required, encrypting at a transmitting end and decrypting at a receiving end;
2. when the cloud calculates the demand, encrypting at a transmitting end, decrypting at a cloud end, calculating, and transmitting to a demand end for use;
3. and when the cloud computing class homomorphic calculates the requirement, encrypting at a transmitting end, and transmitting the encrypted cloud computing class homomorphic to a requirement end for decryption.
S120: the sending end selects a corresponding encryption and decryption scheme to encrypt and send the private data according to the privacy protection strategy;
in this step, when each data demander in the joint test environment issues a data request, a specific operation type of encryption protection should be given according to the difference of encryption service requirements. The cloud end receives the data request of the demand end, marks and judges according to the data request of the data request and the specific encryption and decryption category, and distributes corresponding encryption and decryption schemes for the sending end, the cloud end or the demand end respectively.
In a series of private data transmission processes, encryption and decryption schemes are required to be distributed among all nodes so as to adapt to different demands of different nodes on data privacy confidentiality.
The encryption and decryption scheme comprises an encryption and decryption type 1, an encryption and decryption type 2, an encryption and decryption type 3 and an encryption and decryption type 4; wherein:
the encryption and decryption type 1 is used for point-to-point data transmission, and the demand end receives encrypted private data sent by the sending end and uses the encrypted private data after decryption;
the encryption and decryption type 2 is used for decrypting the privacy data by the cloud end and then calculating the privacy data when the cloud end calculates, and the calculation result is directly used by the demand end;
when the encryption and decryption type 3 is used as a relay node, the cloud decrypts the private data and calculates the private data, the calculation result is encrypted again and transmitted to the demand end, and the demand end decrypts again and uses the private data;
the encryption and decryption type 4 is used for carrying out ciphertext domain operation by the cloud, and the operation result is directly decrypted for use or transmitted to the demand end for decryption processing by the demand end for use.
The encryption and decryption type 1 is selected when the point-to-point transmission is required, the encryption and decryption type 2 is selected when the cloud computing is required, and the encryption and decryption type 3 or the encryption and decryption type 4 is selected when the cloud computing is homomorphic computing is required.
Because the test environment spans a large area and usually relates to a public communication backbone network, a digital signature technology is required to be adopted to verify data, the data integrity is ensured, and the encryption mode is as follows: the sending end carries out digital signature and AES encryption on the private data and then sends the private data. For most transmission and storage situations in the test environment, encryption and decryption and encryption state storage can be performed by adopting a symmetrical encryption method. The AES symmetric encryption algorithm is safe and efficient, and the key length is typically several of 16 bytes, 24 bytes, and 32 bytes. Block encryption is further typically employed to encrypt, block by block, each set of 16 bytes, whether ciphertext or plaintext. The distribution process of the secret key does not pass through the trial network. In other embodiments, different encryption schemes may be selected for encryption depending on the type of data.
The digital signature method comprises the following steps:
first, the data is encrypted using a private key. Generating an asymmetrically encrypted key pair and distributing a public key to a demand end;
carrying out hash operation on the original data by using a hash function, obtaining an original characteristic hash value after operation, and encrypting the hash value by using a private key to obtain a ciphertext;
and sending the original data and the ciphertext to the demand end.
S130: and the cloud end or the demand end decrypts and applies the private data according to the corresponding encryption and decryption scheme.
In this step, the demand end performs decryption processing after checking that the digital signature is correct after receiving the private data. The verification is mainly used for identifying the identity of the node for confirming the transmitted data. The digital signature method generates the check code irreversibly, which belongs to the protection measure of unidirectional transmission and has no encryption and decryption characteristics.
The digital signature verification method comprises the following steps:
the demand end firstly receives a public key distributed by a sending node, and then receives original data and ciphertext;
carrying out hash operation on the original data by adopting the same hash function (namely the hash function must use the same hash function as the signature party) to obtain a new characteristic hash value;
and decrypting the ciphertext by using the public key, comparing the new characteristic hash value with the original characteristic hash value, if the digital signature is the same, checking the digital signature correctly, and if the digital signature is different, the digital signature is incomplete or tampered.
In one embodiment of the present application, the homomorphism calculation method is as follows: and (3) carrying out software encapsulation on the computing process, isolating user interaction, and carrying out secret state computing from a software layer, wherein the process information cannot be directly read.
In a specific example, if real-time measurement data information is input and data fusion information is output, a request is sent out at a demand end, and the cloud judges the operation activity (such as the information to be output and the security level thereof) required to be performed by the request, and selects a corresponding privacy protection policy: when the cloud calculates the demand, encrypting at a transmitting end, decrypting at a cloud end, calculating, and transmitting to a demand end for use; and corresponding encryption and decryption schemes (encryption and decryption type 2) are distributed;
the sending end inputs real-time measurement data information according to the privacy protection strategy, encrypts and sends the information to the cloud end, decrypts the data by the cloud end, calculates the data, obtains data fusion information and directly sends the data fusion information to the demand end for use.
As shown in fig. 2, the server in an embodiment of the present application includes: a memory 201 and at least one processor 202;
the memory 201 stores a computer program, and the at least one processor 202 executes the computer program stored in the memory 201 to implement the data protection method in the distributed LVC training environment.
In an embodiment of the present application, a computer readable storage medium is provided, in which a computer program is stored, and the data protection method in the distributed LVC training environment is implemented when the computer program is executed.
The method has the technical effects that the centralized cloud platform management and control mode is beneficial to reducing the links of the private data staying at the test node, is not easy to be acquired by the test node management department, and is beneficial to the permission of the private data; the data is encrypted in the transmission process, so that the original data cannot be exposed even if the data is intercepted; in the calculation and storage processes of the data, the data are carried out in a ciphertext state, so that the exposure of a plaintext is avoided; in the using process, if the association logic between new and old data is strong, continuing to protect and use the data, and if the association logic between front and back logic is strong, controlling and decrypting by non-technical means and then using the data.
It should be noted that the foregoing detailed description is exemplary and is intended to provide further explanation of the invention. 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 application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular is intended to include the plural unless the context clearly indicates otherwise. Furthermore, it will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, steps, operations, devices, components, and/or groups thereof.
It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or otherwise described herein.
Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Spatially relative terms, such as "above … …," "above … …," "upper surface at … …," "above," and the like, may be used herein for ease of description to describe one device or feature's spatial location relative to another device or feature as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is turned over, elements described as "above" or "over" other devices or structures would then be oriented "below" or "beneath" the other devices or structures. Thus, the exemplary term "above … …" may include both orientations of "above … …" and "below … …". The device may also be positioned in other different ways, such as rotated 90 degrees or at other orientations, and the spatially relative descriptors used herein interpreted accordingly.
In the above detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, like numerals typically identify like components unless context indicates otherwise. The illustrated embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments may be utilized, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The data protection method in the distributed LVC training environment is characterized by comprising the following steps of:
step 1: the method comprises the steps that a demand end sends a data request, and a cloud end receives the data request and selects a corresponding privacy protection strategy according to the service type of the data request; the privacy protection policy includes:
when the point-to-point transmission is required, encrypting at a transmitting end and decrypting at a receiving end;
when the cloud calculates the demand, encrypting at a transmitting end, decrypting at a cloud end, calculating, and transmitting to a demand end for use;
when the cloud computing class homomorphic computing demands, encrypting at a transmitting end, and transmitting to a demand end for decryption after the cloud computing class homomorphic computing;
step 2: the sending end selects a corresponding encryption and decryption scheme to encrypt and send the private data according to the privacy protection strategy; the encryption and decryption scheme comprises an encryption and decryption type 1, an encryption and decryption type 2, an encryption and decryption type 3 and an encryption and decryption type 4; wherein the method comprises the steps of
The encryption and decryption type 1 is used for point-to-point data transmission, and the demand end receives encrypted private data sent by the sending end and uses the encrypted private data after decryption;
the encryption and decryption type 2 is used for decrypting the privacy data by the cloud end and then calculating the privacy data when the cloud end calculates, and the calculation result is directly used by the demand end;
when the encryption and decryption type 3 is used as a relay node, the cloud decrypts the private data and calculates the private data, the calculation result is encrypted again and transmitted to the demand end, and the demand end decrypts again and uses the private data;
the encryption and decryption type 4 is used for carrying out ciphertext domain operation by the cloud, and the operation result is directly decrypted for use or transmitted to the demand end for decryption processing by the demand end for use;
step 3: and the cloud end or the demand end decrypts and applies the private data according to the corresponding encryption and decryption scheme.
2. The method for protecting data in a distributed LVC training environment according to claim 1, wherein an encryption type 1 is selected when a point-to-point transmission is required, an encryption type 2 is selected when a cloud computing is required, and an encryption type 3 or an encryption type 4 is selected when a cloud computing is homomorphic computing.
3. The method for protecting data in a distributed LVC training environment according to claim 1, wherein the cloud receives a data request from a demand end, judges a required privacy protection policy according to the data request and a specific encryption and decryption category of the data request, marks the privacy protection policy, and distributes corresponding encryption and decryption schemes for a transmitting end, the cloud or the demand end respectively.
4. The method for protecting data in a distributed LVC training environment according to claim 1, wherein in the encryption/decryption scheme, the encryption method specifically comprises: the private data is sent after digital signature and AES encryption; and when decrypting, after receiving the privacy data, verifying the digital signature correctly, and then decrypting.
5. The method for protecting data in a distributed LVC training environment according to claim 4, wherein the method for digital signature is:
generating an asymmetrically encrypted key pair and distributing a public key to a demand end;
carrying out hash operation on the original data by using a hash function, obtaining an original characteristic hash value after operation, and encrypting the hash value by using a private key to obtain a ciphertext;
sending the original data and the ciphertext to a demand end;
the digital signature verification method comprises the following steps:
the demand end receives the public key, the original data and the ciphertext;
carrying out hash operation on the original data by adopting the same hash function to obtain a new characteristic hash value;
and decrypting the ciphertext by using the public key, comparing the new characteristic hash value with the original characteristic hash value, and if the new characteristic hash value is the same as the original characteristic hash value, checking the digital signature to be correct.
6. The method for protecting data in a distributed LVC training environment according to claim 1, wherein the homomorphic calculation mode is as follows: and (3) carrying out software encapsulation on the calculation process, isolating user interaction, and carrying out secret state calculation from a software layer.
7. A server, comprising: a memory and at least one processor;
the memory stores a computer program, and the at least one processor executes the computer program stored by the memory to implement the method of data protection in a distributed LVC training environment of any one of claims 1 to 6.
8. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program which, when executed, implements the method for protecting data in a distributed LVC training environment according to any one of claims 1 to 6.
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