CN106973044A - A kind of recognition methods for realizing data owner in big data transaction - Google Patents
A kind of recognition methods for realizing data owner in big data transaction Download PDFInfo
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- CN106973044A CN106973044A CN201710154307.0A CN201710154307A CN106973044A CN 106973044 A CN106973044 A CN 106973044A CN 201710154307 A CN201710154307 A CN 201710154307A CN 106973044 A CN106973044 A CN 106973044A
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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
- H04L63/12—Applying verification of the received information
- H04L63/126—Applying verification of the received information the source of the received data
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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
- H04L63/12—Applying verification of the received information
- H04L63/123—Applying verification of the received information received data contents, e.g. message integrity
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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
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
Abstract
The invention discloses a kind of recognition methods for realizing data owner in big data transaction; include the target data plaintext X1 in the initial data plaintext X encrypted will be needed to handle by FPE protections including data encryption step S100, obtain the target data ciphertext Y1 of same format length；Data authentication step S200 includes verifying target data plaintext X1 using HASH algorithms by algorithm management AM modules, obtains target data plaintext X1 authenticity information and target data plaintext X1 owner's information；Data decryption step S300 includes target data ciphertext Y1 obtaining target data plaintext X1 and initial data plaintext X by FPE decryption.The present invention can be encrypted protection to data by FPE encryption technologies and select AS modules to handle data according to specific encryption or decipherment algorithm by AES; and record the corresponding informance related to owner in initial data; form watermark; prevent that data from illegally being distorted, judge the authenticity and validity of data.
Description
Technical field
The present invention relates to big data discriminating conduct field, more particularly to data encryption recognition methods field, specifically, it is
A kind of recognition methods for realizing data owner in big data transaction.
Background technology
Today's society has completely passed into the information age, and by computer and internet, people can be according to big data
Analysis obtains many unknown information, for the foundation for building, opening up and developing the science of offer of every field and direction, to things
Carry out Scientific evaluation etc..Meanwhile, it is also the credit epoch now, the personal credit information of people is related to the method face face of life,
It is formal that there is very high commercial value due to the personal information under big data, while life is convenient for people to, also occur in that
Some bad social phenomenons, for example：Financial swindling, telephone fraud, personal information forgery etc..
In order to ensure the authenticity and validity of information, data can be encrypted with place generally during the circulation of data
Reason, prevent data because be tampered with, increase illegal fragment or by extracts important information after cause the distortion of data, still,
Existing encryption gimmick if it can prevent that information from not known the third party of password distorts, and can not prevent and shut out
Whether exhausted information, which is had permission the people that checks, carries out carrying out circulation again after malicious modification.In order to avoid information is in circulation process
In there arises a problem that：
A, buyer, which may change hands the data obtained from big data seller, to be sold to third party and is made a profit；
The fragment bought in data may be won out for other purposes by B, buyer；
C, buyer may forge or insert new data change hands be sold to again third party profit.
Data are effectively differentiated, know information whether by by processing and distorting meaning very great.
The current general way of industry is that a part of data are made into some slight changes, such as uses the message registration of user
The excel softwares of Microsoft make some trickle adjustment（The data for being sold to party A-subscriber are the air time to be pushed away forward 0.01 second, are sold to B
The data of user are the air time to be pushed away forward 0.02 second, so contrast the data after processing and initial data, can just judge
The owner of the data belongs to A or B）Although this method is simple, once rule is leaked out, either party may be used
To revert to initial data with opposite method, so as to change hands use or merchandise, and then it can not judge that data are A or B on earth
Leak out.
Moreover, this straightforward procedure can not solve data integrity issues at present, that is to say, that can only at most solve A class wind
Danger, it is impossible to solve B/C class risks.
The present invention solves the problem using a kind of special mechanism, and this technology can solve A/B/C class risks simultaneously.
The content of the invention
It is an object of the invention to provide a kind of recognition methods for realizing data owner in big data transaction, for solving the back of the body
The three class problems that data described in scape technology easily occur during circulation.The present invention is by data encryption-checking-solution
Close processing, can effectively judge authenticity, the integrality of data, at the same can or data original owner's information, to obtain
Know the primary source of information；It is not only able to prevent the third party without authority from carrying out malice to data message and distorting or usurp,
It can also effectively prevent the user with authority from carrying out usurping, change and selling off for malice to data message simultaneously.
The present invention is achieved through the following technical solutions：
A kind of recognition methods for realizing data owner in big data transaction, including the data encryption step carried out by Encryption Model
S100, data authentication step S200 and data decryption step S300, the Encryption Model is by the mould for determining master key MK
Type initializes INIT modules, the algorithm management AM modules for adding/deleting and updating algorithm set EAS, for according to data
Feature selects appropriate AES ALG AES to select AS modules, key to disperse KD modules and guarantor in algorithm set EAS
Form is stayed to encrypt FPE modules composition, the data encryption step S100 is included the mesh in the initial data plaintext X for needing encryption
Mark data clear text X1 is handled by FPE protections, obtains the target data ciphertext Y1 of same format length；The data authentication step
S200 includes verifying target data plaintext X1 using HASH algorithms by algorithm management AM modules, obtains target data bright
Owner's information of literary X1 authenticity information and target data plaintext X1；The data decryption step S300 is included number of targets
Target data plaintext X1 and initial data plaintext X is obtained by FPE decryption according to ciphertext Y1.
In order to preferably realize the present invention, it is preferable that the data encryption step S100 specifically also includes：
S110 selects AS according to the target data plaintext X1 of input type type and format character feature using AES
Module selects appropriate AES ALG in form encryption FPE modular algorithm set EAS is retained；
S120 passes through model initialization INIT modules profit according to target data plaintext X1 format character and algorithm ALG feature
With the scattered generation encryption key key of master key MK；
Target data plaintext X1 is encrypted using AES Enc and encryption key key by S130, generation correspondence ciphertext Y1.
In order to preferably realize the present invention, it is preferable that the data authentication step S200 specifically also includes complete to data
The verification step of property：
S210 randomly selects N number of data cell using AES selection AS modules in target data X1；
S211 calculates the HASH of this N number of data cell using algorithm management AM modules, and fixed and justice is A-HASH；
S212 selects to randomly select corresponding N in step S210 in the target data X2 of AS modules after a transaction using AES
Individual data cell；
S213 utilizes the HASH of N number of data cell in algorithm management AM module calculation procedures S230, and fixed and justice is B-HASH；
S214 judges whether A-HASH=B-HASH is equal, obtains data and truly verifies.
In order to preferably realize the present invention, it is preferable that the data authentication step S200 specifically also includes complete to file
The verification step of property：
S220 randomly selects N number of data cell using AES selection AS modules in target data X1；
S221 calculates the HASH of this N number of data cell using algorithm management AM modules, and fixed and justice is A-HASH；
S222 selects to randomly select correspondence in step S210 in the target data X2 of AS modules after a transaction using AES
N number of data cell；
S223 utilizes the HASH of N number of data cell in algorithm management AM module calculation procedures S230, and fixed and justice is B-HASH；
S224 judges whether A-HASH=B-HASH is equal, obtains data and truly verifies.
In order to preferably realize the present invention, it is preferable that the data decryption step S300 specifically also includes：
S310 inputs need the ciphertext Y1 decrypted type type and format character feature to select AS modules using AES
Appropriate decipherment algorithm ALG is selected in FPE set of algorithms EAS；
S311 passes through model initialization according to ciphertext Y1 type type and format character feature and algorithm ALG feature
INIT modules utilize the scattered generation decruption key key of master key MK；
Ciphertext Y1 is decrypted using decipherment algorithm and decruption key key by S312, generation correspondence target data plaintext X1.
In order to preferably realize the present invention, it is preferable that the data authentication step S200 specifically also includes to data owner
Checking and rendering step：
S230 data owner's verification steps are specially：Decruption key key is inputted, selects AS modules to judge that decryption is close by AES
Key key correctness；
S231 encryption keys key is correct decryption FPE, and target data plaintext X1 and owner's information is presented；
S232 encryption keys key is mistake decryption FPE, and mess code and alarm is presented.
The present invention compared with prior art, with advantages below and beneficial effect：
（1）The present invention can be encrypted protection to data by FPE encryption technologies and select AS modules will by AES
Data are handled according to specific encryption or decipherment algorithm, and the corresponding informance related to owner is recorded in initial data
In, watermark is formed, prevents that data from illegally being distorted, meanwhile, it is easy to the identification of data, judges the authenticity and validity of data.
（2）The present invention can determine master key MK by INIT modules, and generated and deposited safely at random according to security parameter
Storage, during the wrong cipher key used when data deciphering, data will be shown in mess code mode and wrong data information is recorded into number
In, when inputting correct key, data can normally show and while owner's information be shown, for data owner grasp data
Circulation record, checking data whether be tampered or called.
Brief description of the drawings
Fig. 1 is EAS tree structures；
Fig. 2 is the EAS structures described in embodiment 1；
Fig. 3 is EAS index informations；
Fig. 4 is AlgSelect algorithm schematic diagrames；
Fig. 5 is the module calling figure of ciphering process；
Fig. 6 is the flow chart of ciphering process；
Fig. 7 is owner's Information Authentication flow chart.
Embodiment
The present invention is described in further detail with reference to the preferred embodiments of the present invention, but the embodiment party of the present invention
Formula not limited to this.
Before being illustrated to embodiments of the invention, the related terms being related in the present invention are carried out first as follows
Explain：
Model initialization module（Initialization, INIT）：INIT modules determine Encryption Model master key MK, and MK is according to peace
Population parameter is generated and stored safely at random, what deserves to be explained is, if encrypted using network transmission, sender and recipient are common
With storage MK.
Algorithm management module（Algorithm Management, AM）：AM modules include FPE set of algorithms（Encryption
Algorithm Set, EAS）, and with addition, deletion and more new algorithm scheduling algorithm management function.
AES selecting module（Algorithm Selection, AS）：AS modules are according to data type type and form
Binding characteristic feature, selects appropriate reservation form AES ALG, ALG to include in the FPE algorithm sets EAS of model
AES Enc and decipherment algorithm Dec.
Key dispersed modules（Key Diversify, KD）：KD modules are according to lattice such as data type type, length length
The corresponding reservation format algorithms ALG selected in formula feature, and AS modules feature, has the scattered generations of master key MK to retain form
Cryptographic work key.Its A Hong factor is dispersion factor, is mainly made up of data format feature and FPE algorithm characteristics.
Preferred embodiment 1：
A kind of recognition methods for realizing data owner in big data transaction, with reference to shown in accompanying drawing 1-7, specifically, including by adding
Data encryption step S100, data authentication step S200 and data decryption step S300 that close model is carried out, the encryption mould
Type is by the model initialization INIT modules for determining master key MK, the algorithm for adding/deleting and updating algorithm set EAS
Management AM modules, the AES selection AS for selecting appropriate AES ALG in algorithm set EAS according to data characteristics
Module, key disperse KD modules and reservation form encryption FPE module compositions, and the data encryption step S100 includes to need to add
Target data plaintext X1 in close initial data plaintext X is handled by FPE protections, obtains the target data of same format length
Ciphertext Y1；The data authentication step S200 is included by algorithm management AM modules using HASH algorithms to target data plaintext X1
Verified, obtain target data plaintext X1 authenticity information and target data plaintext X1 owner's information；The data
Decryption step S300 includes target data ciphertext Y1 obtaining target data plaintext X1 and initial data plaintext X by FPE decryption.
In order to preferably realize the present invention, it is preferable that the data encryption step S100 specifically also includes：
S110 selects AS according to the target data plaintext X1 of input type type and format character feature using AES
Module selects appropriate AES ALG in form encryption FPE modular algorithm set EAS is retained；
In this step, FPE algorithm sets EAS is subjected to tissue with tree structure in AM modules, as shown in figure 1, making root node
For first layer, FPE algorithms are divided into accumulation by the second layer according to data type, and third layer is on the basis of the second layer according to the type
The format constraints feature such as data length, scope do specific FPE algorithms of all circles' point correspondence in further division, third layer
ALEij。
Specifically, TYPE0 is character type string, contains three FPE algorithms, ALG00：FFX,ALG01：BPS,ALG02：
RtE.TYPE1 is integer integer, contains two FPE algorithms, ALG10：Prefix, ALG11：FFSEM, as shown in Figure 2.
What deserves to be explained is, the appropriate AES ALG of selection mode can be realized in the following way, but not
Being confined to the present embodiment, this is a kind of.
Algorithms selection modules A S is selected suitably according to data type type and form binding characteristic feature in EAS
FPE algorithms ALG（Enc, Dec）←AlgSelect（EAS, type, feature）, wherein Enc is AES, and Dec is correspondence
Decipherment algorithm, either encryption or decrypt, the data selection identical FPE algorithms of same type and feature.AlgSelect
Algorithm is shown as shown in Figure 4.
First, according to data type type, indexed file and index in Selecting Index number, that is, determine tree structure
In the 2nd node layer in position i, then, entered according to other features such as data length, scope feature in secondary index
Row positioning call number, that is, determine that next layer of node i determines position j, the FPEA of the third layer node navigated in tree structure
Algorithm ALGij。
S120 passes through model initialization INIT moulds according to target data plaintext X1 format character and algorithm ALG feature
Block utilizes the scattered generation encryption key key of master key MK；
Described key MK is scattered to generate encryption key key in the present embodiment, is specially：Key is scattered refer to it is high level close
Key combines the identifier feature of low one-level（Dispersion factor）The process of the key of low one-level is derived by decentralized algorithm.Using close
Key decentralized algorithm generation working key key ← KeyDiversify（MK, factor, E（.））, wherein MK is master key, factor
For dispersion factor, key is working key.For being encrypted or decrypting to data every time, according to input data feature and choosing
The algorithm characteristics selected constitute dispersion factor, have master key MK to utilize E（.）Scattered generation working key key, it is then close using work
Key is encrypted or decrypted to data；Wherein, the data characteristics includes data type and data length；The algorithm characteristics
For index information.
Target data plaintext X1 is encrypted using AES Enc and encryption key key by S130, generation correspondence ciphertext
Y1。
In order to preferably realize the present invention, it is preferable that the data authentication step S200 specifically also includes complete to data
The verification step of property：
S210 randomly selects N number of data cell using AES selection AS modules in target data X1；
S211 calculates the HASH of this N number of data cell using algorithm management AM modules, and fixed and justice is A-HASH；
S212 selects to randomly select corresponding N in step S210 in the target data X2 of AS modules after a transaction using AES
Individual data cell；
S213 utilizes the HASH of N number of data cell in algorithm management AM module calculation procedures S230, and fixed and justice is B-HASH；
S214 judges whether A-HASH=B-HASH is equal, obtains data and truly verifies.
What deserves to be explained is, HASH algorithms are a kind of existing algorithms, and " hash " is done in general translation, also have the direct transliteration to be
" Hash ", be exactly the input random length（It is called and does preliminary mapping, pre-image）, by hashing algorithm, it is transformed into solid
The output of measured length, the output is exactly hashed value.This conversion is a kind of compression mapping, it is, the space of hashed value is usual
Much smaller than the space of input, different inputs may hash to identical output, it is impossible to come unique from hashed value
Determine input value.It is exactly briefly a kind of letter of eap-message digest of message compression by random length to a certain regular length
Number.The present embodiment is the one of unit for the technological means for solving the problems, such as use just with HASH algorithms, and utilizes
Above-mentioned calculation verifies data, and accordingly, with respect to HASH computational methods, just it is no longer repeated in the present embodiment.
Preferred embodiment 2：
In order to preferably realize the present invention, it is preferable that the data authentication step S200 specifically also includes to file integrality
Verification step：
S220 randomly selects N number of data cell using AES selection AS modules in target data X1；
S221 calculates the HASH of this N number of data cell using algorithm management AM modules, and fixed and justice is A-HASH；
S222 selects to randomly select correspondence in step S210 in the target data X2 of AS modules after a transaction using AES
N number of data cell；
S223 utilizes the HASH of N number of data cell in algorithm management AM module calculation procedures S230, and fixed and justice is B-HASH；
S224 judges whether A-HASH=B-HASH is equal, obtains data and truly verifies.
In order to preferably realize the present invention, it is preferable that the data decryption step S300 specifically also includes：
S310 inputs need the ciphertext Y1 decrypted type type and format character feature to select AS modules using AES
Appropriate decipherment algorithm ALG is selected in FPE set of algorithms EAS；
S311 passes through model initialization according to ciphertext Y1 type type and format character feature and algorithm ALG feature
INIT modules utilize the scattered generation decruption key key of master key MK；
Ciphertext Y1 is decrypted using decipherment algorithm and decruption key key by S312, generation correspondence target data plaintext X1.
In order to preferably realize the present invention, it is preferable that the data authentication step S200 specifically also includes to data owner
Checking and rendering step：
S230 data owner's verification steps are specially：Decruption key key is inputted, selects AS modules to judge that decryption is close by AES
Key key correctness；
S231 encryption keys key is correct decryption FPE, and target data plaintext X1 and owner's information is presented；
S232 encryption keys key is mistake decryption FPE, and mess code and alarm is presented.
It is described above, be only presently preferred embodiments of the present invention, any formal limitation not done to the present invention, it is every according to
According to the present invention technical spirit above example is made any simple modification, equivalent variations, each fall within the present invention protection
Within the scope of.
Claims (6)
1. a kind of recognition methods for realizing data owner in big data transaction, including the data encryption carried out by Encryption Model are walked
Rapid S100, data authentication step S200 and data decryption step S300, it is characterised in that：The Encryption Model is by for determining
Master key MK model initialization INIT modules, the algorithm management AM modules for adding/deleting and updating algorithm set EAS,
For being selected appropriate AES ALG AES to select AS modules, key point in algorithm set EAS according to data characteristics
KD modules and reservation form encryption FPE module compositions are dissipated, the data encryption step S100 includes that the original number of encryption will be needed
Handled according to the target data plaintext X1 in plaintext X by FPE protections, obtain the target data ciphertext Y1 of same format length；Institute
Stating data authentication step S200 includes verifying target data plaintext X1 using HASH algorithms by algorithm management AM modules,
Obtain target data plaintext X1 authenticity information and target data plaintext X1 owner's information；The data decryption step
S300 includes target data ciphertext Y1 obtaining target data plaintext X1 and initial data plaintext X by FPE decryption.
2. a kind of recognition methods for realizing data owner in big data transaction according to claim 1, it is characterised in that institute
Stating data encryption step S100 specifically also includes：
S110 selects AS according to the target data plaintext X1 of input type type and format character feature using AES
Module selects appropriate AES ALG in form encryption FPE modular algorithm set EAS is retained；
S120 passes through model initialization INIT modules profit according to target data plaintext X1 format character and algorithm ALG feature
With the scattered generation encryption key key of master key MK；
Target data plaintext X1 is encrypted using AES Enc and encryption key key by S130, generation correspondence ciphertext Y1.
3. a kind of recognition methods for realizing data owner in big data transaction according to claim 1 or 2, its feature exists
In the data authentication step S200 specifically also includes the verification step to data integrity：
S210 randomly selects N number of data cell using AES selection AS modules in target data X1；
S211 calculates the HASH of this N number of data cell using algorithm management AM modules, and fixed and justice is A-HASH；
S212 selects to randomly select corresponding N in step S210 in the target data X2 of AS modules after a transaction using AES
Individual data cell；
S213 utilizes the HASH of N number of data cell in algorithm management AM module calculation procedures S230, and fixed and justice is B-HASH；
S214 judges whether A-HASH=B-HASH is equal, obtains data and truly verifies.
4. a kind of recognition methods for realizing data owner in big data transaction according to claim 3, it is characterised in that institute
Stating data authentication step S200 specifically also includes the verification step to file integrality：
S220 randomly selects N number of data cell using AES selection AS modules in target data X1；
S221 calculates the HASH of this N number of data cell using algorithm management AM modules, and fixed and justice is A-HASH；
S222 selects to randomly select correspondence in step S210 in the target data X2 of AS modules after a transaction using AES
N number of data cell；
S223 utilizes the HASH of N number of data cell in algorithm management AM module calculation procedures S230, and fixed and justice is B-HASH；
S224 judges whether A-HASH=B-HASH is equal, obtains data and truly verifies.
5. a kind of recognition methods for realizing data owner in big data transaction according to claim 1 or 2 or 4, its feature
It is, the data decryption step S300 specifically also includes：
S310 inputs need the ciphertext Y1 decrypted type type and format character feature to select AS modules using AES
Appropriate decipherment algorithm ALG is selected in FPE set of algorithms EAS；
S311 passes through model initialization according to ciphertext Y1 type type and format character feature and algorithm ALG feature
INIT modules utilize the scattered generation decruption key key of master key MK；
Ciphertext Y1 is decrypted using decipherment algorithm and decruption key key by S312, generation correspondence target data plaintext X1.
6. a kind of recognition methods for realizing data owner in big data transaction according to claim 5, it is characterised in that institute
Stating data authentication step S200 specifically also includes the checking to data owner and rendering step：
S230 data owner's verification steps are specially：Decruption key key is inputted, selects AS modules to judge that decryption is close by AES
Key key correctness；
S231 encryption keys key is correct decryption FPE, and target data plaintext X1 and owner's information is presented；
S232 encryption keys key is mistake decryption FPE, and mess code and alarm is presented.
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