CN115618398A - System and method for encrypting user information of network database - Google Patents
System and method for encrypting user information of network database Download PDFInfo
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- CN115618398A CN115618398A CN202211635939.6A CN202211635939A CN115618398A CN 115618398 A CN115618398 A CN 115618398A CN 202211635939 A CN202211635939 A CN 202211635939A CN 115618398 A CN115618398 A CN 115618398A
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- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000008569 process Effects 0.000 claims abstract description 13
- 230000011218 segmentation Effects 0.000 claims description 31
- 239000013598 vector Substances 0.000 claims description 29
- 238000004891 communication Methods 0.000 claims description 12
- 238000012545 processing Methods 0.000 claims description 6
- 238000013145 classification model Methods 0.000 claims description 4
- 230000008901 benefit Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 1
- 238000005206 flow analysis Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/602—Providing cryptographic facilities or services
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
- G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
Abstract
The invention discloses a system and a method for encrypting user information of a network database, wherein the system comprises a semantic identification module, a selection module and an encryption module; the semantic recognition module is used for performing semantic recognition on the stored user information to acquire sensitive data in the user information; the selection module is used for selecting a text to be encrypted from the sensitive data according to a set rule; the encryption module is used for encrypting the text to be encrypted by using a set encryption algorithm to obtain the encrypted user information. The method corresponds to the system. In the process of encrypting the user information stored in the network database, the sensitive data is firstly obtained through semantic recognition, then the text in the sensitive data is screened, and finally the screened text is encrypted.
Description
Technical Field
The invention relates to the field of data encryption, in particular to a system and a method for encrypting user information of a network database.
Background
In the process of storing user information, the network database needs to encrypt and store sensitive data such as names, telephones, addresses and the like, so that sensitive information of users is prevented from being leaked after the network database is attacked. In the prior art, generally, the identified sensitive data is directly and completely encrypted, and the encryption mode easily causes excessive data to be encrypted, so that the performance requirement of the database server in the aspect of data encryption is high, which affects the retrieval performance of the database.
Disclosure of Invention
The invention aims to disclose a system and a method for encrypting user information of a network database, which solve the problems that when sensitive data is encrypted in the prior art, the sensitive data is directly and completely encrypted, so that the performance requirement on the aspect of data encryption is high, and the retrieval performance of the database is influenced.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the invention provides a network database user information encryption system, which comprises a semantic identification module, a selection module and an encryption module;
the semantic recognition module is used for performing semantic recognition on the stored user information and acquiring sensitive data in the user information;
the selection module is used for selecting a text to be encrypted from the sensitive data according to a set rule;
the encryption module is used for encrypting the text to be encrypted by using a set encryption algorithm to obtain the encrypted user information.
Optionally, the network database user information encryption system further includes a user module;
the user module is used for inputting user information by a user.
Optionally, the network database user information encryption system further includes a communication module and a storage module;
the communication module is used for communicating with the user module;
the user module is also used for encrypting the user information and transmitting the encrypted user information to the communication module;
the communication module is also used for receiving the encrypted user information and transmitting the encrypted user information to the storage module;
the storage module is used for decrypting the encrypted user information to obtain the decrypted user information and storing the decrypted user information.
Optionally, the user module encrypts the user information by using the public key of the storage module to obtain the encrypted user information;
the storage module decrypts the encrypted user information by using a private key of the storage module to obtain the decrypted user information.
Optionally, performing semantic recognition on the stored user information to obtain sensitive data in the user information, including:
acquiring text characteristics of a text contained in user information;
inputting the text features into a pre-trained text classification model for classification, and determining the type of the text;
it is determined whether the text is sensitive data based on the type of text.
Optionally, obtaining text features of a text included in the user information includes:
performing word segmentation on the text to obtain the text after word segmentation;
and acquiring text characteristics of the segmented text.
Optionally, performing word segmentation on the text to obtain a word-segmented text, including:
and performing word segmentation processing on the text by using a word segmentation algorithm based on a dictionary to obtain the text after word segmentation.
Optionally, the obtaining of the text feature of the text after word segmentation includes:
acquiring text to form a text vector;
acquiring the weight of each text vector;
and taking the text vector and the weight of the text vector as text features.
Optionally, obtaining the weight of each text vector includes:
the weights of the text vectors are obtained using the TF-IDF algorithm.
In a second aspect, the present invention provides a method for encrypting user information of a network database, including:
performing semantic recognition on the stored user information to acquire sensitive data in the user information;
selecting a text to be encrypted from the sensitive data according to a set rule;
and encrypting the text to be encrypted by using a set encryption algorithm to obtain the encrypted user information.
In the process of encrypting the user information stored in the network database, the sensitive data is firstly obtained through semantic recognition, then the text in the sensitive data is screened, and finally the screened text is encrypted.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic diagram of a network database user information encryption system according to the present invention.
Fig. 2 is a schematic diagram of a method for encrypting user information of a network database according to the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
In a first aspect, as an embodiment shown in fig. 1, the present invention provides a network database user information encryption system, which includes a semantic recognition module 101, a selection module 102, and an encryption module 103;
the semantic recognition module 101 is configured to perform semantic recognition on the stored user information, and acquire sensitive data in the user information;
the selection module 102 is configured to select a text to be encrypted from the sensitive data according to a set rule;
the encryption module 103 is configured to encrypt a text to be encrypted by using a set encryption algorithm, so as to obtain encrypted user information.
Optionally, the network database user information encryption system further includes a user module;
the user module is used for inputting user information by a user.
In the process of encrypting the user information stored in the network database, the sensitive data is firstly obtained through semantic recognition, then the text in the sensitive data is screened, and finally the screened text is encrypted.
In the process of encrypting the sensitive data, the invention only encrypts partial participles in the sensitive data, thereby reducing the number of the participles needing to be encrypted while keeping the encryption effect as much as possible.
For example, when encrypting the contact, a word is randomly selected from the text representing the contact to be encrypted, so as to obtain the result needing encryption. Even if the encrypted contact information is illegally acquired, the user information cannot be leaked.
In one embodiment, the network database user information encryption system further comprises a communication module and a storage module;
the communication module is used for communicating with the user module;
the user module is also used for encrypting the user information and transmitting the encrypted user information to the communication module;
the communication module is also used for receiving the encrypted user information and transmitting the encrypted user information to the storage module;
the storage module is used for decrypting the encrypted user information to obtain the decrypted user information and storing the decrypted user information.
In the uploading link of the user information, the user information is encrypted and then transmitted, so that data leakage of the user information in the transmission process can be avoided.
In one embodiment, performing semantic recognition on the stored user information to acquire sensitive data in the user information includes:
and performing semantic recognition on the user information stored in the storage module to acquire sensitive data in the user information.
In one embodiment, selecting text to be encrypted from sensitive data according to a set rule includes:
randomly selecting Q participles from the sensitive data as participles needing to be encrypted;
and taking the selected participles needing to be encrypted as texts needing to be encrypted.
In one embodiment, encrypting a text to be encrypted by using a set encryption algorithm to obtain encrypted user information includes:
acquiring a character code of a text needing to be encrypted;
encrypting the character code by using a preset encryption algorithm to obtain the encrypted character code;
acquiring word codes of word segmentation which do not need to be encrypted;
and taking the encrypted character code and the character code of the word segmentation which does not need to be encrypted as the encrypted user information.
In one embodiment, the user module encrypts the user information by using the public key of the storage module to obtain the encrypted user information;
the storage module decrypts the encrypted user information by using a private key of the storage module to obtain the decrypted user information.
Specifically, an asymmetric encryption mode is adopted, the encryption safety is higher, and even if the user information is maliciously subjected to flow analysis in the process of being transmitted to the storage module by the user module, the encrypted user information cannot be decrypted under the condition of no private key, so that the safety of the transmission process of the user information is ensured.
The asymmetric encryption algorithm adopted can be an RSA algorithm, an ECC algorithm and the like.
RSA public key cryptosystems are based on the principle that finding two large prime numbers is relatively simple, and decomposing their product is extremely difficult, according to number theory, so that the product can be made public as an encryption key.
The main advantage of ECC is that it provides an equal or higher level of security using smaller keys than other methods (such as the RSA encryption algorithm) in some cases. Another advantage of ECC is that it can define bilinear mappings between groups based on Weil pairs or Tate pairs; bilinear mappings have many applications in cryptography, such as identity-based encryption. However, one disadvantage is that the implementation of encryption and decryption operations takes longer than other mechanisms.
In one embodiment, performing semantic recognition on the stored user information to acquire sensitive data in the user information includes:
acquiring text characteristics of texts contained in user information;
inputting the text features into a pre-trained text classification model for classification, and determining the type of the text;
it is determined whether the text is sensitive data based on the type of text.
In particular, the text classification model may include a machine learning-based model or a deep learning-based model.
Machine learning based models include RF models, KNN models, and the like. The deep learning-based models include a fastText model, a TextCNN model, a TextRNN model, and the like.
Specifically, the type of text includes address, name, phone call, shopping record, personal profile, signature information, and the like.
Specifically, determining whether the text is sensitive data based on the type of the text includes:
acquiring a set NM of data types of sensitive data;
and judging that the type of the text is an element of the set NM, if so, indicating that the text is sensitive data, and if not, indicating that the text does not belong to the sensitive data.
In one embodiment, obtaining text features of text contained in user information includes:
performing word segmentation on the text to obtain the text after word segmentation;
and acquiring text characteristics of the text after word segmentation.
Specifically, stop words such as adverbs and adjectives need to be removed in the process of word segmentation processing.
In one embodiment, performing word segmentation on a text to obtain a word-segmented text includes:
and performing word segmentation processing on the text by using a word segmentation algorithm based on a dictionary to obtain the text after word segmentation.
In the word segmentation algorithm based on the dictionary, the core is to establish a unified dictionary firstly. When a sentence needs to be participled, the sentence is firstly divided into a plurality of parts, and each part corresponds to the dictionary one by one. If the word is in the dictionary, the word segmentation is successful, otherwise, the splitting and matching are continued until the word segmentation is successful. Thus, the dictionary, the segmentation rules, and the matching order are the core of the dictionary-based word segmentation algorithm.
In another embodiment, performing word segmentation on a text to obtain a word-segmented text includes:
and performing word segmentation processing on the text by using a word segmentation algorithm based on statistics to obtain the text after word segmentation.
In one embodiment, obtaining text features of the segmented text comprises:
acquiring text to form a text vector;
acquiring the weight of each text vector;
and taking the text vector and the weight of the text vector as text features.
Specifically, the text vector may be represented as:
n denotes the number of different participles and the weight is expressed as
。
Optionally, obtaining the weight of each text vector includes:
the weights of the text vectors are obtained using the TF-IDF algorithm.
Specifically, the invention improves the TF-IDF algorithm, and obtains the weight of the text vector by using the TF-IDF algorithm, wherein the weight comprises the following steps:
calculating the frequency TF of the vector appearing in the user information:
calculating the frequency IDF of the reverse file:
wherein, the first and the second end of the pipe are connected with each other,
the vector is represented by a vector of values,
the representation of the text is carried out by,
to represent
Is contained in
The number of the (c) is (c),
representing a collection of different text in the user information,
number representing different text contained in user informationThe amount of the (B) component (A),
representing inclusion vectors
The number of texts of (a);
calculating a vector
The weight of (c):
wherein the content of the first and second substances,
representing a vector
The weight of (a) is calculated,
represents a pre-set auxiliary calculation coefficient,
representing a vector
The adjustment coefficient of (2) is set,
representing a vector
Average number of primary selections in all texts.
In the process of calculating the weight, the weight calculation function is mainly improved, and by setting the adjusting coefficient, the weight value of a vector which only appears in a single text and does not appear in other texts in the text can be improved.
In a second aspect, as an embodiment shown in fig. 2, the present invention provides a method for encrypting user information of a network database, including:
and step 203, encrypting the text to be encrypted by using a set encryption algorithm to obtain the encrypted user information.
It should be noted that, the above numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one.. Said.", it is not intended to exclude that an additional identical element is present in a process, apparatus, article or method that includes the same element.
Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method of the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but in many cases, the former is a better implementation. Based on such understanding, the technical solution of the present invention essentially or contributing to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) as described above and includes several instructions for enabling a terminal device (such as a mobile phone, a computer, an electronic device, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A network database user information encryption system is characterized by comprising a semantic recognition module, a selection module and an encryption module;
the semantic recognition module is used for performing semantic recognition on the stored user information to acquire sensitive data in the user information;
the selection module is used for selecting a text to be encrypted from the sensitive data according to a set rule;
the encryption module is used for encrypting the text to be encrypted by using a set encryption algorithm to obtain the encrypted user information.
2. The system for encrypting the user information of the network database according to claim 1, further comprising a user module;
the user module is used for inputting user information by a user.
3. The system for encrypting the user information of the network database according to claim 2, further comprising a communication module and a storage module;
the communication module is used for communicating with the user module;
the user module is also used for encrypting the user information and transmitting the encrypted user information to the communication module;
the communication module is also used for receiving the encrypted user information and transmitting the encrypted user information to the storage module;
the storage module is used for decrypting the encrypted user information to obtain the decrypted user information and storing the decrypted user information.
4. The system of claim 3, wherein the user module encrypts the user information using the public key of the storage module to obtain the encrypted user information;
the storage module decrypts the encrypted user information by using a private key of the storage module to obtain the decrypted user information.
5. The system for encrypting the user information of the network database according to claim 1, wherein the semantic recognition of the stored user information to obtain the sensitive data in the user information comprises:
acquiring text characteristics of a text contained in user information;
inputting the text features into a pre-trained text classification model for classification, and determining the type of the text;
it is determined whether the text is sensitive data based on the type of text.
6. The system for encrypting the user information of the network database according to claim 5, wherein the obtaining of the text feature of the text included in the user information comprises:
performing word segmentation processing on the text to obtain a word-segmented text;
and acquiring text characteristics of the text after word segmentation.
7. The system for encrypting the user information in the network database according to claim 6, wherein the process of segmenting words of the text to obtain the segmented text comprises:
and performing word segmentation processing on the text by using a word segmentation algorithm based on a dictionary to obtain the text after word segmentation.
8. The system for encrypting the user information of the network database according to claim 6, wherein the obtaining of the text feature of the segmented text comprises:
acquiring text to form a text vector;
acquiring the weight of each text vector;
and taking the text vector and the weight of the text vector as text features.
9. The system for encrypting the user information of the network database according to claim 8, wherein the obtaining of the weight of each text vector comprises:
the weights of the text vectors are obtained using the TF-IDF algorithm.
10. A network database user information encryption method is characterized by comprising the following steps:
performing semantic recognition on the stored user information to acquire sensitive data in the user information;
selecting a text to be encrypted from the sensitive data according to a set rule;
and encrypting the text to be encrypted by using a set encryption algorithm to obtain the encrypted user information.
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Application publication date: 20230117 |