CN104794406A - Private data protecting method based on data camouflage model - Google Patents
Private data protecting method based on data camouflage model Download PDFInfo
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- CN104794406A CN104794406A CN201510119589.1A CN201510119589A CN104794406A CN 104794406 A CN104794406 A CN 104794406A CN 201510119589 A CN201510119589 A CN 201510119589A CN 104794406 A CN104794406 A CN 104794406A
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- private data
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Abstract
The invention discloses a private data protecting method based on a data camouflage model. Firstly, features, which comprise file headers, file creators, file sizes, file formats, file types, creation date, last modified date and statistical information, of a data storage environment are analyzed; the information is extracted to serve as the features of the data storage environment, and different weights are endowed. The features are arranged in descending order according to the significance of the features, and the maximal first N features are selected to serve as the features of the data storage environment. The distance between private data and feature vectors of the data storage environment is calculated, the mapping between the N environmental features with the minimal distance and the private data features is established, and the mapping is stored into a mapping database; the user private data are converted into data expressed by environmental features according to the mapping. When a user needs to access the data, the data are recovered by mapping tables in the mapping database. The method is easy to achieve and to popularize.
Description
Technical field
The present invention proposes a kind of private data guard method based on data camouflage color model, the method relates to the fields such as internet data safety, image watermarking, large data security storage.
Background technology
Along with the development of internet and cloud computing technology, together with personal lifestyle is closely connected with various social networks, the information be closely related with personal identification and many spreading on internet of data grows.The private data of these magnanimity is for some enterprises or institutionally have very great value, and such as they are by excavating and analyze classifying to crowd of these data, obtain huge interests by precision marketing.The privacy of people has seriously been invaded when knowing nothing.How effectively the individual private data of protection becomes the problem that people are concerned about most.
In reality, soldier can by camouflage oneself being hidden in [1] in physical environment, ultimate principle becomes irregular part significant pattern or characteristic change exactly, use some combined materials, painted or illumination to be hidden in similar background, make them be difficult to be found.Gain enlightenment thus, we have proposed a kind of private data guard method based on data camouflage color model, the method carrys out hiding data by setting up a mode being similar to military camouflage painting the same, realizes the safe storage of individual private data.This method can improve the safety of individual private information significantly, eliminates people to the misgivings of social networks simultaneously.
Summary of the invention
The object of this invention is to provide a kind of private data guard method based on data camouflage color model; the method carrys out hiding data by setting up a mode being similar to military camouflage painting the same; realize the safe storage of individual private data, eliminate people simultaneously and using internet and the worry to individual private information security when interaction on social networks.
For achieving the above object, technical scheme of the present invention is:
The present invention proposes a kind of private data guard method based on data camouflage color model, the method analyzes the feature of user's private data, and adopts a maximum M feature to represent data.When user needs to store private data, first the feature of data storage environment is analyzed, comprise file title, document creation people, file size, file layout, file type, date created, finally revises the statistical information of date and data itself, extract the feature of these information as storage environment, and give different weights; Then carry out descending sort according to value, select wherein maximum top n feature as the feature of data storage environment.Calculate the distance between private data and the proper vector of storage environment, set up apart from the mapping between minimum N number of environmental characteristic and private data feature, and be deposited in mapping database; According to mapping data user's private data being converted to environmental characteristic and represent.When user needs to access these data time, recover raw data by the mapping table in mapping database.
Individual private data of the present invention is changed and is hidden schematic flow sheet as shown in Figure 1;
In the present invention, individual private data is changed and hides process flow diagram as shown in Figure 2, and its concrete steps are as follows:
1) individual private data feature interpretation
The present invention comprises title, author by extraction data, and some statistical informations of data itself are as the feature of data, and these features are defined as F
p={ F
p1, F
p2, F
p3... F
pm, wherein, m is characteristic dimension; Consider that the significance level of different characteristic is different, each feature is endowed different weights:
and adopt the M of a maximum weight feature to represent data;
2) storage environment feature is extracted
The present invention analyzes the feature of data storage environment, comprises file title, document creation people, file size, file layout, file type, date created, finally revise the statistical information of date and data itself, extract the feature of these information as storage environment, the feature of environmental characteristic is defined as F
e={ F
e1, F
e2, F
e3... F
en, the wherein characteristic dimension of n, and n is much larger than m.Consider that the significance degree of different characteristic is different, each feature is endowed different weights:
then carry out descending sort according to the conspicuousness of these features, the top n feature selecting wherein conspicuousness maximum is as the feature of data storage environment;
3) individual private data conversion is with hiding
The characterization of the individual private data that the present invention obtains according to step 1 and 2 represents and to represent with the characterization of data storage environment, calculates the distance between private data and the proper vector of storage environment, for every a pair (F
e, F
p), calculate their distance, (F
e, F
p) as follows apart from computing formula:
Dis(F
e，F
p)＝||αF
e-αF
p||
By the distance of gained according to according to ascending order arrangement, selected distance minimum a pair as the distance of individual private data feature and storage environment feature, and sets up mapping ruler [F
e→ F
p], finally set up apart from the mapping between minimum N number of environmental characteristic and private data feature, and be deposited in mapping rules database; Then according to mapping data user's private data being converted to environmental characteristic and represent;
4) individual private data recovers
When user needs to access these data time, according to the environmental characteristic representing these data, extract original data characteristics from mapping rules database, by original data characteristics table registration certificate, thus recover data, and return to user.
The invention has the beneficial effects as follows, environmentally automatically can complete hiding individual private data, have good adaptive faculty to different data environments.The present invention utilizes data camouflage to hide data, add the difficulty that individual private data is excavated by unauthorized organizations and individuals and finds, significantly can improve the security of individual private data, eliminate the worry to safety problem when people use public network simultaneously, and the present invention easily realizes, be easy to promote.
Accompanying drawing explanation
Fig. 1 is the present invention individual private data conversion and hides schematic flow sheet schematic diagram.
Fig. 2 is that in the present invention, individual private data is changed and hides process flow diagram.
Embodiment
Below in conjunction with specific embodiment, the present invention is illustrated further.
Based on a private data guard method for data camouflage color model, the present invention is characterised in that: analyze user's private data and adopt a maximum M feature to represent data; Wherein, when user needs to store private data, first analyze the feature of data storage environment, comprise file title, document creation people, file size, file layout, file type, date created, finally revise the statistical information of date and data itself, extract the feature of these information as storage environment, and give different weights; Then carry out descending sort according to the conspicuousness of these features, select wherein maximum top n feature as the feature of data storage environment; Calculate the distance between private data and the proper vector of storage environment, set up apart from the mapping between minimum N number of environmental characteristic and private data feature, and be deposited in mapping rules database; User's private data converted to according to mapping ruler the data that environmental characteristic represents; When user needs to access these data time, recover raw data by the mapping table in mapping rules database.
1) individual private data feature interpretation
The present invention comprises title, author by extraction data, and some statistical informations of data itself are as the feature of data, and these features are defined as F
p={ F
p1, F
p2, F
p3... F
pm, wherein, m is characteristic dimension; Consider that the significance level of different characteristic is different, each feature is endowed different weights:
and adopt the M of a maximum weight feature to represent data;
2) storage environment feature is extracted
The present invention analyzes the feature of data storage environment, comprises file title, document creation people, file size, file layout, file type, date created, finally revise the statistical information of date and data itself, extract the feature of these information as storage environment, the feature of environmental characteristic is defined as F
e={ F
e1, F
e2, F
e3... F
en, the wherein characteristic dimension of n, and n is much larger than m.Consider that the significance degree of different characteristic is different, each feature is endowed different weights:
then carry out descending sort according to the conspicuousness of these features, the top n feature selecting wherein conspicuousness maximum is as the feature of data storage environment;
3) individual private data conversion is with hiding
The characterization of the individual private data that the present invention obtains according to step 1 and 2 represents and to represent with the characterization of data storage environment, calculates the distance between private data and the proper vector of storage environment, for every a pair (F
e, F
p), calculate their distance, (F
e, F
p) as follows apart from computing formula:
Dis(F
e，F
p)＝||αF
e-αF
p||
By the distance of gained according to according to ascending order arrangement, selected distance minimum a pair as the distance of individual private data feature and storage environment feature, and sets up mapping ruler [F
e→ F
p], finally set up apart from the mapping between minimum N number of environmental characteristic and private data feature, and be deposited in mapping rules database; Then according to mapping data user's private data being converted to environmental characteristic and represent;
4) individual private data recovers
When user needs to access these data time, according to the environmental characteristic representing these data, extract original data characteristics from mapping rules database, by original data characteristics table registration certificate, thus recover data, and return to user.
Claims (2)
1. based on a private data guard method for data camouflage color model, it is characterized in that: analyze user's private data and adopt a maximum M feature to represent data; Wherein, when user needs to store private data, first analyze the feature of data storage environment, comprise file title, document creation people, file size, file layout, file type, date created, finally revise the statistical information of date and data itself, extract the feature of these information as storage environment, and give different weights; Then carry out descending sort according to the conspicuousness of these features, select wherein maximum top n feature as the feature of data storage environment; Calculate the distance between private data and the proper vector of storage environment, set up apart from the mapping between minimum N number of environmental characteristic and private data feature, and be deposited in mapping rules database; User's private data converted to according to mapping ruler the data that environmental characteristic represents; When user needs to access these data time, recover raw data by the mapping table in mapping rules database.
2. a kind of private data guard method based on data camouflage color model according to claim 1, is characterized in that: the step of user's private data conversion is:
1) individual private data feature interpretation
The present invention comprises title, author by extraction data, and some statistical informations of data itself are as the feature of data, and these features are defined as F
p={ F
p1, F
p2, F
p3... F
pm, wherein, m is characteristic dimension; Consider that the significance level of different characteristic is different, each feature is endowed different weights:
and adopt the M of a maximum weight feature to represent data;
2) storage environment feature is extracted
Analyze the feature of data storage environment, comprise file title, document creation people, file size, file layout, file type, date created, finally revise the statistical information of date and data itself, extract the feature of these information as storage environment, the feature of environmental characteristic is defined as F
e={ F
e1, F
e2, F
e3... F
en, the wherein characteristic dimension of n, and n is much larger than m; Consider that the significance degree of different characteristic is different, each feature is endowed different weights:
then carry out descending sort according to the conspicuousness of these features, the top n feature selecting wherein conspicuousness maximum is as the feature of data storage environment;
3) individual private data conversion is with hiding
The characterization of the individual private data obtained according to step 1 and 2 represents and to represent with the characterization of data storage environment, calculates the distance between private data and the proper vector of storage environment, for every a pair (F
e, F
p), calculate their distance, (F
e, F
p) as follows apart from computing formula:
Dis(F
e，F
p)＝||aF
e-aF
p||
By the distance of gained according to according to ascending order arrangement, selected distance minimum a pair as the distance of individual private data feature and storage environment feature, and sets up mapping ruler [F
e→ F
p], finally set up apart from the mapping between minimum N number of environmental characteristic and private data feature, and be deposited in mapping rules database; Then according to mapping data user's private data being converted to environmental characteristic and represent;
4) individual private data recovers
When user needs to access these data time, according to the environmental characteristic representing these data, extract original data characteristics from mapping rules database, by original data characteristics table registration certificate, thus recover data, and return to user.
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| CN106778295A (en) * | 2016-11-30 | 2017-05-31 | 广东欧珀移动通信有限公司 | File storage, display methods, device and terminal |
| CN108133294A (en) * | 2018-01-10 | 2018-06-08 | 阳光财产保险股份有限公司 | Forecasting Methodology and device based on information sharing |
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|---|---|---|---|---|
| CN106778295A (en) * | 2016-11-30 | 2017-05-31 | 广东欧珀移动通信有限公司 | File storage, display methods, device and terminal |
| CN106778295B (en) * | 2016-11-30 | 2020-04-10 | Oppo广东移动通信有限公司 | File storage method, file display method, file storage device, file display device and terminal |
| CN108133294A (en) * | 2018-01-10 | 2018-06-08 | 阳光财产保险股份有限公司 | Forecasting Methodology and device based on information sharing |
| WO2019137049A1 (en) * | 2018-01-10 | 2019-07-18 | 阳光财产保险股份有限公司 | Prediction method and apparatus based on information sharing, electronic device and computer storage medium |
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