CN116149546A - Data security storage method based on big data platform - Google Patents
Data security storage method based on big data platform Download PDFInfo
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- CN116149546A CN116149546A CN202211608504.2A CN202211608504A CN116149546A CN 116149546 A CN116149546 A CN 116149546A CN 202211608504 A CN202211608504 A CN 202211608504A CN 116149546 A CN116149546 A CN 116149546A
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- 238000013507 mapping Methods 0.000 claims abstract description 21
- 230000011218 segmentation Effects 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 12
- 125000006850 spacer group Chemical group 0.000 claims description 12
- 238000005192 partition Methods 0.000 claims description 6
- 238000012217 deletion Methods 0.000 claims description 3
- 230000037430 deletion Effects 0.000 claims description 3
- 238000000926 separation method Methods 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 3
- 230000005856 abnormality Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000036651 mood Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0602—Interfaces specially adapted for storage systems specifically adapted to achieve a particular effect
- G06F3/062—Securing storage systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
- G06F3/0638—Organizing or formatting or addressing of data
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The invention discloses a data safety storage method based on a big data platform, which relates to the technical field of data safety storage and comprises the steps of acquiring all target data; acquiring file attributes of target data, establishing pseudo target data, filling the pseudo target data with contents, automatically matching related contents according to the title of the target data and the attributes of specific contents, and filling the contents into the pseudo target data; and then adding the unique numerical value into the pseudo-target data, re-segmenting the pseudo-target data, keeping the unique numerical value consistent with paragraph characteristics in the corresponding pseudo-target data, establishing a mapping data relation between the unique numerical value and target characters in the dark file address, and endowing redundant paragraph contents in the pseudo-target data with a discarding identifier to obtain updated pseudo-target data, mapping data relation and discarding identifier.
Description
Technical Field
The invention belongs to the technical field of data security storage, and particularly relates to a data security storage method based on a big data platform.
Background
Patent number CN107122685a discloses a big data secure storage method, comprising: monitoring a preset monitoring index representing storage safety of a storage device, wherein the preset monitoring index comprises: a working environment index; and in response to monitoring that the index value of the working environment index of the storage device is abnormal, adjusting the storage mode of the stored data according to a preset processing strategy corresponding to the working environment index with the abnormal index value. The invention also provides a big data safety storage device. According to the big data safe storage method and the big data safe storage device, the working environment where the storage device is located is detected through the sensor, and corresponding processing is carried out when the working environment is abnormal, so that damage to stored data caused by environment abnormality is avoided, and safe storage of the big data is realized.
However, for this patent, there is a lack of confusing content for the storage of target data to target the problem of loss caused by the fact that the data content after the environment is hacked and accessed is peeped by others, based on which a solution is provided.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art; therefore, the invention provides a data security storage method based on a big data platform.
To achieve the above object, an embodiment according to a first aspect of the present invention provides a data security storage method based on a big data platform, the method specifically including the following steps:
step one: all data to be stored are obtained and marked as target data;
step two: acquiring file attributes of target data, establishing pseudo target data, keeping the attributes and titles of the pseudo target data consistent, then filling the contents of the pseudo target data, automatically matching related contents according to the attributes of the titles and specific contents of the target data, and filling the contents into the pseudo target data;
step three: adding the unique numerical value into the pseudo-target data, re-segmenting the pseudo-target data, establishing a mapping data relation between the unique numerical value and a target character in the dark file address after keeping consistency between the unique numerical value and paragraph characteristics in the corresponding pseudo-target data, and endowing redundant paragraph contents in the pseudo-target data with a discarding identifier to obtain updated pseudo-target data, mapping data relation and discarding identifier;
step four: the address of the pseudo target data is marked as a file plaintext address, then the mapping data relationship and the abandoned mark are stored in a key disc, and the key disc is a mobile hard disc and is carried by a corresponding authorized user.
Further, the specific way of filling the content in the second step is as follows:
s1: acquiring a title of target data, performing word segmentation processing on the title to obtain a plurality of word segments, removing common words, and marking the rest word segments as keywords;
s2: obtaining all contents in target data, performing word segmentation processing on all contents, dividing the target data into a plurality of word segments, and removing the residual word segments after the common words are marked as single word segments;
s3: classifying all the single word segments, dividing the same word segments into single word segments, counting the occurrence frequency of each single word segment, and marking the single word segment as a single occurrence frequency;
s4: then obtaining the highest numerical value of a single outlet, marking the numerical value as an upper limit number, and marking the numerical value obtained by multiplying the upper limit number by X1 as a quasi-linear number;
s5: marking corresponding single word segments in single output times which are greater than or equal to the quasi line times as target word segments, and marking single word segments consistent with the keywords as target word segments; obtaining all target word segmentation;
s6: dividing target data according to a spacer, dividing the target into a plurality of spacer segments, wherein the spacer is a preset separation symbol;
s7: marking more than two target segmentation words in the interval section as key interval sections, and marking the rest as conventional interval sections;
s8: copying all contents in the target data to one copy, and marking the copied contents as contents to be filled;
s9: deleting key partitions in the content to be filled, keeping the sequence unchanged after the deletion is completed, and reserving conventional partitions;
s10: acquiring a title of target data, searching data with highest similarity with the title from a published file, marking the data as replacement data, searching a content segment with the same sequence number as a key interval in the content to be filled from the replacement data, filling the content segment in the deleted key interval in sequence to form new content to be filled, and marking the new content to be filled as pseudo target data;
here, the content segments in the replacement data are also divided according to the spacers, and are divided into a plurality of content segments, and a number is given from the first to the last, wherein the number is the sequence;
s11: and obtaining the pseudo target data.
Further, the general words in step S1 are general words preset by the administrator.
Further, in step S4, X1 is a preset value, and certainly the quasi-line number cannot be less than or equal to 2, and if the quasi-line number is less than or equal to 2, it is automatically marked as 3.
Further, the specific way of adding the dark file address to the pseudo target data in the third step is as follows:
SS1: constructing a dark file address, wherein the target data content of the dark file address can be accessed and checked only through the dark file address;
SS2: dividing the address of the dark file into characters, marking each character as a target character, and marking the number of the character as the address number;
SS3: then, each target character is assigned a unique numerical value which is randomly assigned and mutually different, and the unique numerical value is ensured to be more than 50; after each target character is assigned with a unique numerical value, a mapping data relationship is constructed;
SS4: then, a first target character is obtained, pseudo target data is synchronously obtained, first paragraph division is carried out on pseudo target data content, the first paragraph ensures that the number of other characters except punctuation marks and spaces is consistent with the unique numerical value of the corresponding first target character, and if the first paragraph does not have punctuation marks at last, a sentence is automatically added for the first paragraph;
SS5: then, a second target character is obtained, and the pseudo target data is processed in the same way of the step SS4 to obtain a second paragraph;
SS6: sequentially obtaining the next target character, carrying out the same processing in the step SS5 to obtain corresponding target character paragraphs, placing the rest content in the same paragraph, and marking a abandoned mark at the initial position of the paragraph, wherein the abandoned mark is preset by a manager;
SS7: and obtaining the updated pseudo target data, the mapping data relationship and the discarding identifier.
Further, when a user needs to access the target file, the user must access the pseudo target data through the plaintext address, then find the address of the dark file through the mapping data relationship in the key disc, and can open the corresponding target data to access through the address of the dark file, and all other access modes are refused.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, all target data are obtained; acquiring file attributes of target data, establishing pseudo target data, filling the pseudo target data with contents, automatically matching related contents according to the title of the target data and the attributes of specific contents, and filling the contents into the pseudo target data; then adding the unique numerical value into the pseudo-target data, re-segmenting the pseudo-target data, keeping the unique numerical value consistent with paragraph characteristics in the corresponding pseudo-target data, establishing a mapping data relation between the unique numerical value and target characters in the dark file address, and endowing redundant paragraph contents in the pseudo-target data with a discarding identifier to obtain updated pseudo-target data, mapping data relation and discarding identifier;
the false target data can be decoded by a user entering the access environment, the false target data is accessed, and the false target data has similar attributes to the normal target data, so that the false target data is prevented from being easily recognized and the correct content is continuously tracked.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The application provides a data security storage method based on a big data platform, which specifically comprises the following steps:
step one: all data to be stored are obtained and marked as target data;
step two: the file attribute of the target data is acquired, the pseudo target data is established, the pseudo target data keeps the attribute and the title consistent, then the pseudo target data is filled with contents, and the specific mode of the contents is as follows:
s1: acquiring a title of target data, performing word segmentation processing on the title to obtain a plurality of word segments, removing common words, and marking the rest word segments as keywords; the general words are common words such as a mood word, a fluxing word and the like, such as words like 'your', 'ground' and the like, and are preset by an administrator; the word segmentation process adopts the prior art, and detailed description is not provided here;
s2: obtaining all contents in target data, performing word segmentation processing on all contents, dividing the target data into a plurality of word segments, and removing the residual word segments after the common words are marked as single word segments;
s3: classifying all the single word segments, dividing the same word segments into single word segments, counting the occurrence frequency of each single word segment, and marking the single word segment as a single occurrence frequency;
s4: then obtaining the highest numerical value of a single output time, marking the numerical value as an upper limit time, marking the numerical value obtained by multiplying the upper limit time by X1 as a quasi-linear time, wherein X1 is a preset numerical value, the value is usually 0.5, of course, the quasi-linear time cannot be less than or equal to 2, and if the quasi-linear time is less than or equal to 2, automatically marking the quasi-linear time as 3;
s5: marking corresponding single word segments in single output times which are greater than or equal to the quasi line times as target word segments, and marking single word segments consistent with the keywords as target word segments; obtaining all target word segmentation;
s6: dividing the target data according to a spacer, dividing the target into a plurality of spacer segments, wherein the spacer is a preset separation symbol such as punctuation mark;
s7: marking more than two target segmentation words in the interval section as key interval sections, and marking the rest as conventional interval sections;
s8: copying all contents in the target data to one copy, and marking the copied contents as contents to be filled;
s9: deleting key partitions in the content to be filled, keeping the sequence unchanged after the deletion is completed, and reserving conventional partitions;
s10: acquiring a title of target data, searching data with highest similarity with the title from a published file, marking the data as replacement data, searching a content segment with the same sequence number as a key interval in the content to be filled from the replacement data, filling the content segment in the deleted key interval in sequence to form new content to be filled, and marking the new content to be filled as pseudo target data;
here, the content segments in the replacement data are also divided according to the spacers, and are divided into a plurality of content segments, and a number is given from the first to the last, wherein the number is the sequence;
s11: obtaining pseudo target data;
step three: adding the dark file address into the pseudo target data, wherein the specific adding mode is as follows:
SS1: constructing a dark file address, wherein the target data content of the dark file address can be accessed and checked only through the dark file address;
SS2: dividing the address of the dark file into characters, marking each character as a target character, and marking the number of the character as the address number;
SS3: then, each target character is assigned a unique numerical value which is randomly assigned and mutually different, and the unique numerical value is ensured to be more than 50; for example, if any target character is h, a number 65 is allocated for the time, a mapping relationship is formed between the number 65 and the target character, and after each target character is allocated with a unique value, a mapping data relationship is formed;
SS4: then, a first target character is obtained, pseudo target data is synchronously obtained, first paragraph division is carried out on pseudo target data content, the first paragraph ensures that the number of other characters except punctuation marks and spaces is consistent with the unique numerical value of the corresponding first target character, and if the first paragraph does not have punctuation marks at last, a sentence is automatically added for the first paragraph;
SS5: then, a second target character is obtained, and the pseudo target data is processed in the same way of the step SS4 to obtain a second paragraph;
SS6: sequentially obtaining the next target character, carrying out the same processing in the step SS5 to obtain corresponding target character paragraphs, placing the rest content in the same paragraph, and marking a abandoned mark at the initial position of the paragraph, wherein the abandoned mark is preset by a manager;
SS7: obtaining updated pseudo target data, mapping data relation and abandoned identifiers;
step four: the address of the pseudo target data is marked as a file plaintext address, then the mapping data relationship and the abandoned mark are stored in a key disc, and the key disc is a mobile hard disc and is carried by a corresponding authorized user;
step five: when the user accesses the pseudo target data through the plaintext address, then the user finds the dark file address through the key disc and the mapping data relationship in the key disc, and the user can open the corresponding target data to access through the dark file address, and all other access modes are refused.
As a second embodiment of the present invention, the difference between the remaining embodiments is that the manner of content filling of the pseudo target data in the second step is different, specifically:
s1: acquiring a title of target data, searching data of which the similarity ranks are first and second from a published file, and marking the data as replacement data;
s2: acquiring a first section of content of target data, and selecting a section of replacement with the closest character number from the two pieces of replacement data;
s3: then selecting a second section of content of the target data, and performing the same processing in a mode of step S2, wherein the selected section of content is not selected;
s4: and completing replacement of each piece of content of the target data in turn.
As an embodiment three of the present invention, it is specifically that the first embodiment and the second embodiment are implemented in a combined manner, the method in the first embodiment and the method in the second embodiment are randomly selected, specifically, the file size of the target data is selected, if the number of bits in the file size is odd, the implementation of the first embodiment is selected, otherwise, the implementation of the second embodiment is selected.
The partial data in the formula are all obtained by removing dimension and taking the numerical value for calculation, and the formula is a formula closest to the real situation obtained by simulating a large amount of collected data through software; the preset parameters and the preset threshold values in the formula are set by those skilled in the art according to actual conditions or are obtained through mass data simulation.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (6)
1. The data security storage method based on the big data platform is characterized by comprising the following steps:
step one: all data to be stored are obtained and marked as target data;
step two: acquiring file attributes of target data, establishing pseudo target data, keeping the attributes and titles of the pseudo target data consistent, then filling the contents of the pseudo target data, automatically matching related contents according to the attributes of the titles and specific contents of the target data, and filling the contents into the pseudo target data;
step three: adding the unique numerical value into the pseudo-target data, re-segmenting the pseudo-target data, establishing a mapping data relation between the unique numerical value and a target character in the dark file address after keeping consistency between the unique numerical value and paragraph characteristics in the corresponding pseudo-target data, and endowing redundant paragraph contents in the pseudo-target data with a discarding identifier to obtain updated pseudo-target data, mapping data relation and discarding identifier;
step four: the address of the pseudo target data is marked as a file plaintext address, then the mapping data relationship and the abandoned mark are stored in a key disc, and the key disc is a mobile hard disc and is carried by a corresponding authorized user.
2. The data security storage method based on big data platform as claimed in claim 1, wherein the content filling in the second step is specifically:
s1: acquiring a title of target data, performing word segmentation processing on the title to obtain a plurality of word segments, removing common words, and marking the rest word segments as keywords;
s2: obtaining all contents in target data, performing word segmentation processing on all contents, dividing the target data into a plurality of word segments, and removing the residual word segments after the common words are marked as single word segments;
s3: classifying all the single word segments, dividing the same word segments into single word segments, counting the occurrence frequency of each single word segment, and marking the single word segment as a single occurrence frequency;
s4: then obtaining the highest numerical value of a single outlet, marking the numerical value as an upper limit number, and marking the numerical value obtained by multiplying the upper limit number by X1 as a quasi-linear number;
s5: marking corresponding single word segments in single output times which are greater than or equal to the quasi line times as target word segments, and marking single word segments consistent with the keywords as target word segments; obtaining all target word segmentation;
s6: dividing target data according to a spacer, dividing the target into a plurality of spacer segments, wherein the spacer is a preset separation symbol;
s7: marking more than two target segmentation words in the interval section as key interval sections, and marking the rest as conventional interval sections;
s8: copying all contents in the target data to one copy, and marking the copied contents as contents to be filled;
s9: deleting key partitions in the content to be filled, keeping the sequence unchanged after the deletion is completed, and reserving conventional partitions;
s10: acquiring a title of target data, searching data with highest similarity with the title from a published file, marking the data as replacement data, searching a content segment with the same sequence number as a key interval in the content to be filled from the replacement data, filling the content segment in the deleted key interval in sequence to form new content to be filled, and marking the new content to be filled as pseudo target data;
here, the content segments in the replacement data are also divided according to the spacers, and are divided into a plurality of content segments, and a number is given from the first to the last, wherein the number is the sequence;
s11: and obtaining the pseudo target data.
3. The method for securely storing data based on a big data platform according to claim 1, wherein the general words in step S1 are general words preset by an administrator.
4. The method of claim 1, wherein in the step S4, X1 is a preset value, and certainly the quasi-linear number cannot be equal to or less than 2, and if the quasi-linear number is equal to or less than 2, it is automatically marked as 3.
5. The method for securely storing data based on a big data platform according to claim 1, wherein the specific way of adding the address of the dark file to the pseudo target data in the third step is as follows:
SS1: constructing a dark file address, wherein the target data content of the dark file address can be accessed and checked only through the dark file address;
SS2: dividing the address of the dark file into characters, marking each character as a target character, and marking the number of the character as the address number;
SS3: then, each target character is assigned a unique numerical value which is randomly assigned and mutually different, and the unique numerical value is ensured to be more than 50; after each target character is assigned with a unique numerical value, a mapping data relationship is constructed;
SS4: then, a first target character is obtained, pseudo target data is synchronously obtained, first paragraph division is carried out on pseudo target data content, the first paragraph ensures that the number of other characters except punctuation marks and spaces is consistent with the unique numerical value of the corresponding first target character, and if the first paragraph does not have punctuation marks at last, a sentence is automatically added for the first paragraph;
SS5: then, a second target character is obtained, and the pseudo target data is processed in the same way of the step SS4 to obtain a second paragraph;
SS6: sequentially obtaining the next target character, carrying out the same processing in the step SS5 to obtain corresponding target character paragraphs, placing the rest content in the same paragraph, and marking a abandoned mark at the initial position of the paragraph, wherein the abandoned mark is preset by a manager;
SS7: and obtaining the updated pseudo target data, the mapping data relationship and the discarding identifier.
6. The data security storage method based on big data platform according to claim 1, wherein when a user needs to access the target file, the user must access the pseudo target data through a plaintext address, then find a dark file address through a mapping data relationship in the key disc, and open the corresponding target data through the dark file address to access, and all other access modes are refused.
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