CN111898163A - Big data center level protection safety coefficient - Google Patents
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Abstract
The invention belongs to the technical field of big data safety management, and particularly relates to a big data center grade protection safety system which comprises a big data center grade judgment unit and a stored data grade judgment unit, wherein the big data center grade judgment unit is used for grading a big data center, the big data center grade judgment unit comprises a safety factor weight setting unit and a grade judgment algorithm unit, the stored data grade judgment unit is used for judging and storing the safety grade of data, and the stored data grade judgment unit comprises a data grade division unit and a data filing unit and protects the battery safety of a microgrid by monitoring the temperature and humidity of the microgrid and controlling the input voltage and the input power. The big data center is subjected to grade judgment through the big data center grade judgment unit, data are stored in the substation according to the grade of the big data center, the data are conveniently stored in the big data center in the same grade, and effective and safe data management of the big data center is guaranteed.
Description
Technical Field
The invention belongs to the technical field of big data security management, and particularly relates to a big data center level protection security system.
Background
Big data is often used to describe the large amount of unstructured and semi-structured data created by a company that can take excessive time and money to download to a relational database for analysis. Big data analysis is often tied to cloud computing, and big data requires special technology, and the technology of cloud computing needs to be utilized to effectively process data which is transmitted in a large amount in a data center in a period of time. The method is suitable for the technology of big data, and comprises a large-scale parallel processing database, data mining, a distributed file system, a distributed database, a cloud computing platform, the Internet and an extensible storage system. The strategic significance of big data technology is not to grasp huge data information, but to specialize the data containing significance.
The big data have corresponding requirements on the grade of the big data center when being stored, but the evaluation of the big data center in the prior art is not intelligent and convenient enough, and the evaluation of multiple influence factors on the big data center cannot be carried out, wherein when the big data center is rated, because different big data centers have different characteristic influence factors with other big data centers, the influence factors cannot be intelligently included in the traditional big data evaluation process.
Disclosure of Invention
The invention aims to provide a large data center level protection safety system to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
the big data center grade protection safety system comprises a big data center grade judgment unit and a stored data grade judgment unit, wherein the big data center grade judgment unit is used for grading a big data center, the big data center grade judgment unit comprises a safety factor weight setting unit and a grade judgment algorithm unit, the stored data grade judgment unit is used for judging and storing the safety grade of data, and the stored data grade judgment unit comprises a data grade division unit and a data archiving unit.
Preferably, the safety factor weight setting unit includes a weight value item adding module and a specific gravity setting module, the weight value item adding module is configured to add items affecting the safety level of the big data center in a user-defined manner, and the specific gravity setting module is configured to set a weight value corresponding to the items affecting the safety level of the big data center.
Preferably, the calculation formula of the grade calculation algorithm of the grade judgment algorithm unit is as follows:
wherein,
in order to determine the parameter for the level,
to influence the security level of a big data center
Completion of an item
And corresponding weighted value
Product, parameter of formula
Is shown as
Items that affect the security level of a large data center.
Preferably, the method for grading the big data center in the grade judgment algorithm unit comprises the following steps:
step S1: counting a plurality of big data center types, and carrying out data statistics on the big data centers according to an error tolerance type, a redundancy type and a basic type;
step S2: error tolerance calculationThe redundancy type and the basic type are corresponding to grade judgment parameters, and the fault tolerance type is selected
Setting the maximum value and the minimum value of the values as a primary big data center
Taking value interval and taking redundancy
Setting the maximum value to the minimum value of the values as a second-level big data center
Taking value interval and basic form
Setting the maximum value to the minimum value of the values as a three-level big data center
A value range;
step S3: computing big data centers
Value according to
The value determines the big data center tier.
Preferably, the data grading unit is used for grading the primary data, the secondary data and the tertiary data according to the medium and large data center grade.
Preferably, the primary data includes high-sensitivity internal data, the secondary data includes unpublished data with low security requirements, the tertiary data includes free public data, the primary data is stored in a primary big data center, the secondary data is stored in a secondary big data center, and the tertiary data is stored in a tertiary big data center.
Preferably, the data archiving step in the data archiving unit includes:
step S4: adding a data grade characteristic value to the data, and uploading the data;
step S5: the server reads the characteristic value of the data and correspondingly encrypts the data according to the characteristic value;
step S6: and the encrypted data is stored in the large data center of the corresponding grade.
Preferably, the characteristic value is added through a characteristic value adding algorithm formula, and the characteristic value is associated with the big data grade through a hook processing function.
Preferably, the formula of the characteristic value adding algorithm is as follows:
where u is the user, b is the transmitted data, and i is the keyword, which is the number of times the keyword i appears in the data b, and is the number of times the keyword i is used as the feature code.
Preferably, the encryption algorithm adopts an AES encryption algorithm, and the calculation formula of the AES encryption algorithm is as follows:
wherein p is a data plaintext, k is an encryption function with the length of 128 bits, and C is an encryption ciphertext.
Compared with the prior art, the invention has the beneficial effects that: when the big data center level judging unit is used for judging the level of the big data center, the data is stored in the substation according to the grade of the big data center, the data level and the big data center level correspond to three levels, the data can be conveniently stored in the big data center of the same level, and the effective and safe management of the data of the big data center is guaranteed.
Drawings
FIG. 1 is a schematic diagram of a big data level protection security system according to the present invention;
FIG. 2 is a schematic diagram of a big data center level fade unit of the present invention;
FIG. 3 is a schematic diagram of a storage data rank determination unit according to the present invention;
FIG. 4 is a diagram of a security factor weight setting unit according to the present invention;
fig. 5 is a schematic view of a big data center level classification flow according to the present invention.
In the figure: the system comprises a 1 big data center grade judging unit, a 2 storage data grade judging unit, a 101 safety factor weight setting unit, a 1011 weighted value item adding module, a 1012 proportion setting module, a 102 grade judging algorithm unit, a 201 data grade dividing unit and a 202 data filing unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, the present invention provides a technical solution:
a big data center grade protection safety system comprises a big data center grade judging unit 1 and a stored data grade judging unit 2, wherein the data center grade judging unit 1 is used for grading a big data center, the big data center grade judging unit 1 comprises a safety factor weight setting unit 101 and a grade judging algorithm unit 102, the stored data grade judging unit 2 is used for judging and storing the safety grade of data, and the stored data grade judging unit 2 comprises a data grade dividing unit 201 and a data archiving unit 202. The safety factor weight setting unit 101 includes a weight value item adding module 1011 and a specific gravity setting module 1012, the weight value item adding module 1011 is used for adding items affecting the safety level of the big data center in a user-defined manner, and the specific gravity setting module 1012 is used for setting a level calculation algorithm calculation formula of the weight value level determination algorithm unit 102 corresponding to the items affecting the safety level of the big data center as follows:
wherein,
in order to determine the parameter for the level,
to influence the security level of a big data center
Completion of an item
And corresponding weighted value
Product, parameter of formula
Is shown as
Items that affect the security level of a large data center. The method for grading the big data center in the grade judgment algorithm unit 102 comprises the following steps:
step S1: counting a plurality of big data center types, and carrying out data statistics on the big data centers according to an error tolerance type, a redundancy type and a basic type;
step S2: calculating the corresponding grade judgment parameters of the fault tolerance type, the redundancy type and the basic type, and taking the fault tolerance type
Setting the maximum value and the minimum value of the values as a primary big data center
Taking value interval and taking redundancy
Setting the maximum value to the minimum value of the values as a second-level big data center
Taking value interval and basic form
Setting the maximum value to the minimum value of the values as a three-level big data center
A value range;
step S3: computing big data centers
Value according to
The value determines the big data center tier.
The system is used for carrying out grade judgment on the big data center, the big data center is convenient to set safety protection system measures according to the grade, the big data center judges that the grade of the big data center has three grades, big data center data statistics is carried out according to an error tolerance type, a redundancy type and a basic type, big data grade judgment parameters are calculated according to the statistical data, and then value ranges of a primary big data center, a secondary big data center and a tertiary big data center are set according to three corresponding numerical value range ranges of the error tolerance type, the redundancy type and the basic type.
The data grading unit 201 grades primary data, secondary data and tertiary data according to the medium and large data center grade. The primary data comprises high-sensitivity internal data, the secondary data comprises non-public data with low safety requirements, and the tertiary data comprises free public data. The primary data are stored in the primary big data center, the secondary data are stored in the secondary big data center, and the tertiary data are stored in the tertiary big data center. The data archiving step in the data archiving unit 202 includes:
step S4: adding a data grade characteristic value to the data, and uploading the data;
step S5: the server reads the characteristic value of the data and correspondingly encrypts the data according to the characteristic value;
step S6: and the encrypted data is stored in the large data center of the corresponding grade.
The classification protection of the stored data is important in the big data center level protection, the data is classified into primary data, secondary data and tertiary data according to the big data center level, and the internal data are stored in the big data center more conveniently. The big data center perfects the aspects of machine room site selection, building structure, machine room environment, safety management and power supply safety of the big data center according to the corresponding big data center grade so as to improve the grade of the big data center.
The characteristic value is added through a characteristic value adding algorithm formula, the characteristic value is associated with the big data grade through a hook processing function, and the hook processing function can be used for linking the characteristic value with the data grade. The formula of the characteristic value adding algorithm is as follows:
wherein u is a user, b is transmitted data, i is a keyword,
is the number of times the keyword i appears in the data b,
is the number of times the keyword i is used as a feature code. The data is conveniently processed by adding the characteristic value to the data and establishing the hook connection between the characteristic value and the data grade. The encryption algorithm adopts an AES encryption algorithm, and the calculation formula of the AES encryption algorithm is as follows:
wherein p is a data plaintext, k is an encryption function with the length of 128 bits, and C is an encryption ciphertext. The data encryption enables the big data center to play a safety protection role in data storage, and data stealing is prevented.
The specific working process of the invention is as follows: when the big data center grade judgment method is used, the big data center grade is judged through the big data center grade judgment unit 1, factors influencing the big data center grade are subjected to custom addition and specific gravity setting through the safety factor weight setting unit 101, and then the big data grade judgment parameters are judged through the grade judgment algorithm unit 102
Calculating to obtain the grade of the big data center, performing security management perfection on the big data center according to the grade of the big data, and periodically judging parameters of the grade of the big data
The updating calculation is carried out to ensure the maintenance and the grade upgrading of the big data center, the big data center most intuitively reflects the grade of the big data center in the storage and the protection of data, and the data grade is classified and stored according to the grade of the big data center to ensure the safety of the big data center and the data.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. A big data center grade protection safety system comprises a big data center grade judgment unit (1) and a stored data grade judgment unit (2), and is characterized in that: the big data center grade judging unit (1) is used for grading a big data center, the big data center grade judging unit (1) comprises a safety factor weight setting unit (101) and a grade judging algorithm unit (102), the stored data grade judging unit (2) is used for judging and storing the safety grade of data, and the stored data grade judging unit (2) comprises a data grade dividing unit (201) and a data archiving unit (202); the safety factor weight setting unit (101) comprises a weight value item adding module (1011) and a specific gravity setting module (1012), wherein the weight value item adding module (1011) is used for adding items influencing the safety level of the big data center in a user-defined mode, and the specific gravity setting module (1012) is used for setting weight values corresponding to the items influencing the safety level of the big data center; the grade calculation algorithm calculation formula of the grade judgment algorithm unit (102) is as follows:
wherein,
in order to determine the parameter for the level,
to influence the security level of a big data center
Completion of an item
And corresponding weighted value
Product, parameter of formula
Is shown as
Items that affect the security level of a big data center; the method for grading the large data center in the grade judgment algorithm unit (102) comprises the following steps:
step S1: counting a plurality of big data center types, and carrying out data statistics on the big data centers according to an error tolerance type, a redundancy type and a basic type;
step S2: calculating the corresponding grade judgment parameters of the fault tolerance type, the redundancy type and the basic type, and taking the fault tolerance type
Setting the maximum value and the minimum value of the values as a primary big data center
Taking value interval and taking redundancy
Setting the maximum value to the minimum value of the values as a second-level big data center
Taking value interval and basic form
Setting the maximum value to the minimum value of the values as a three-level big data center
A value range;
step S3: computing big data centers
Value according to
The value determines the big data center tier.
2. The big data center level protection security system of claim 1, wherein: the data grade division unit (201) divides the data into primary data, secondary data and tertiary data according to the grade of a medium and large data center.
3. The big data center level protection security system of claim 2, wherein: the primary data comprises high-sensitivity internal data, the secondary data comprises non-public data with low safety requirements, the tertiary data comprises free public data, the primary data is stored in a primary big data center, the secondary data is stored in a secondary big data center, and the tertiary data is stored in a tertiary big data center.
4. The big data center level protection security system of claim 1, wherein: the data archiving step in the data archiving unit (202) includes:
step S4: adding a data grade characteristic value to the data, and uploading the data;
step S5: the server reads the characteristic value of the data and correspondingly encrypts the data according to the characteristic value;
step S6: and the encrypted data is stored in the large data center of the corresponding grade.
5. The big data center level protection security system of claim 4, wherein: the characteristic values are added through a characteristic value adding algorithm formula, and the characteristic values are associated with the big data grade through a hook processing function.
6. The big data center level protection security system of claim 5, wherein: the addition algorithm formula of the characteristic value is as follows:
wherein u is the user, b is the transmitted data, and i is offThe number of the key words is one,
is the number of times the keyword i appears in the data b,
is the number of times the keyword i is used as a feature code.
7. The big data center level protection security system of claim 6, wherein: the encryption algorithm adopts an AES encryption algorithm, and the calculation formula of the AES encryption algorithm is as follows:
wherein p is a data plaintext, k is an encryption function with the length of 128 bits, and C is an encryption ciphertext.
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| CN113395286A (en) * | 2021-06-17 | 2021-09-14 | 国网信通亿力科技有限责任公司 | Sensitive data multidimensional encryption processing method |
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