CN103279718A - Data integrity verification method based on SBT in cloud storage - Google Patents
Data integrity verification method based on SBT in cloud storage Download PDFInfo
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- CN103279718A CN103279718A CN2013101854620A CN201310185462A CN103279718A CN 103279718 A CN103279718 A CN 103279718A CN 2013101854620 A CN2013101854620 A CN 2013101854620A CN 201310185462 A CN201310185462 A CN 201310185462A CN 103279718 A CN103279718 A CN 103279718A
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Abstract
The invention discloses a data integrity verification method based on SBT in cloud storage. The data integrity verification method is a data integrity verification scheme based on a node size balanced tree, the node size balanced tree has good balance so that the tree height can be controlled better, and the node size balanced tree is close to a complete binary tree. As time complexity of date updating and inquiring on the binary tree is relative to the tree height, the node size balanced tree has great advantages in efficiency of data operation, and time for data operation can be maintained on O (logn). The node size balanced tree has good flexibility in a data dynamic updating process, data are not only stored in leaf nodes of the node size balanced tree when stored in the node size balanced tree, and memory overhead of a server can be reduced to a certain extent. According to the technical scheme, the node size balanced tree and a hash function are combined, a high-efficiency authentication data structure suitable for large-scale data dynamic updating is designed, and therefore verification efficiency of data integrity is improved.
Description
Technical field
The invention belongs to the data security technical field in the cloud storage, more specifically say, relate in a kind of cloud storage the data integrity verification method based on SBT.
Background technology
The cloud storage is to be extended and development by the cloud computing concept, and as a kind of Service Operation pattern that has practical value and marketable value concurrently, it has caused that the stakeholder more and more pays close attention to.The thinking of cloud stores service and theory still are that the personal user is attractive for the enterprise customer, but safety problem has wherein also caused user's worry.
Data integrity verification technique in the cloud storage is one of gordian technique that guarantees data security in the cloud storage.The data integrity authentication mechanism is based on three-party model in the cloud storage.So-called three parts refers to cloud storage user, insincere server and trust data source.In three-party model, the user is outsourced to data on the external server, comprises a trust data source and a lot of insincere server.Wherein the trust data source is complete and in store user's data correctly, and it is published to data each insincere server again.When the user used the data of outsourcing at needs, one of them is visited by a needs or several insincere server gets final product.Because the server that the user visited when fetching data is incredible, is the raw data of not distorted and forging with regard to the data that need the data integrity authentication mechanism to guarantee that the user fetches at this moment.
The core concept of data integrity authentication mechanism is to adopt a kind of strategy of member's inquiry.This strategy be will the storage data Hash table combine with a data structure with confirmability, the authentication authorization and accounting data structure makes the answer of member's inquiry have verifiability, the user can verify whether draw the outsourcing data of visiting complete whereby.Member's inquiry can abstractly be following mathematical procedure: the data abstraction of outsourcing is become a data set S=(e
1, e
2..., e
n), e wherein
iThe data block of a fixed size in the data of representative.Verify so a certain data block whether complete process can regard abstractively whether element x of proof belongs to the process of data set S as, wherein x just representative want the data block verified.This process is done detailed being described below on the basis of three-party model:
1), the user sends an inquiry request to insincere server, whether inquiry data element x among data set S;
2), insincere server carries out corresponding query manipulation in this locality, answer Yes or the No that draws returned to the user.Also to return " evidence " that generates in the query script simultaneously;
3), the user is by " evidence " that insincere server returns, carries out a series of calculating, draws the eigenwert of data again;
4), the user is with the 3rd) (this eigenwert draws and passes to the user by trust data source calculated in advance to the eigenwert that obtains in the step with the data feature values in this locality, the user is pre-stored in this locality with it) compare, if identical then user accepts insincere server and returns next answer, otherwise, then refuse.
At the verify data structure Design, the researchist has had some valuable investigations.Merkle has proposed employing Merkle Hash tree and has set up the verify data structure.During with Merkle tree construction stored data sets S, the element among the S all is stored in the leaf of Hash tree T, and each node is stored a label value in tree.If node is leaf node, its label value is identical with the data of its storage; Otherwise its label value is calculated by anti-collision hash function by the label value of its child nodes.People such as Goodrich have proposed to adopt jumping list structure and commutative hash function to realize the verify data organization plan.The jumping table is a kind of data structure with randomness, and it adopts all data of storage of linked list in lowermost layer, and element is its probability temper collection of one deck down in the last layer chained list.People such as Tomassia combine tree and construct RSA tree with the unidirectional totalizer technology of RSA, it makes that by introducing parameter ε the branch number of the height of tree and tree all is constant, so its evidence size, search and the time complexity verified is O (1).
By existing methods is discovered, though the control of the time complexity of data manipulation is in O (1) on the RSA tree, but need to use complicated power modular arithmetic in the unidirectional totalizer technology that it adopts, its actual run time is also pessimistic, and the RSA tree is also dumb when data are inserted, and may cause the reconstruct of complicated structure.And all adopted simply and efficiently hash function in the verify data structural design based on Merkle Hash tree and jumping table, but the time complexity of the data manipulation on them all is O (logn), and the Merkle tree is not supported the insertion operation of data.
In verify data structure in the past, upgrade to support it is not very flexible for Data Dynamic always, and improve one's methods at the major part of data structure, its structure all is confined to the model of initial Merkle Hash tree, namely in leaf node, store data and an intermediate node authentication storage information, this structural design makes the work that improves data manipulation efficient run into bottleneck, can make it have the constant height though equally introduce parameter just like the design of RSA tree, but this design is in the storage environment of large-scale data, be easy to cause the reconstruct of structure, therefore also inapplicable.
Summary of the invention
The objective of the invention is to overcome the deficiencies in the prior art, the data integrity verification method based on SBT is provided in the storage of a kind of cloud, to improve the dirigibility that Data Dynamic upgrades, the storage overhead that reduces server, improve the efficient of data integrity checking.
For achieving the above object, based on the data integrity verification method of SBT, it is characterized in that in the cloud storage of the present invention, may further comprise the steps:
The piecemeal of (1), outsourcing data
Piecemeal will be carried out from the outsourcing data that the user receives in the trust data source, be about to the outsourcing data and be divided into n the data block with fixed size;
(2), SBT(Size Balanced Tree) the authenticated change of structure, obtain authentication structures
Be the full node storage tree T that foundation structure is set up with SBT, full node storage tree T has individual n node, wherein a data block in each node correspondence step (1);
Each node v among the full node storage tree T, all store three contents:
1), is stored in the data block D of this node
v
2), the digest value H of this node data
v=h (D
v), wherein h is the hash function that calculates digest value;
3), associating digest value H
Sum(v):
If a) node v is leaf node, then unite digest value H
Sum(v)=H
v
B) if node v is not leaf node, and have only left child nodes, then unite digest value H
Sum(v)=h (H
v, H
Sum(left[v])), left[v wherein] the left child nodes of representation node v, H
SumThe left child nodes left[v of (left[v]) representation node v] the associating digest value;
C) if node v is not leaf node, and have only right child nodes, then unite digest value H
Sum(v)=h (H
v, H
Sum(right[v])), right[v wherein] the right child nodes of representation node v, H
SumThe right child nodes left[v of (right[v]) representation node v] the associating digest value;
D) if node v is not leaf node, and have left and right sides child nodes concurrently, then unite digest value H
Sum(v)=h (H
v, H
Sum(left[v]),, H
Sum(right[v]));
The digest value Digest (T) of whole outsourcing data namely is the associating digest value of full node storage tree T root node;
(3), data integrity checking
The user at first stores the outsourcing data into the trust data source, and the trust data source calculates the digest value Digest (T) of outsourcing data according to step (1), (2), and digest value Digest (T) value of these outsourcing data is offered the user is stored in the locality;
Then, the storage of cloud storage service provider, i.e. insincere server in the three-party model are transferred to outsourcing data and authentication structures in the trust data source.
When the user sends the inquiry of member's data and arrives insincere server, if insincere server is not finding the respective objects node v that is storing target data block in full node storage tree T
0, then return the user who does not find and answer No, finish checking;
If insincere server finds the respective objects node v that is storing target data block in full node storage tree T
0, then recorded from destination node v
0To head node v
lSearch path path={v
0→ v
1→ ... → v
L-1→ v
l, v wherein
1..., v
L-1Be the node on the path of path; At this moment, insincere server is answered Yes and is returned corresponding evidence information Proof={ η, π to the user
1, π
2..., π
l, wherein, η is defined as:
1), if destination node v
0Be leaf node, then
2), if destination node v
0Not leaf node, then:
If a) destination node v
0Has only left child nodes, then
, left[v wherein
0] represent destination node v
0Left child nodes, H
Sum(left[v
0]) represent destination node v
0Left child nodes left[v
0] the associating digest value;
B) if destination node v
0Has only right child nodes, then
, right[v wherein
0] represent destination node v
0Right child nodes, H
Sum(right[v
0]) represent destination node v
0Right child nodes left[v
0] the associating digest value;
C) if destination node v
0Have left and right sides child nodes concurrently, then
For 1≤i≤l, π
iBe defined as follows:
1), if node v
I-1Be left child nodes, then:
, node v wherein
I-1Be node v
iLeft child nodes, with node v
iRight child nodes right[v
i] be the brotgher of node;
2), if node v
I-1Be right child nodes, then:
, node v wherein
I-1Be node v
iRight child nodes, with node v
iLeft child nodes left[v
i] be the brotgher of node;
When the user receives the evidence information Proof={ η that insincere server returns, π
1, π
2..., π
lAfter, carry out following proof procedure:
1), at first calculates
, wherein
In the element η of evidence information Proof;
If node v
0Be leaf node, then verify a=H
Sum(v
0) whether set up H
Sum(v
0) at the element π of evidence information Proof
1In;
If node v
0Be not leaf node:
If a) node v
0Have only left child nodes, then verify h (a, H
Sum(left[v
0]))=H
Sum(v
0) whether set up
B) if node v
0Have only right child nodes, then verify h (a, H
Sum(right[v
0]))=H
Sum(v
0) whether set up
C) if node v
0Have left and right sides child nodes concurrently, then verify h (a, H
Sum(left[v
0]), H
Sum(right[v
0]))=H
Sum(v
0) whether set up;
2), for π
i(1≤i＜l), if node v
I-1For left child nodes is then calculated
, if node v
I-1Be right child nodes, then calculate
, and verify this value and node v
iAssociating digest value H
Sum(v
i) whether equate H wherein
Sum(v
i) at π
I+1In;
3), for π
l, if node v
L-1For left child nodes is then calculated
, if node v
L-1For right child nodes is then calculated
, and will be worth with the user before the digest value Digest (T) of the outsourcing data of storing compare;
If above all checkings are all set up, prove that then the answer that insincere server returns is correct, think that namely the data block data of institute's inquiry are complete, otherwise the user thinks that then these data block data are distorted or forged.
Goal of the invention of the present invention is achieved in that
Data integrity verification method based on SBT in the cloud storage of the present invention is a kind of data integrity proof scheme based on the node size balanced tree.The well balanced property that the node size balanced tree has can better be controlled the height of tree, makes it level off to complete binary tree.And unbalanced tree is probably degenerated when constantly inserting new data, and the height of tree can't better controlled, causes the path from root node to a certain leafy node very long.Because the time complexity of Data Update and inquiry is all relevant with the height of tree on binary tree, therefore on unbalanced tree, the node size balanced tree has very big advantage in the efficient of data manipulation, and it can be held in the time dimension of data manipulation O (logn).The node size balanced tree has better flexibility in the Data Dynamic renewal process, and storage is not limited to only be stored in its leaf node during data in the node size balanced tree, and this can reduce the storage overhead of server to a certain extent.This scheme is suitable for the efficient verify data structure that large-scale data dynamically updates by the node size balanced tree being combined with hash function, designing, thereby improves the efficient of data integrity checking.
Description of drawings
Fig. 1 is the synoptic diagram of the three-party model of cloud storage;
Fig. 2 is based on the process flow diagram of the data integrity verification method of SBT in the cloud of the present invention storage;
Fig. 3 is that the present invention is a kind of instantiation synoptic diagram of full node storage tree that foundation structure is set up with SBT;
Fig. 4 is evidence Proof generative process figure;
Fig. 5 is that evidence Proof one generates example schematic;
Fig. 6 is data integrity proof procedure example schematic.
Embodiment
Below in conjunction with accompanying drawing the specific embodiment of the present invention is described, so that those skilled in the art understands the present invention better.What need point out especially is that in the following description, when perhaps the detailed description of known function and design can desalinate main contents of the present invention, these were described in here and will be left in the basket.
Fig. 2 is based on the process flow diagram of the data integrity verification method of SBT in the cloud of the present invention storage.
In the present embodiment, as shown in Figure 2, the data integrity verification method based on SBT in the cloud storage of the present invention comprises step S1～S3, the step of corresponding summary of the invention (1)～(3), and particular content is identical, does not repeat them here.
Fig. 3 is that the present invention is a kind of instantiation synoptic diagram of full node storage tree that foundation structure is set up with SBT.
In the present embodiment, piecemeal will be carried out from the outsourcing data that the user receives in the trust data source, be about to the outsourcing data and be divided into 6 data blocks with fixed size; Then, be the full node storage tree T that foundation structure is set up with SBT, full node storage tree T has 6 node, wherein corresponding a data block, i.e. node v of each node
N0～v
N5The corresponding data piece
, node v
N0Be root node.
Three contents of each node v storage of method according to step (2) obtain the authentication structures based on SBT as shown in Figure 3, wherein, and the associating digest value H of root node
Sum(v
N0) be the digest value Digest (T) of whole outsourcing data.
Fig. 4 is evidence information Proof generative process figure.
As shown in Figure 4, the generation of evidence information Proof at first generates η, generates π then
i, up to π
lTill the generation, namely i≤l is false then and is finished.Generative process in its content synchronization rapid (3) does not repeat them here.
In the present embodiment, the generation result of evidence information Proof wherein, needs the data block of checking to be as shown in Figure 5
, path={v
N4→ v
N1→ v
N0, i.e. v
N4=v
0, v
N1=v
1, v
N0=v
2, substitution step (3) generates, and obtains evidence information Proof={ η, π
1, π
2, value separately is:
Fig. 6 is data integrity proof procedure example schematic.
In the present embodiment, as shown in Figure 6, at first calculate checking
, namely
Whether set up, then to π
1Verify node v
I-1Be v
0Be v
N4, be right child nodes, then according to computing formula
, right
Verify; At last to π
lChecking, node v
L-1Be v
1Be v
N1, left child nodes is then according to computing formula
, right
Verify, if all set up, then prove data integrity, otherwise authentication failed proves that data are imperfect, is distorted or forges.
Although above the illustrative embodiment of the present invention is described; so that those skilled in the art understand the present invention; but should be clear; the invention is not restricted to the scope of embodiment; to those skilled in the art; as long as various variations appended claim limit and the spirit and scope of the present invention determined in, these variations are apparent, all utilize innovation and creation that the present invention conceives all at the row of protection.
Claims (1)
1. based on the data integrity verification method of SBT, it is characterized in that during a cloud is stored, may further comprise the steps:
The piecemeal of (1), outsourcing data
Piecemeal will be carried out from the outsourcing data that the user receives in the trust data source, be about to the outsourcing data and be divided into n the data block with fixed size;
(2), SBT(Size Balanced Tree) the authenticated change of structure, obtain authentication structures
Be the full node storage tree T that foundation structure is set up with SBT, full node storage tree T has individual n node, wherein a data block in each node correspondence step (1);
Each node v among the full node storage tree T, all store three contents:
1), is stored in the data block D of this node
v
2), the digest value H of this node data
v=h (D
v), wherein h is the hash function that calculates digest value;
3), associating digest value H
Sum(v):
If a) node v is leaf node, then unite digest value H
Sum(v)=H
v
B) if node v is not leaf node, and have only left child nodes, then unite digest value H
Sum(v)=h (H
v, H
Sum(left[v])), left[v wherein] the left child nodes of representation node v, H
SumThe left child nodes left[v of (left[v]) representation node v] the associating digest value;
C) if node v is not leaf node, and have only right child nodes, then unite digest value H
Sum(v)=h (H
v, H
Sum(right[v])), right[v wherein] the right child nodes of representation node v, H
SumThe right child nodes left[v of (right[v]) representation node v] the associating digest value;
D) if node v is not leaf node, and have left and right sides child nodes concurrently, then unite digest value H
Sum(v)=h (H
v, H
Sum(left[v]),, H
Sum(right[v]));
The digest value Digest (T) of whole outsourcing data namely is the associating digest value of full node storage tree T root node;
(3), data integrity checking
The user at first stores the outsourcing data into the trust data source, and the trust data source calculates the digest value Digest (T) of outsourcing data according to step (1), (2), and digest value Digest (T) value of these outsourcing data is offered the user is stored in the locality;
Then, the storage of cloud storage service provider, i.e. insincere server in the three-party model are transferred to outsourcing data and authentication structures in the trust data source.
When the user sends the inquiry of member's data and arrives insincere server, if insincere server is not finding the respective objects node v that is storing target data block in full node storage tree T
0, then return the user who does not find and answer No, finish checking;
If insincere server finds the respective objects node v that is storing target data block in full node storage tree T
0, then recorded from destination node v
0To head node v
lSearch path path={v
0→ v
1→ ... → v
L-1→ v
l, v wherein
1..., v
L-1Be the node on the path of path; At this moment, insincere server is answered Yes and is returned corresponding evidence information Proof={ η, π to the user
1, π
2..., π
l, wherein, η is defined as:
1), if destination node v
0Be leaf node, then
2), if destination node v
0Not leaf node, then:
If a) destination node v
0Has only left child nodes, then
, left[v wherein
0] represent destination node v
0Left child nodes, H
Sum(left[v
0]) represent destination node v
0Left child nodes left[v
0] the associating digest value;
B) if destination node v
0Has only right child nodes, then
, right[v wherein
0] represent destination node v
0Right child nodes, H
Sum(right[v
0]) represent destination node v
0Right child nodes left[v
0] the associating digest value;
C) if destination node v
0Have left and right sides child nodes concurrently, then
For 1≤i≤l, π
iBe defined as follows:
1), if node v
I-1Be left sibling, then:
, node v wherein
I-1Be node v
iLeft child nodes, with node v
iRight child nodes right[v
i] be the brotgher of node;
2), if node v
I-1Be right node, then:
, node v wherein
I-1Be node v
iRight child nodes, with node v
iLeft child nodes left[v
i] be the brotgher of node;
When the user receives the evidence information Proof={ η that insincere server returns, π
1, π
2..., π
lAfter, carry out following proof procedure:
1), at first calculates
, wherein
In the element η of evidence information Proof;
If node v
0Be leaf node, then verify a=H
Sum(v
0) whether set up H
Sum(v
0) at the element π of evidence information Proof
1In;
If node v
0Be not leaf node:
If a) node v
0Have only left child nodes, then verify h (a, H
Sum(left[v
0]))=H
Sum(v
0) whether set up
B) if node v
0Have only right child nodes, then verify h (a, H
Sum(right[v
0]))=H
Sum(v
0) whether set up
C) if node v
0Have left and right sides child nodes concurrently, then verify h (a, H
Sum(left[v
0]), H
Sum(right[v
0]))=H
Sum(v
0) whether set up;
2), for π
i(1≤i＜l), if node v
I-1For left sibling then calculates
, if node v
I-1For right node then calculates
, and verify this value and node v
iAssociating digest value H
Sum(v
i) whether equate H wherein
Sum(v
i) at π
I+1In;
3), for π
l, if node v
L-1For left sibling then calculates
, if node v
L-1For right node then calculates
, and will be worth with the user before the digest value Digest (T) of the outsourcing data of storing compare;
If above all checkings are all set up, prove that then the answer that insincere server returns is correct, think that namely the data block data of institute's inquiry are complete, otherwise the user thinks that then these data block data are distorted or forged.
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| CN112069286A (en) * | 2020-08-28 | 2020-12-11 | 喜大（上海）网络科技有限公司 | Dictionary tree parameter updating method, device, equipment and storage medium |
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| CN103716404A (en) * | 2013-12-31 | 2014-04-09 | 华南理工大学 | Remote data integrity authentication data structure in cloud environment and implement method thereof |
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| CN112069286B (en) * | 2020-08-28 | 2024-01-02 | 喜大（上海）网络科技有限公司 | Dictionary tree parameter updating method, device, equipment and storage medium |
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