CN113129395B - Data compression encryption system - Google Patents
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- CN113129395B CN113129395B CN202110497683.6A CN202110497683A CN113129395B CN 113129395 B CN113129395 B CN 113129395B CN 202110497683 A CN202110497683 A CN 202110497683A CN 113129395 B CN113129395 B CN 113129395B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T9/00—Image coding
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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
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/04—Protocols for data compression, e.g. ROHC
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
- H04L9/0861—Generation of secret information including derivation or calculation of cryptographic keys or passwords
Abstract
The invention discloses a data compression encryption system, which belongs to the technical field of data compression encryption and aims to solve the problem that more and more data need to be stored and transmitted and also face the risk of data stealing during transmission, and the data compression encryption system comprises a compression library, an encryption module, an administrator module, a decryption module, a server and a storage module; the compression library is used for establishing a data compression corresponding library, acquiring data to be compressed, establishing a data segmentation model, inputting the data to be compressed and preset segmentation conditions into the data segmentation model to obtain a plurality of data segments, inputting the data segments into the coding model to obtain corresponding data segment codes, arranging the data segment codes according to the compressed data before data segmentation, inputting the input data segments into the coding table for storage when the input data segments are not successfully matched with the coding table, and automatically updating the data segments without input and performing real-time supplementary recording.
Description
Technical Field
The invention belongs to the technical field of data compression and encryption; in particular to a data compression encryption system.
Background
With the development of internet technology and cloud computing technology, more and more data need to be stored and transmitted, the storage and transmission cost of the mass data is very high, and meanwhile, the risk of data stealing is also faced during transmission.
Disclosure of Invention
The invention aims to provide a data compression encryption system, which solves the problem that more and more data need to be stored and transmitted, and simultaneously faces the risk of data stealing during transmission.
The purpose of the invention can be realized by the following technical scheme:
a data compression encryption system comprises a compression library, an encryption module, an administrator module, a decryption module, a server and a storage module; the compression library is used for establishing a data compression corresponding library, acquiring data to be compressed, establishing a data segmentation model, inputting the data to be compressed and preset segmentation conditions into the data segmentation model to obtain a plurality of data segments, inputting the data segments into a coding model to obtain corresponding data segment codes, arranging the data segment codes according to the compressed data before data segmentation, and deleting the segmented data;
the encryption module is used for encrypting the data segment codes to obtain a high-definition picture, the data segment codes needing to be compressed and encrypted are obtained from a compression library, the data segment codes needing to be compressed and encrypted are marked as encryption codes, the high-definition picture is divided into a plurality of image blocks, the number of the image blocks is more than that of the encryption codes, the number of the encryption codes is marked as N, N image blocks are randomly selected from the image blocks, the obtained encryption codes are randomly distributed into the N image blocks according to the sequence, a distribution record is generated, the unselected image blocks in the high-definition picture are marked as confusion blocks, the number of the confusion blocks is marked as Z, Z codes are randomly selected from a code table, the selected Z codes are randomly distributed into the confusion blocks, and the high-definition picture is marked as the encryption picture.
Further, the method for establishing the data segmentation model comprises the following steps: acquiring a plurality of groups of historical compressed data, setting preset segmentation conditions, constructing an artificial intelligence model, inputting the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning and training, and dividing the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a check set according to a set proportion; training, testing and checking the artificial intelligence model through the training set, the testing set and the checking set, and marking the trained artificial intelligence model as a data segmentation model.
Further, the method for establishing the coding model comprises the following steps: acquiring a plurality of groups of historical data segments, summarizing the historical data segments, deleting the repeated data segments, sorting the deleted historical data segments according to the segmentation time and the data size, encoding the sorted historical data segments, establishing an encoding table, setting a matching unit for matching the input data segments with the encoding table, inputting the input data segments into the encoding table for storage when the input data segments are not successfully matched with the encoding table, and generating corresponding data segment codes according to the encoding sequence; and when the input data segment is successfully matched with the coding table, obtaining the corresponding data segment code.
Furthermore, the encryption module comprises a jigsaw unit, the jigsaw unit is used for encrypting the distribution records, a plurality of pictures are stored in the jigsaw unit, one picture is selected from the plurality of pictures to be a jigsaw picture, the number of parts of the jigsaw picture is selected, V parts of pictures are randomly selected from the divided pictures, and the correct arrangement patterns of the V parts of pictures are set and stored.
Further, the administrator module is used for an administrator to log in the management system, obtain verified face identification information and fingerprint information, match the obtained face identification information and fingerprint information with administrator information in the storage module, when matching is successful, login is successful, and when matching is failed, an alarm signal is generated to photograph and store the verified person.
Further, the decryption module is configured to decrypt the encrypted data to obtain an encrypted picture, perform verification in the puzzle unit to obtain a distribution record, sequentially extract encrypted codes from the encrypted picture according to the distribution record, match the encrypted codes with the code table to obtain corresponding data segments, and then obtain decrypted data after successful decryption.
The invention has the beneficial effects that: the method comprises the steps of dividing data into data segments through the setting of a data division model, summarizing historical data segments, deleting repeated data segments, avoiding the influence of the repeated data segments on data encryption, sequencing the deleted historical data segments according to division time and data size, coding the sequenced historical data segments, establishing a coding table, facilitating encryption and decryption, setting a matching unit, matching the input data segments with the coding table, inputting the input data segments into the coding table for storage when the input data segments are not successfully matched with the coding table, automatically updating the data segments which are not recorded, performing real-time logging, and generating corresponding data segment codes according to the coding sequence; when the input data segment is successfully matched with the coding table, obtaining the corresponding data segment code;
encrypting the data segment codes through an encryption module to obtain a high-definition picture, obtaining the data segment codes needing to be compressed and encrypted from a compression library, marking the data segment codes needing to be compressed and encrypted as encryption codes, dividing the high-definition picture into a plurality of image blocks, wherein the number of the image blocks is more than that of the encryption codes, increasing the difficulty of cracking, marking the number of the encryption codes as N, randomly selecting N image blocks from the image blocks, randomly distributing the obtained encryption codes into the N image blocks according to the sequence to prevent confusion, avoiding data loss caused by wrong sequence during decryption, marking the unselected image blocks in the high-definition picture as confusion blocks, marking the number of the confusion blocks as Z, randomly selecting Z codes from a code table, randomly distributing the selected Z codes into the confusion blocks, and further reducing the possibility of the codes being cracked, if only encryption coding is carried out, correct data can be listed from the semantics of the encryption coding after other personnel obtain the coding table, and the importance of the distribution record is reflected, so that the distribution record can be encrypted to further increase the security, and other personnel are prevented from obtaining the distribution record; the distribution records are encrypted through the picture splicing unit, a plurality of pictures are stored in the picture splicing unit, one picture is picked from the plurality of pictures to be used as the picture splicing picture, the number of parts of the picture splicing picture is selected, the number of the divided parts is larger than ten, V parts of pictures are randomly selected from the divided pictures, V is a proportionality coefficient, V is a positive integer larger than nine, the correct arrangement patterns of the V parts of pictures are set and stored, the difficulty of cracking the picture splicing by other people is increased more conveniently, and the safety of the distribution records is ensured.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood 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.
As shown in fig. 1, a data compression encryption system includes a compression library, an encryption module, an administrator module, a decryption module, a server and a storage module;
the compression library is used for establishing a data compression corresponding library, acquiring data to be compressed, establishing a data segmentation model, inputting the data to be compressed and preset segmentation conditions into the data segmentation model to obtain a plurality of data segments, inputting the data segments into the coding model to obtain corresponding data segment codes, arranging the data segment codes according to the compressed data before data segmentation, and deleting the segmented data; therefore, the data which needs to be compressed originally is converted into data segment codes, the memory occupied by the data is greatly reduced, and meanwhile, the data is encrypted;
further, the method for establishing the data segmentation model comprises the following steps: acquiring a plurality of groups of historical compressed data, wherein the historical compressed data is data which needs to be compressed by a user once, setting a preset segmentation condition, wherein the preset segmentation condition is used for providing a segmentation basis for data segmentation, for example, a statement is set as the preset segmentation condition, the compressed data is 'good of little buddies', an example of data splitting is shared by people today 'and people' and 'good' of little buddies ', the' today 'and people' share 'and' one 'of data splitting' are obtained according to the segmentation result of the statement segmentation, constructing an artificial intelligence model, wherein the artificial intelligence model comprises an error inverse propagation neural network, an RBF neural network and a deep convolution neural network, inputting the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into an artificial intelligence model for learning and training, and dividing the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set according to a set proportion, A test set and a check set; the set proportion comprises 4: 2: 1. 4: 3: 1 and 3: 2: 2; training, testing and checking the artificial intelligence model through a training set, a testing set and a checking set, and marking the trained artificial intelligence model as a data segmentation model;
further, the method for establishing the coding model comprises the following steps: acquiring a plurality of groups of historical data segments, summarizing the historical data segments, deleting repeated data segments, sequencing the deleted historical data segments according to the division time and the data size, sequencing according to the division time, sequencing according to the data size at the same division time, randomly sequencing all the same, and encoding the sequenced historical data segments, wherein the encoding labels have a rule, for example, according to 1, 2, 3, … …; or a1, a2, a3 and … … in a certain sequence, preferably, a sorting function can be used to automatically generate codes, and further confidentiality is increased; establishing a coding table, namely summarizing the coded historical data segments and the corresponding codes into the table, setting a matching unit for matching the input data segments with the coding table, inputting the input data segments into the coding table for storage when the input data segments are not successfully matched with the coding table, and generating the corresponding data segment codes according to the coding sequence; when the input data segment is successfully matched with the coding table, obtaining the corresponding data segment code;
the encryption module is used for encrypting the data segment codes to obtain a high-definition picture, or combining a plurality of data segments into a high-definition picture, obtaining the data segment codes to be compressed and encrypted from a compression library, marking the data segment codes to be compressed and encrypted as encryption codes, wherein the data segment codes are ordered data segment codes, dividing the high-definition picture into a plurality of image blocks, marking the number of the image blocks to be more than the number of the encryption codes, marking the number of the encryption codes as N, wherein N is a positive integer greater than zero, randomly selecting N image blocks from the plurality of image blocks, randomly distributing the obtained encryption codes into the N image blocks according to the sequence, namely the original arrangement sequence of the encryption codes or the reverse sequence, preventing confusion, avoiding that the sequence is not right when decrypting to cause data loss, and generating distribution records, recording the distribution sequence and position of encrypted codes in the distribution record, marking unselected image blocks in the high-definition picture as obfuscated blocks, marking the number of the obfuscated blocks as Z, wherein Z is a positive integer greater than zero, randomly selecting Z codes from a code table, randomly distributing the selected Z codes into the obfuscated blocks, and marking the high-definition picture as an encrypted picture; the possibility of password cracking is further reduced, because if only encryption codes are used, correct data can be listed from the semantics of the encryption codes after other people obtain the coding tables, and the importance of the distribution records is reflected, so that the distribution records can be encrypted to further increase the security, and other people are prevented from obtaining the distribution records; setting a jigsaw unit, wherein the jigsaw unit is used for encrypting the distribution record, a plurality of pictures are stored in the jigsaw unit, one picture is selected from the plurality of pictures to be a jigsaw picture, the number of parts of the jigsaw picture is selected, the number of the parts of the jigsaw picture is larger than ten, V parts of pictures are randomly selected from the divided pictures, V is a proportionality coefficient, V is a positive integer larger than nine, and the correct arrangement pattern of the V parts of pictures is set and stored;
reference example: a user needs to encrypt the distribution records, opens the jigsaw unit, selects one picture from six pictures in the jigsaw unit as a jigsaw picture, selects and divides the jigsaw picture into eighteen parts, selects nine pictures from the eighteen parts, arranges the nine pictures to form a correct jigsaw pattern, and stores the picture; when the distribution records need to be decrypted, one method is to directly decrypt through administrator authentication, and the other method is to carry out jigsaw puzzle games, wherein correct pictures are selected from six pictures in a jigsaw unit, and when the correct pictures are selected, decryption fails, an alarm signal is generated, and decryption personnel are photographed and stored; when the selection is correct, selecting the number of parts of the picture to be divided, and when the number of the divided parts is not eighteen, failing to decrypt, generating an alarm signal, and photographing and storing decryption personnel; when the number of the divided parts is eighteen, selecting correct nine parts of pictures from the eighteen parts of pictures, and when the number of the divided parts is not correct, failing to decrypt, generating an alarm signal, and photographing and storing decryption personnel; when the selection is correct, nine pictures are sequenced, and when the sequencing is wrong, decryption fails, an alarm signal is generated, and decryption personnel are photographed and stored; when the sequencing is correct, the decryption is successful; preferably, in the decryption process, when the decryption is wrong, the alarm is not given out until the last picture is sequenced, so that other personnel are prevented from trying for the mistake step by step and the wrong answer is eliminated;
the administrator module is used for an administrator to log in the management system, acquiring verified face identification information and fingerprint information, matching the acquired face identification information and fingerprint information with administrator information in the storage module, logging in successfully when matching is successful, generating an alarm signal when matching is failed, and taking a picture of the verified person for storage;
the decryption module is used for decrypting the encrypted data to obtain an encrypted picture, verifying the encrypted picture in the picture splicing unit to obtain a distribution record, sequentially extracting the encrypted codes from the encrypted picture according to the distribution record, matching the encrypted codes with the code table to obtain corresponding data segments, and then successfully decrypting to obtain decrypted data.
A use method of a data compression encryption system specifically comprises the following steps:
the method comprises the following steps: the administrator logs in the management system, acquires the verified face identification information and fingerprint information, matches the acquired face identification information and fingerprint information with the administrator information in the storage module, and if the matching is successful, the login is successful, and if the matching is failed, an alarm signal is generated, and the verified person is photographed and stored;
step two: establishing a data compression corresponding library, acquiring data to be compressed, establishing a data segmentation model, inputting the data to be compressed and preset segmentation conditions into the data segmentation model to obtain a plurality of data segments, inputting the data segments into a coding model to obtain corresponding data segment codes, arranging the data segment codes according to the compressed data before data segmentation, and deleting the segmented data;
the method for establishing the data segmentation model comprises the following steps: acquiring a plurality of groups of historical compressed data, setting preset segmentation conditions, constructing an artificial intelligence model, wherein the artificial intelligence model comprises an error reverse propagation neural network, an RBF neural network and a deep convolution neural network, inputting the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning training, and dividing the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a check set according to a set proportion; the set proportion comprises 4: 2: 1. 4: 3: 1 and 3: 2: 2; training, testing and checking the artificial intelligence model through a training set, a testing set and a checking set, and marking the trained artificial intelligence model as a data segmentation model;
the method for establishing the coding model comprises the following steps: acquiring a plurality of groups of historical data segments, summarizing the historical data segments, deleting the repeated data segments, sorting the deleted historical data segments according to the segmentation time and the data size, encoding the sorted historical data segments, establishing an encoding table, setting a matching unit for matching the input data segments with the encoding table, inputting the input data segments into the encoding table for storage when the input data segments are not successfully matched with the encoding table, and generating corresponding data segment codes according to the encoding sequence; when the input data segment is successfully matched with the coding table, obtaining the corresponding data segment code;
step three: encrypting a data segment code, obtaining a high-definition picture, obtaining the data segment code needing to be compressed and encrypted from a compression library, marking the data segment code needing to be compressed and encrypted as an encrypted code, dividing the high-definition picture into a plurality of image blocks, marking the number of the image blocks as N, randomly selecting N image blocks from the plurality of image blocks, randomly distributing the obtained encrypted codes into the N image blocks according to the sequence, generating a distribution record, marking the unselected image blocks in the high-definition picture as confusion blocks, marking the number of the confusion blocks as Z, randomly selecting Z codes from a code table, randomly distributing the selected Z codes into the confusion blocks, and marking the high-definition picture as the encrypted picture;
step four: encrypting the distribution record, selecting one picture from a plurality of pictures as a jigsaw picture, selecting the number of parts for dividing the jigsaw picture, randomly selecting V parts of pictures from the divided pictures, setting the correct arrangement pattern of the V parts of pictures, and storing;
step five: decrypting the encrypted data to obtain an encrypted picture, performing puzzle verification to obtain a distribution record, sequentially extracting encrypted codes from the encrypted picture according to the distribution record, matching the encrypted codes with a code table to obtain corresponding data segments, and then successfully decrypting to obtain decrypted data.
When the system is used, an administrator logs in the management system to obtain verified face identification information and fingerprint information, the obtained face identification information and fingerprint information are matched with administrator information in the storage module, when the matching is successful, the login is successful, and when the matching is failed, an alarm signal is generated to photograph and store the verified person; establishing a data compression corresponding library, acquiring data to be compressed, establishing a data segmentation model, inputting the data to be compressed and preset segmentation conditions into the data segmentation model to obtain a plurality of data segments, inputting the data segments into a coding model to obtain corresponding data segment codes, arranging the data segment codes according to the compressed data before data segmentation, and deleting the segmented data; the method for establishing the data segmentation model comprises the following steps: acquiring a plurality of groups of historical compressed data, setting preset segmentation conditions, constructing an artificial intelligence model, inputting the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning and training, and dividing the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a check set according to a set proportion; training, testing and checking the artificial intelligence model through a training set, a testing set and a checking set, and marking the trained artificial intelligence model as a data segmentation model;
the method for establishing the coding model comprises the following steps: acquiring a plurality of groups of historical data segments, summarizing the historical data segments, deleting the repeated data segments, sorting the deleted historical data segments according to the segmentation time and the data size, encoding the sorted historical data segments, establishing an encoding table, setting a matching unit for matching the input data segments with the encoding table, inputting the input data segments into the encoding table for storage when the input data segments are not successfully matched with the encoding table, and generating corresponding data segment codes according to the encoding sequence; when the input data segment is successfully matched with the coding table, obtaining the corresponding data segment code;
encrypting a data segment code, obtaining a high-definition picture, obtaining the data segment code needing to be compressed and encrypted from a compression library, marking the data segment code needing to be compressed and encrypted as an encrypted code, dividing the high-definition picture into a plurality of image blocks, marking the number of the image blocks as N, randomly selecting N image blocks from the plurality of image blocks, randomly distributing the obtained encrypted codes into the N image blocks according to the sequence, generating a distribution record, marking the unselected image blocks in the high-definition picture as confusion blocks, marking the number of the confusion blocks as Z, randomly selecting Z codes from a code table, randomly distributing the selected Z codes into the confusion blocks, and marking the high-definition picture as the encrypted picture; encrypting the distribution record, selecting one picture from a plurality of pictures as a jigsaw picture, selecting the number of parts for dividing the jigsaw picture, randomly selecting V parts of pictures from the divided pictures, setting the correct arrangement pattern of the V parts of pictures, and storing; decrypting the encrypted data to obtain an encrypted picture, performing puzzle verification to obtain a distribution record, sequentially extracting encrypted codes from the encrypted picture according to the distribution record, matching the encrypted codes with a code table to obtain corresponding data segments, and then successfully decrypting to obtain decrypted data.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (6)
1. A data compression encryption system is characterized by comprising a compression library, an encryption module, an administrator module, a decryption module, a server and a storage module; the compression library is used for establishing a data compression corresponding library, acquiring data to be compressed, establishing a data segmentation model, inputting the data to be compressed and preset segmentation conditions into the data segmentation model to obtain a plurality of data segments, inputting the data segments into a coding model to obtain corresponding data segment codes, arranging the data segment codes according to the compressed data before data segmentation, and deleting the segmented data;
the encryption module is used for encrypting the data segment codes to obtain a high-definition picture, the data segment codes needing to be compressed and encrypted are obtained from a compression library, the data segment codes needing to be compressed and encrypted are marked as encryption codes, the high-definition picture is divided into a plurality of image blocks, the number of the image blocks is more than that of the encryption codes, the number of the encryption codes is marked as N, N image blocks are randomly selected from the image blocks, the obtained encryption codes are randomly distributed into the N image blocks according to the sequence, a distribution record is generated, the unselected image blocks in the high-definition picture are marked as confusion blocks, the number of the confusion blocks is marked as Z, Z codes are randomly selected from a code table, the selected Z codes are randomly distributed into the confusion blocks, and the high-definition picture is marked as the encryption picture.
2. The data compression encryption system of claim 1, wherein the data segmentation model is established by a method comprising: acquiring a plurality of groups of historical compressed data, setting preset segmentation conditions, constructing an artificial intelligence model, inputting the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning and training, and dividing the plurality of groups of historical compressed data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a check set according to a set proportion; training, testing and checking the artificial intelligence model through the training set, the testing set and the checking set, and marking the trained artificial intelligence model as a data segmentation model.
3. The data compression encryption system of claim 1, wherein the coding model is established by a method comprising: acquiring a plurality of groups of historical data segments, summarizing the historical data segments, deleting the repeated data segments, sorting the deleted historical data segments according to the segmentation time and the data size, encoding the sorted historical data segments, establishing an encoding table, setting a matching unit for matching the input data segments with the encoding table, inputting the input data segments into the encoding table for storage when the input data segments are not successfully matched with the encoding table, and generating corresponding data segment codes according to the encoding sequence; and when the input data segment is successfully matched with the coding table, obtaining the corresponding data segment code.
4. The data compression and encryption system as claimed in claim 1, wherein the encryption module comprises a picture splicing unit, the picture splicing unit is used for encrypting the distribution record, a plurality of pictures are stored in the picture splicing unit, one picture is selected from the plurality of pictures to be the picture splicing picture, the number of the split picture splicing picture is selected, V parts of the picture are randomly selected from the split pictures, and the V parts of the picture are arranged in a correct arrangement pattern and stored.
5. The data compression and encryption system as claimed in claim 1, wherein the administrator module is used for an administrator to log in the management system, obtain the verified face identification information and fingerprint information, match the obtained face identification information and fingerprint information with the administrator information in the storage module, when the matching is successful, the login is successful, and when the matching is failed, an alarm signal is generated to take a picture of the verified person for storage.
6. The system according to claim 1, wherein the decryption module is configured to decrypt encrypted data to obtain an encrypted picture, perform verification in the puzzle unit to obtain a distribution record, sequentially extract encrypted codes from the encrypted picture according to the distribution record, match the encrypted codes with the code table to obtain corresponding data segments, and then perform decryption successfully to obtain decrypted data.
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| CN114221792B (en) * | 2021-11-23 | 2023-06-16 | 杭州天宽科技有限公司 | Internet data transmission encryption system |
| CN114629701B (en) * | 2022-03-11 | 2023-04-18 | 娄底职业技术学院 | Information display system based on information encryption |
| CN114640523B (en) * | 2022-03-18 | 2023-01-20 | 深圳小鹅网络技术有限公司 | Computer data security encryption method and system |
| CN115330446A (en) * | 2022-08-11 | 2022-11-11 | 武汉耳东信息科技有限公司 | Data center data management method and system based on artificial intelligence |
| CN116707863B (en) * | 2023-05-05 | 2024-02-13 | 广州劲源科技发展股份有限公司 | High-capacity data transmission management and control system |
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