CN106886722A - Big data information processing method and device - Google Patents
Big data information processing method and device Download PDFInfo
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Abstract
The embodiment of the present invention provides a kind of big data information processing method and device.The method includes：First node receives the attribute information of the big data that Section Point sends, the attribute information generation target block according to big data, the corresponding information of target block is sent into Section Point, so that Section Point is verified to the corresponding information of target block；If target block to be connected to the end of block chain to target block corresponding Information Authentication success for Section Point；Wherein first node and Section Point are the nodes in peer-to-peer network.The embodiment of the present invention generates target block by the big data attribute information directly provided according to Section Point, and by the checking of each Section Point, it is ensured that the accuracy and authenticity of target block；Because block chain technology has the characteristic that cannot be tampered once generation in itself, it is ensured that the big data attribute information in the block chain of announcement will not be tampered, and thereby may be ensured that the authenticity of the big data attribute information of announcement.
Description
Technical field
The present embodiments relate to data communication technology field, more particularly to a kind of big data information processing method and dress
Put.
Background technology
With the development of big data and big data technology, big data transaction platform is occurred in that, big data transaction platform can connect
The big data that each supplier is provided is received, and big data is collected, arranges and is announced, the specific attribute letter for announcing big data
Breath, supplier's information of the attribute information including big data, Transaction Information, content introduction etc..Buyer concludes the business according to big data
The attribute information that platform is announced buys the big data of oneself needs.
Big data transaction platform is the center of big data transaction, the category of the big data that complete independently is provided each supplier
Property information collection, arrange and announce.Data maintenance personnel by big data transaction platform can arbitrarily announce new information and
The attribute information of the big data that modification has been announced.
Big data transaction platform is once successfully invaded by attacker, and attacker can just be announced by big data transaction platform
The attribute information of deceptive information, the random big data for distorting announcement, causes the attribute information of the big data announced untrue.Cause
This, there is the risk being tampered in the data that big data transaction platform is announced, reliability is relatively low.
The content of the invention
The embodiment of the present invention provides a kind of big data information processing method and device, is handed over solving big data in the prior art
There is the risk being tampered, the relatively low problem of reliability in the data that easy platform is announced.
The one side of the embodiment of the present invention is to provide a kind of big data information processing method, including：
First node receives the attribute information of the big data that Section Point sends；
The first node generates target block according to the attribute information of the big data, and the target block is used to constitute
Block chain；
The corresponding information of the target block is sent to the Section Point by the first node, so that the second section
Point is verified to the corresponding information of the target block；
If the Section Point is to the target block corresponding Information Authentication success, the first node is by the mesh
Mark block is connected to the end of the block chain；Wherein, the first node and the Section Point are the sections in peer-to-peer network
Point.
The other side of the embodiment of the present invention is to provide a kind of big data information processing method, including：
Section Point sends the attribute information of big data to first node, so that the first node is according to the big data
Attribute information generation target block, the target block be used for constitute block chain；
The Section Point receives the corresponding information of the target block that the first node sends；
The Section Point is verified to the corresponding information of the target block；
If the Section Point is to the target block corresponding Information Authentication success, the Section Point is by the mesh
Mark block is connected to the end of the block chain；
Wherein, the first node and the Section Point are the nodes in peer-to-peer network.
The other side of the embodiment of the present invention is to provide a kind of big data information processor, is applied to first node,
Including：
First sending module, the attribute information of the big data for receiving Section Point transmission；
First processing module, for generating target block according to the attribute information of the big data, the target block is used
In composition block chain；
First sending module is additionally operable to for the corresponding information of the target block to be sent to the Section Point, so that
The Section Point is verified to the corresponding information of the target block；
If the first processing module is additionally operable to the Section Point to the corresponding Information Authentication success of the target block,
The target block is then connected to the end of the block chain；
Wherein, the first node and the Section Point are the nodes in peer-to-peer network.
The other side of the embodiment of the present invention is to provide a kind of big data information processor, is applied to Section Point,
Including：
Second sending module, for first node send big data attribute information so that the first node according to
The attribute information generation target block of the big data, the target block is used to constitute block chain；
Receiver module, for receiving the corresponding information of the target block that the first node sends；
Authentication module, for being verified to the corresponding information of the target block；
Second processing module, if for the Section Point to the corresponding Information Authentication success of the target block, will
The target block is connected to the end of the block chain；
Wherein, the first node and the Section Point are the nodes in peer-to-peer network.
Big data information processing method provided in an embodiment of the present invention and device, by first node according to each Section Point
The attribute information of the big data of transmission, generates target block, and target block is sent into each Section Point, so that each second section
Point is verified to the corresponding information of target block, after Section Point Information Authentication success corresponding to target block, first
Target block is connected to node the end of block chain.Each target block in block chain is directly provided according to each Section Point
The generation of big data attribute information, and by the checking of each Section Point, it is to avoid individually complete the category of big data by Centroid
Property information announcement process, it is ensured that generation target block accuracy and authenticity；And block chain technology has one in itself
The characteristic that denier generation cannot just be tampered, the big data attribute information further ensured in the block chain of announcement will not be usurped
Change, thereby may be ensured that the authenticity of the big data attribute information of announcement.
Brief description of the drawings
Fig. 1 is the flow chart of the big data information processing method that the embodiment of the present invention one is provided；
Fig. 2 is the data structure schematic diagram of the block chain that the present invention two is provided and target block；
Fig. 3 is the flow chart of the big data information processing method that the embodiment of the present invention three is provided；
Fig. 4 is the signaling diagram of the big data information processing method that the embodiment of the present invention five is provided；
Fig. 5 is the structure chart of the big data information processor that the embodiment of the present invention six is provided；
Fig. 6 is the structure chart of the big data information processor that the embodiment of the present invention seven is provided；
Fig. 7 is the structure chart of the big data information processor that the embodiment of the present invention eight is provided.
Specific embodiment
It is right below in conjunction with the accompanying drawing in the embodiment of the present invention to make technical scheme and advantage clearer
Technical scheme is clearly and completely described, it is clear that described embodiment is a part of embodiment of the invention,
Rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art are not making creative labor
The every other embodiment obtained under the premise of dynamic, belongs to the scope of protection of the invention.
Peer-to-peer network, i.e. peer-to-peer computer network, are that one kind distributes task and workload between peer network node
Distributed Application framework, be a kind of networking or latticed form that P2P computing model is formed in application layer.In a peer-to-peer network,
All in the status of equity between the multiple stage computers being connected to each other, each computer has identical function, without master-slave, one
Platform computer can not only be used for server, and setting shared resource is used for other computers in peer-to-peer network, again can be as work
Stand, whole network is independent of special centralized servers, also without special work station.Each computer in network was both
Can serve as the requestor of network service, but request to other computers is responded, there is provided resource, service and content.Equity
Each computer in network is referred to as a network node.
Block chain technology is the computer technologies such as Distributed Storage, peer-to-peer network transmission, common recognition mechanism, AES
New application pattern, wherein common recognition mechanism be realize setting up between different nodes in the peer-to-peer network for generate block chain trust,
The rule of rights and interests is obtained, including data transmit-receive form and rule etc..Block chain be it is a kind of sequentially in time by data block with
A kind of linked data structure that the connected mode of order is combined into, and ensure that block can not be distorted and can not be pseudo- in cryptography mode
Make, anti-counterfeiting information is included in each data block, validity (false proof) and generation for verifying information in the data block
Next block.
Embodiment one
Fig. 1 is the flow chart of the big data information processing method that the embodiment of the present invention one is provided.The embodiment of the present invention is directed to
There is the risk being tampered in the big data attribute information that big data transaction platform is announced in the prior art, reliability is relatively low to ask
Topic, there is provided big data information processing method.As shown in figure 1, the method is comprised the following steps that：
Step S101, first node receive the attribute information of the big data that Section Point sends.
Wherein, first node and Section Point are the nodes in peer-to-peer network；The attribute information of big data at least includes category
Property information encoding, the mark of big data commodity, metadata, data trade information, data set provider information.In the present embodiment, greatly
Availability of data business can provide multiple big data commodity, each big data commodity one attribute information of big data of correspondence.Greatly
The mark for being designated the big data commodity corresponding to big data attribute information of data commodity, can be used for unique mark one big
The attribute information of data.Metadata is the description information to big data commodity, for example, for big data commodity purposes, field, interior
Summarized introduction of appearance etc. etc..
In the present embodiment, the peer-to-peer network includes two kinds of network node, first node and Section Point.Wherein,
Section Point can be the terminal device of the corresponding data message that can be used to manage big data supplier of big data supplier,
Section Point is corresponded with big data supplier.First node is the network node for generating target block, can be single
One in the network node solely set up, or Section Point set in advance.Peer-to-peer network includes multiple second sections
Point and a first node, first node is identical with each Section Point interaction in the present embodiment, only with first node with appoint
Data exchange process between one Section Point of meaning is illustrated.In the step, first node receives what each Section Point sent
The attribute information of big data.
For example, a more believable supplier cannot be put forward in major data suppliers, a network is individually set up
Node is used to generate target block；Or, major data suppliers arrange a believable target offerings business in advance, by the target
The corresponding Section Point of supplier is used as first node.
Step S102, first node generate target block according to the attribute information of big data, and target block is used to constitute area
Block chain.
In the present embodiment, the big number that first node sends according to default block generating algorithm and each Section Point for receiving
According to attribute information, generate target block.Wherein, block generating algorithm is preset by technical staff according to actual needs in common recognition machine
Preset in system.
The corresponding information of target block is sent to Section Point by step S103, first node, so that Section Point is to mesh
The corresponding information of mark block is verified.
In the present embodiment, after first node generation target block, the corresponding information of target block is sent to each second
Node so that each Section Point is according to the default block verification algorithm corresponding with default block generating algorithm to the target block
Corresponding information is verified, and confirms that the result is fed back to first node by rule according to default checking.
Specifically, the corresponding information of target block can be sent to Section Point by first node in the form of broadcast,
That is, first node is broadcasted the corresponding information of target block so that each Section Point in peer-to-peer network can receive institute
The corresponding information of target block of broadcast.
Wherein, preset block verification algorithm is used to generate the default block life of target block with first node in step S102
It is corresponding into algorithm, preset according to actual needs by technical staff.Default proof rule is the Section Point of pre-selection setting
To the rule of first node feedback validation result so that first node can recognize Section Point feedback according to default proof rule
The result, and follow-up data processing is carried out according to the result.
For example, default checking confirms that a kind of implementation of rule can be：Section Point is corresponding to target block
After Information Authentication failure, to first node feedback validation failed message；If Section Point is to the corresponding Information Authentication of target block
Success, then do not feed back any message to first node；Correspondingly, if first node receives second section in the first Preset Time
The authentication failed message of point feedback, it is determined that the Section Point authentication failed, if otherwise first node is in the first Preset Time
It is not received by the authentication failed message of Section Point feedback, it is determined that the Section Point is proved to be successful.Or, preset checking true
Recognizing another implementation of rule can be：If Section Point is to the corresponding Information Authentication failure of target block, to first
Node feeding back authentication failed message, if Section Point feeds back to the corresponding Information Authentication success of target block to first node
It is proved to be successful message；Correspondingly, if first node receives the authentication failed message of Section Point in the first Preset Time,
The Section Point authentication failed is determined, if the checking achievement that first node receives Section Point in the first Preset Time disappears
Breath, it is determined that the Section Point is proved to be successful.Wherein the first Preset Time, default proof rule are by technical staff according to actual need
To be preset in common recognition mechanism.
If step S104, Section Point are to target block corresponding Information Authentication success, first node is by target block
It is connected to the end of block chain.
Whether in the step, first node confirms rule according to default checking, determine Section Point to target block correspondence
Information Authentication success, can specifically realize in the following ways：
(1) first node confirms rule according to default checking, determines whether each Section Point is corresponding to target block
Information Authentication success, if all of Section Point is to target block corresponding Information Authentication success, it is determined that Section Point is
It is no successful to the corresponding Information Authentication of target block；Otherwise, if any Section Point loses to the corresponding Information Authentication of target block
Lose, it is determined that Section Point is to the corresponding Information Authentication failure of target block.(2) first node confirms rule according to default checking
Then, whether each Section Point is determined to the corresponding Information Authentication success of target block, if testing the corresponding information of target block
When demonstrate,proving the shared ratio in all Section Points of successful Section Point more than or equal to predetermined threshold value, it is determined that second section
Point is to the corresponding Information Authentication success of target block；Otherwise, if to the target block successful Section Point of corresponding Information Authentication
When shared ratio is less than predetermined threshold value in all Section Points, it is determined that Section Point is tested the corresponding information of target block
Card failure.Wherein, preset checking and confirm that rule is preset in common recognition mechanism according to actual needs by technical staff.
In the present embodiment, however, it is determined that to target block corresponding Information Authentication success, first node is by target for Section Point
Block is connected to the end of block chain so that each Section Point is corresponding during user can obtain block chain by downloading block chain
The attribute information of big data.
In the present embodiment, block chain is stored on first node and each Section Point simultaneously, and each Section Point and the
The block chain synchronization of one node storage, when the block chain in first node updates, the block chain of each Section Point storage will be same
Step is updated to the newest block chain stored on first node.
The attribute information of the big data that the embodiment of the present invention is sent by first node according to each Section Point, generates target
Block, and target block is sent to each Section Point, so that each Section Point is verified to the corresponding information of target block,
After Section Point Information Authentication success corresponding to target block, target block is connected to first node the end of block chain
Tail.Each target block in block chain is the big data attribute information generation directly provided according to each Section Point, and by each
The checking of Section Point, it is to avoid the announcement process of the attribute information of big data is individually completed by Centroid, it is ensured that generation mesh
Mark the accuracy and authenticity of block；And block chain technology has the characteristic that cannot be tampered once generation in itself, enters one
Step ensure that the big data attribute information in the block chain of announcement will not be tampered, and thereby may be ensured that the big data attribute of announcement
The authenticity of information.
Embodiment two
Fig. 2 is the data structure schematic diagram of the block chain that the embodiment of the present invention two is provided and target block.As shown in Fig. 2
20 block chains include multiple blocks 21, and the block for being connected to block chain end is the block being newly generated.Target block 22 includes
Header information 221 and main information 222, header information 221 include block-identified information, the first information, the second information, time
Stamp；Main information 222 includes the attribute information of each big data.The data of each block 21 in target block 22 and block chain 20
Structure all same.
Wherein, the first information of target block is determined according to the header information of last block of block chain, mesh
The second information for marking block is determined according to the attribute information of big data；The timestamp of target block is used to represent target block
The moment of generation.
On the basis of above-described embodiment one, in the present embodiment, first node generates mesh according to the attribute information of big data
Mark block, specifically includes：First node generates the header information of target block according to the attribute information of big data；First node root
Target block is constituted according to the attribute information of big data and the header information of target block, the attribute information of big data is target block
Main information.
In the present embodiment, first node generates the header information of target block according to the attribute information of big data, including：The
One node generates the head of target block according to the header information of last block of the attribute information and block chain of big data
Information.Can specifically realize in the following way：
The attribute information of each big data in the main information of target block, calculates the second letter of target block
Breath.Second information is Merkle tree roots, is that all records collect on the main information to target block.Wherein, the second letter
The summary info reality that breath can be calculated by the attribute information of each big data in the main information for calculating target block
Show, or the method realization of Merkle tree roots can be calculated using any one Merkle tree algorithm in the prior art, this
Inventive embodiments are not specifically limited to this.
The first information of last block according to block chain and the second information, generate the first information of target block.
Wherein, the first information of target block can be the first information and the second information sum of last block of block chain.
After the other information of generation target block, finally for target block covers timestamp.
In the present embodiment, identification information, the first information, the second information and main body in the header information of generation target block
It is that target block covers timestamp after information.The timestamp can be generated by first node can also be by believable third party
There is provided, the present embodiment is not specifically limited for the generating mode of the timestamp.
In the present embodiment, block chain is stored on first node and each Section Point simultaneously, and each Section Point and the
The block chain synchronization of one node storage, when the block chain in first node updates, the block chain of each Section Point storage will be same
Step is updated to the newest block chain stored on first node.
In another embodiment of the present invention, according to common recognition mechanism, if each Section Point has mutually carried out checking identity
Information, first node includes according to the attribute information of big data generation target block：Receive that each Section Point sends to each
The result of Section Point identity, according to the result to each Section Point identity that each Section Point sends, to receiving
The attribute information of big data arranged, the attribute information of effective big data is obtained, according to the attribute of effective big data
Information generates target block.
The embodiment of the present invention gives the detailed process of generation target block, by first node according to the attribute of big data
The header information of last block of information and block chain, generates the header information of target block, the attribute information of big data
It is the main information of target block, by the first information of header information by last block of target block and block chain
Header information is associated, and the header information of target block can be carried out according to the header information of last block of block chain
Checking, and plus timestamp so that the header information of target block can not be tampered；In addition, the second information root of target block
Generated according to main information, can be used for verifying whether the big data attribute information in main information is tampered, thereby may be ensured that
Target block is not tampered with.
Embodiment three
Fig. 3 is the flow chart of the big data information processing method that the embodiment of the present invention three is provided.The embodiment of the present invention is directed to
There is the risk being tampered in the big data attribute information that big data transaction platform is announced in the prior art, reliability is relatively low to ask
Topic, there is provided big data information processing method.As shown in figure 3, the method is comprised the following steps that：
Step S301, Section Point send the attribute information of big data to first node, so that first node is according to big number
According to attribute information generate target block, target block be used for constitute block chain.
Wherein, first node and Section Point are the nodes in peer-to-peer network；The attribute information of big data at least includes category
Property information encoding, the mark of big data commodity, metadata, data trade information, data set provider information.In the step, second
The attribute information of big data is sent to first node by node according to default form, wherein default form is by technical staff's root
Preset in common recognition mechanism according to being actually needed.
In the present embodiment, the supplier of big data can provide multiple big data commodity, each big data commodity correspondence one
The attribute information of individual big data.The mark for being designated the big data commodity corresponding to big data attribute information of big data commodity,
Can be used for one attribute information of big data of unique mark.Metadata is the description information to big data commodity, for example, for
Summarized introduction of big data commodity purposes, field, content etc. etc..
In the present embodiment, the peer-to-peer network includes two kinds of network node, first node and Section Point.Wherein,
Section Point can be the terminal device of the corresponding data message that can be used to manage big data supplier of big data supplier,
Section Point is corresponded with big data supplier.First node is the network node for generating target block, can be single
One in the network node solely set up, or Section Point set in advance.Peer-to-peer network includes multiple second sections
Point and a first node, first node is identical with each Section Point interaction in the present embodiment, only with any one second
Data exchange process between node with first node is illustrated.
Step S302, Section Point receive the corresponding information of target block that first node sends.
Step S303, Section Point are verified to the corresponding information of target block.
Specifically, Section Point according to the default block verification algorithm corresponding with default block generating algorithm to the target
The corresponding information of block is verified, and confirms that rule is broadcasted the result according to default checking, feeds back to first segment
Point.
Wherein, preset block verification algorithm is used to generate the default block life of target block with first node in step S102
It is corresponding into algorithm, preset according to actual needs by technical staff.Default proof rule is the Section Point of pre-selection setting
To the rule of first node feedback validation result so that first node can recognize Section Point feedback according to default proof rule
The result, and follow-up data processing is carried out according to the result.
For example, default checking confirms that a kind of implementation of rule can be：Section Point is corresponding to target block
After Information Authentication failure, verifying broadcasts failed message；If Section Point is to the corresponding Information Authentication success of target block, wideless
Broadcast any message；If during so that first node receiving the authentication failed message of Section Point feedback in the first Preset Time,
The Section Point authentication failed is determined, if otherwise first node is not received by Section Point feedback in the first Preset Time
Authentication failed message, it is determined that the Section Point is proved to be successful.Or, preset checking and confirm that another implementation of rule can
Think：If Section Point is to the corresponding Information Authentication failure of target block, verifying broadcasts failed message, if Section Point is to mesh
The corresponding Information Authentication of mark block is successful, then verifying broadcasts success message；If so that first node connects in the first Preset Time
The authentication failed message of Section Point is received, it is determined that the Section Point authentication failed, if first node is in the first Preset Time
Inside receive the checking achievement message of Section Point, it is determined that the Section Point is proved to be successful.
If step S304, Section Point are to target block corresponding Information Authentication success, Section Point is by target block
It is connected to the end of block chain.
In the step, Section Point confirms rule according to default checking, it is determined whether the corresponding information of target block is tested
Demonstrate,prove successfully, can specifically realize in the following ways：
(1) Section Point verifies that, if being proved to be successful, Section Point is tested according to default to the corresponding information of target block
Whether card confirms rule, other Section Points is determined to the corresponding Information Authentication success of target block, if all of Section Point
To the corresponding Information Authentication success of target block, then target block is connected to the Section Point end of block chain；Otherwise,
If any Section Point fails to the corresponding Information Authentication of target block, the first node to be received such as the Section Point is sent out again
The corresponding information of target block sent.(2) Section Point verifies to the corresponding information of target block, if being proved to be successful,
Two nodes confirm rule according to default checking, determine other each Section Points whether to the corresponding Information Authentication of target block into
Work(, if the ratio shared in all Section Points to the target block successful Section Point of corresponding Information Authentication be more than or
During equal to predetermined threshold value, then target block is connected to the Section Point end of block chain；Otherwise, if to target block correspondence
The successful Section Point of Information Authentication ratio shared in all Section Points when being less than predetermined threshold value, then Section Point will
Target block is connected to the end of block chain.
In the present embodiment, if target block is connected to area by Section Point to the corresponding Information Authentication success of target block
The end of block chain so that user can download block chain and obtain the corresponding big number of each Section Point in block chain by Section Point
According to attribute information.
In the present embodiment, because block chain is stored on first node and each Section Point simultaneously, and each Section Point
It is synchronous with the block chain that first node is stored, when the block chain in first node updates, the block chain of each Section Point storage
It is the newest block chain stored on first node by synchronized update, therefore step S304 can also be by direct synchronization block
Chain is realized.
The embodiment of the present invention sends the attribute information of big data by Section Point to first node, so that first node root
Target block is generated according to the attribute information of big data, each Section Point is verified to the corresponding information of target block, when second
After node is to the corresponding Information Authentication success of target block, target block is connected to the end of block chain.It is each in block chain
Target block is the big data attribute information generation directly provided according to each Section Point, and by the checking of each Section Point,
The announcement process of the attribute information for avoiding individually completing big data by Centroid, it is ensured that the accuracy of generation target block and
Authenticity；And block chain technology has the characteristic that cannot be tampered once generation in itself, further ensures the area of announcement
Big data attribute information in block chain will not be tampered, and thereby may be ensured that the authenticity of the big data attribute information of announcement.
Example IV
On the basis of above-described embodiment three, in the present embodiment, big data is sent to first node according in Section Point
Attribute information before, also include：Each Section Point is mutually authenticated identity information.
In the present embodiment, each Section Point is stored with can uniquely indicate the public, private key pair of the Section Point, and simultaneously
And the Section Point is stored with the public key of other each Section Points, whether legal to the identity of other each Section Points can carry out
Checking.The process that each Section Point is mutually authenticated identity information can specifically be realized in the following way：
Section Point is encrypted with the private key of itself to the attribute information of the big data with preset format, and broadcast adds
The data message obtained after close so that other Section Points use being somebody's turn to do for storage after the data message for receiving the broadcast
The public key of Section Point carries out checking decryption to the identity of the Section Point, if the data after decryption are with the big of preset format
The attribute information of data, then confirm that the Section Point identity is legal, by the attribute information of the big data and its corresponding second section
The authentication result of point is sent to first node；If the data after decryption are not the attribute letters of the big data with preset format
Breath, then confirm that the Section Point identity is illegal, and the authentication result of the Section Point is sent into first node.
In the present embodiment, any Section Point is verified to the identity information of other each Section Points.In addition, this reality
Apply in example, Section Point can be the mode or other modes broadcasted to the mode that first node sends information, by technical staff
Preset in common recognition mechanism according to actual needs, the present embodiment is not specifically limited to this.
The embodiment of the present invention is mutually authenticated identity information by each Section Point, it is ensured that the identity of each Section Point it is legal
Property, will only verify that the data message of the big data of legal Section Point is sent to first node, and by the body of each Section Point
Part the result is sent to first node so that first node according to the authentication result of each Section Point and receive it is big
The attribute information generation target block of data, it is ensured that the authenticity of the information of generation target block.
Embodiment five
Fig. 4 is the signaling diagram of the big data information processing method that the embodiment of the present invention five is provided.As shown in figure 4, the method
Comprise the following steps：
Step S401, Section Point send the attribute information of big data to first node.
Step S402, first node receive the attribute information of the big data that Section Point sends, according to the attribute of big data
Information generates target block, and target block is used to constitute block chain.
The corresponding information of target block is sent to Section Point by step S403, first node.
Step S404, Section Point receive the corresponding information of target block that first node sends, and Section Point is to target
The corresponding information of block is verified；
Step S405, to first node feedback validation result.
If step S406, Section Point are to target block corresponding Information Authentication success, Section Point is by target block
It is connected to the end of the block chain of itself storage.
If step S407, Section Point are to target block corresponding Information Authentication success, first node is by target block
It is connected to the end of the block chain of itself storage.
The embodiment of the present invention gives the interaction of first node and Section Point in big data information processing method, right
The interaction all same of each Section Point and first node in Deng network.
Embodiment six
Fig. 5 is the structure chart of the big data information processor that the embodiment of the present invention six is provided.The embodiment of the present invention is provided
Big data information processor should perform big data information processing method embodiment one offer handling process, the device
It is applied to first node.As shown in figure 5, the device 50 includes：First sending module 501 and first processing module 502.
Wherein, the first sending module 501 is used for the attribute information of the big data for receiving Section Point transmission.
First processing module 502 is used to generate target block, the target block according to the attribute information of the big data
For constituting block chain.
First sending module 501 is additionally operable to for the corresponding information of the target block to be sent to the Section Point,
So that the Section Point is verified to the corresponding information of the target block.
If the first processing module 502 be additionally operable to the Section Point to the corresponding Information Authentication of the target block into
Work(, then the target block is connected to the end of the block chain.
Wherein, the first node and the Section Point are the nodes in peer-to-peer network.
The embodiment of the method that device provided in an embodiment of the present invention can be provided specifically for execution above-described embodiment one,
Here is omitted for concrete function.
The attribute information of the big data that the embodiment of the present invention is sent by first node according to each Section Point, generates target
Block, and target block is sent to each Section Point, so that each Section Point is verified to the corresponding information of target block,
After Section Point Information Authentication success corresponding to target block, target block is connected to first node the end of block chain
Tail.Each target block in block chain is the big data attribute information generation directly provided according to each Section Point, and by each
The checking of Section Point, it is ensured that the accuracy and authenticity of generation target block；Have in itself once due to block chain technology
The characteristic that generation cannot just be tampered, it is ensured that the big data attribute information in the block chain of announcement will not be tampered, so that can
To ensure the authenticity of the big data attribute information announced.
Embodiment seven
Fig. 6 is the structure chart of the big data information processor that the embodiment of the present invention seven is provided.In above-described embodiment six
On the basis of, in the present embodiment, as shown in fig. 6, the first processing module 502 includes：First treatment submodule 5021 and the
Two treatment submodules 5022.
Specifically, the first treatment submodule 5021 is used to generate the target block according to the attribute information of the big data
Header information.
Second processing submodule 5022 is used for the head letter of the attribute information and the target block according to the big data
Breath constitutes the target block, and the attribute information of the big data is the main information of the target block.
The first treatment submodule 5021 is additionally operable to according to the attribute information and the block chain of the big data most
The latter header information of block, generates the header information of the target block.
In the present embodiment, the header information includes：Block-identified information, the first information, the second information, timestamp.Its
In, the first information is to determine that second information is according to the header information of last block of the block chain
What the attribute information according to the big data determined；The timestamp is used to represent the moment of the target block generation.
The embodiment of the method that device provided in an embodiment of the present invention can be provided specifically for execution above-described embodiment two,
Here is omitted for concrete function.
The embodiment of the present invention is by first node according to last block of the attribute information of big data and block chain
Header information, generates the header information of target block, and the attribute information of big data is the main information of target block, by head
With the header information of last block of block chain be associated target block by the first information of information, can be according to block chain
The header information of last block the header information of target block is verified, and plus timestamp so that target area
The header information of block can not be tampered；In addition, the second information of target block is generated according to main information, can be used for checking master
Whether the big data attribute information in body information is tampered, and thereby may be ensured that target block is not tampered with.
Embodiment eight
Fig. 7 is the structure chart of the big data information processor that the embodiment of the present invention eight is provided.The embodiment of the present invention is provided
Big data information processor can perform the processing stream that big data information processing method embodiment three and example IV are provided
Journey, the device is applied to Section Point.As shown in fig. 7, the device 70 includes：Second sending module 701, receiver module 702, test
Card module 703 and Second processing module 704.
Wherein, the second sending module 701 is used to be sent to first node the attribute information of big data, so that the first segment
Point generates target block according to the attribute information of the big data, and the target block is used to constitute block chain.
Receiver module 702 is used to receive the corresponding information of the target block that the first node sends.
Authentication module 703 is used to verify the corresponding information of the target block.
Second processing module, if 704 are used for the Section Point to the corresponding Information Authentication success of the target block,
The target block is connected to the end of the block chain.
Wherein, the first node and the Section Point are the nodes in peer-to-peer network.
What device provided in an embodiment of the present invention can be provided specifically for execution above-described embodiment three and example IV
Embodiment of the method, here is omitted for concrete function.
The embodiment of the present invention sends the attribute information of big data by Section Point to first node, so that first node root
Target block is generated according to the attribute information of big data, each Section Point is verified to the corresponding information of target block, when second
After node is to the corresponding Information Authentication success of target block, target block is connected to the end of block chain.It is each in block chain
Target block is the big data attribute information generation directly provided according to each Section Point, and by the checking of each Section Point,
Ensure that the accuracy and authenticity of generation target block；Cannot be tampered once generation because block chain technology has in itself
Characteristic, it is ensured that the big data attribute information in the block chain of announcement will not be tampered, and thereby may be ensured that the big number of announcement
According to the authenticity of attribute information.
In several embodiments provided by the present invention, it should be understood that disclosed apparatus and method, can be by it
Its mode is realized.For example, device embodiment described above is only schematical, for example, the division of the unit, only
Only a kind of division of logic function, can there is other dividing mode when actually realizing, such as multiple units or component can be tied
Another system is closed or is desirably integrated into, or some features can be ignored, or do not perform.It is another, it is shown or discussed
Coupling each other or direct-coupling or communication connection can be the INDIRECT COUPLINGs or logical of device or unit by some interfaces
Letter connection, can be electrical, mechanical or other forms.
The unit that is illustrated as separating component can be or may not be it is physically separate, it is aobvious as unit
The part for showing can be or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On NE.Some or all of unit therein can be according to the actual needs selected to realize the mesh of this embodiment scheme
's.
In addition, during each functional unit in each embodiment of the invention can be integrated in a processing unit, it is also possible to
It is that unit is individually physically present, it is also possible to which two or more units are integrated in a unit.Above-mentioned integrated list
Unit can both be realized in the form of hardware, it would however also be possible to employ hardware adds the form of SFU software functional unit to realize.
The above-mentioned integrated unit realized in the form of SFU software functional unit, can store and be deposited in an embodied on computer readable
In storage media.Above-mentioned SFU software functional unit storage is in a storage medium, including some instructions are used to so that a computer
Equipment (can be personal computer, server, or network equipment etc.) or processor (processor) perform the present invention each
The part steps of embodiment methods described.And foregoing storage medium includes：USB flash disk, mobile hard disk, read-only storage (Read-
Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disc or CD etc. it is various
Can be with the medium of store program codes.
Those skilled in the art can be understood that, for convenience and simplicity of description, only with above-mentioned each functional module
Division carry out for example, in practical application, can distribute complete by different functional modules by above-mentioned functions as needed
Into, will the internal structure of device be divided into different functional modules, to complete all or part of function described above.On
The specific work process of the device of description is stated, the corresponding process in preceding method embodiment is may be referred to, be will not be repeated here.
Finally it should be noted that：Various embodiments above is merely illustrative of the technical solution of the present invention, rather than its limitations；To the greatest extent
Pipe has been described in detail with reference to foregoing embodiments to the present invention, it will be understood by those within the art that：Its according to
The technical scheme described in foregoing embodiments can so be modified, or which part or all technical characteristic are entered
Row equivalent；And these modifications or replacement, the essence of appropriate technical solution is departed from various embodiments of the present invention technology
The scope of scheme.
Claims (10)
1. a kind of big data information processing method, it is characterised in that including：
First node receives the attribute information of the big data that Section Point sends；
The first node generates target block according to the attribute information of the big data, and the target block is used to constitute block
Chain；
The corresponding information of the target block is sent to the Section Point by the first node, so that the Section Point pair
The corresponding information of the target block is verified；
If the Section Point is to the target block corresponding Information Authentication success, the first node is by the target area
Block is connected to the end of the block chain；
Wherein, the first node and the Section Point are the nodes in peer-to-peer network.
2. method according to claim 1, it is characterised in that attribute information of the first node according to the big data
Generation target block, including：The first node generates the head of the target block according to the attribute information of the big data
Information；
The first node constitutes the target according to the attribute information of the big data and the header information of the target block
Block, the attribute information of the big data is the main information of the target block.
3. method according to claim 2, it is characterised in that attribute information of the first node according to the big data
The header information of the target block is generated, including：
The first node according to the header information of last block of the attribute information and the block chain of the big data,
Generate the header information of the target block.
4. according to the method in claim 2 or 3, it is characterised in that the header information includes：Block-identified information,
One information, the second information, timestamp；
Wherein, the first information is determined according to the header information of last block of the block chain, described second
Information is determined according to the attribute information of the big data；
The timestamp is used to represent the moment of the target block generation.
5. a kind of big data information processing method, it is characterised in that including：
Section Point sends the attribute information of big data to first node, so that category of the first node according to the big data
Property information generation target block, the target block be used for constitute block chain；
The Section Point receives the corresponding information of the target block that the first node sends；
The Section Point is verified to the corresponding information of the target block；
If the Section Point is to the target block corresponding Information Authentication success, the Section Point is by the target area
Block is connected to the end of the block chain；
Wherein, the first node and the Section Point are the nodes in peer-to-peer network.
6. a kind of big data information processor, is applied to first node, it is characterised in that including：
First sending module, the attribute information of the big data for receiving Section Point transmission；
First processing module, for generating target block according to the attribute information of the big data, the target block is used for structure
Into block chain；
First sending module is additionally operable to for the corresponding information of the target block to be sent to the Section Point, so that described
Section Point is verified to the corresponding information of the target block；
If the first processing module is additionally operable to the Section Point to the corresponding Information Authentication success of the target block, will
The target block is connected to the end of the block chain；
Wherein, the first node and the Section Point are the nodes in peer-to-peer network.
7. device according to claim 6, it is characterised in that the first processing module includes：
First treatment submodule, the header information for generating the target block according to the attribute information of the big data；
Second processing submodule, the header information for the attribute information according to the big data and the target block constitutes institute
Target block is stated, the attribute information of the big data is the main information of the target block.
8. device according to claim 7, it is characterised in that the first treatment submodule is additionally operable to：
The header information of last block of attribute information and the block chain according to the big data, generates the target
The header information of block.
9. the device according to claim 7 or 8, it is characterised in that the header information includes：Block-identified information,
One information, the second information, timestamp；
Wherein, the first information is determined according to the header information of last block of the block chain, described second
Information is determined according to the attribute information of the big data；
The timestamp is used to represent the moment of the target block generation.
10. a kind of big data information processor, is applied to Section Point, it is characterised in that including：
Second sending module, the attribute information for sending big data to first node, so that the first node is according to
The attribute information generation target block of big data, the target block is used to constitute block chain；
Receiver module, for receiving the corresponding information of the target block that the first node sends；
Authentication module, for being verified to the corresponding information of the target block；
Second processing module, if for the Section Point to the corresponding Information Authentication success of the target block, will be described
Target block is connected to the end of the block chain；
Wherein, the first node and the Section Point are the nodes in peer-to-peer network.
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| CN201710179634.1A CN106886722A (en) | 2017-03-23 | 2017-03-23 | Big data information processing method and device |
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Application publication date: 20170623 |