Attribute-based encryption access tree attribute assignment method based on secret sharing and reversible embedding

Abstract

The invention discloses an attribute-based encryption access tree attribute assignment method based on secret sharing and reversible embedding, which belongs to the technical field of information security, and comprises the following steps: defining different access strategies by constructing an attribute tree; segmenting the secret to obtain sub-keys, and associating each sub-key with a leaf node of the attribute tree; when the user requests to access the secret, verifying whether the attribute of the user meets the access strategy or not, and if yes, obtaining a sub-key corresponding to the attribute of the user by the user; and recovering the sub-key through a secret sharing scheme to obtain decrypted data and access the decrypted data. According to the method, by constructing the complex attribute tree and embedding the path label, the problems of performance bottleneck and expandability are effectively solved, meanwhile, user privacy is protected, and the risk of trust single point failure is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of information security, and in particular relates to an attribute assignment method for an attribute-based encrypted access tree based on secret sharing and reversible embedding. Background Art

[0002] Attribute-Based Encryption (ABE) is an attribute-based encryption technology that implements fine-grained access control, allowing data owners to encrypt data based on user attributes, and the data can only be decrypted when the user has a specific combination of attributes. This encryption method provides a flexible and secure solution for data sharing and access control. As a public key encryption framework, ABE's encryption and decryption operations rely on user attributes rather than specific user identities. To implement a tree-like access structure for attribute encryption, it is generally necessary to first build a policy tree. The root node of the tree is generally the decryption key. According to the attribute policy, the leaf nodes of the policy tree represent the attribute set in the access structure, and different intermediate nodes represent predicates. Through a linear secret sharing scheme, each leaf node is given a vector containing a secret, that is, the secret corresponding to each attribute.

[0003] ABE can achieve more fine-grained access control, with high flexibility. It does not require a centralized trust agency, reducing the risk of single point failure of trust. At the same time, it can achieve encryption and decryption without revealing the user's identity. ABE is widely used in cloud storage, electronic medical records, and information sharing systems. Although ABE provides fine-grained access control, its algorithm is usually more complex than traditional encryption algorithms, so it may face performance bottlenecks in computing and storage. In addition, with the increase in attribute sets and the number of users, the scalability of the ABE system has also become a problem that needs to be solved. The main reason for these problems is the intersection between user tags, forming a complex network, which greatly increases the path complexity of attribute encryption and also increases the number of conflicts. If we can represent the same attribute with multiple nodes, we can form a good recursive tree structure, improve computing efficiency and reduce complexity.

[0004] The Shamir threshold scheme is a secret sharing scheme based on Lagrange interpolation polynomials. Its core idea is to use a secret S as a constant term of the polynomial, construct a t-1 degree polynomial, and divide the secret into n parts and give them to n participants respectively. In the key generation and distribution stage, the Shamir scheme generates subkeys by calculating the value of the polynomial at a specific point. This process is relatively direct and efficient. By setting different t values ​​(threshold values), the scheme can flexibly control the number of participants required to recover the secret. At the same time, the scheme is based on the security assumption of the discrete logarithm problem, so that any subset of less than t participants cannot recover the secret, and it is secure. Compared with the Shamir scheme, the Blakley scheme has a lower information rate, and any t subsecrets are independent of each other except for determining the intersection point. In terms of computing speed, since the Blakley scheme needs to process points and hyperplane equations in multidimensional space, its computational complexity may be slightly higher than that of the Shamir scheme, especially when there are more participants or higher dimensions. Linear secret sharing schemes (such as vector space secret sharing VSS) are another common secret sharing method. Such schemes usually have good information rate and flexibility, but the computational speed may vary depending on the specific implementation. Compared with Shamir's scheme, linear secret sharing schemes may require more computing resources in the key generation and distribution stages.

[0005] In the CP-ABE scheme originally proposed, the access policy is embedded in the data ciphertext in plain text. Anyone who obtains the data ciphertext can obtain the content of the access policy, regardless of whether they have the decryption permission. However, the access policy that completely exposes the data will lead to the leakage of sensitive information of the encryptor and the decryptor. Especially in the era of big data, people can use the leaked information to mine more private information. Therefore, it is necessary to hide the attribute information in the access policy to prevent privacy leakage. However, existing schemes have shortcomings, such as the inability to completely hide the attributes. Summary of the invention

[0006] In order to solve the above technical problems, the present invention proposes an attribute assignment method for attribute-based encrypted access tree based on secret sharing and reversible embedding to solve the problems existing in the above prior art.

[0007] To achieve the above object, the present invention provides an attribute-based encrypted access tree attribute assignment method based on secret sharing and reversible embedding, comprising the following steps:

[0008] Define different access strategies by building a property tree;

[0009] Split the secret to obtain subkeys, and associate each subkey with a leaf node of the attribute tree;

[0010] When a user requests access to a secret, verify whether the user's attributes satisfy the access policy, and if so, the user obtains a subkey corresponding to the user's attributes;

[0011] The subkey is recovered through a secret sharing scheme, and the decrypted data is obtained and accessed.

[0012] Preferably, the method for constructing the attribute tree includes:

[0013] Construct child nodes Node according to the embedding method until the number of constructed child nodes is greater than the number of strategies, complete the generation of all subtrees of the current node, then jump out of the child nodes to generate NodeList = Gen (n, t, f), put the new node into the child node set to be processed NodeList, pop up the first node of NodeList, if the strategy Strategy is (0,0), it is a leaf node, and then pop up the first node of NodeList until NodeList = = {}, the attribute tree construction is completed;

[0014] Where Gen(n,t,f) represents the child node generation function.

[0015] Preferably, the attribute tree includes a root node, an intermediate node and a leaf node, and the root node, the intermediate node and the leaf node are all constructed as Node;

[0016]

[0017] In the formula, Represents the concatenation of the previous and next strings, R = Bin (RandomDigital), where RandomDigital is Random sampling in, q is a large prime number, P represents the embedded information, and n represents the number of embedded valid bits.

[0018] Preferably, each node in the attribute tree selects a subkey generation function according to a policy, and the subkey generation function includes:

[0019] f(x)=S+a1×x+a2×x 2 +…+a n-1 × n-1 ;

[0020] f(x)=S+a1×x;

[0021] f(x)=S+a1×x+a2×x 2 +…+a t-1 × t-1 ;

[0022] In the formula, S represents secret, a1 represents satisfying a i ← RA random integer of GF(q)\{0}(i=1,2,…k-1)(q is a large prime number satisfying q≥u+1, u represents the number of people holding the key), and x represents the attribute value.

[0023] Preferably, the attribute assignment method further includes:

[0024] When leaf nodes with the same attribute are constructed at different levels and policy sets on the attribute tree, path labels are embedded in the user's attributes through reversible information hiding technology.

[0025] Preferably, the method for obtaining decrypted data comprises:

[0026] Assign policy content according to the corresponding label of the policy set, and then restore it layer by layer from bottom to top using the Lagrange interpolation method.

[0027] Preferably, the expression of the Lagrange interpolation method is:

[0028]

[0029] In the formula, k represents the threshold value, x j represents the attribute value of the jth user, x l Represents the attribute value of the lth user.

[0030] Compared with the prior art, the present invention has the following advantages and technical effects:

[0031] The present invention discloses an attribute-based encrypted access tree attribute assignment method based on secret sharing and reversible embedding, comprising the following steps: defining different access policies by constructing an attribute tree; splitting the secret to obtain subkeys, and associating each subkey with a leaf node of the attribute tree; when a user requests to access the secret, verifying whether the user's attributes meet the access policy, if so, the user obtains the subkey corresponding to the user's attributes; restoring the subkey through a secret sharing scheme, obtaining decrypted data and accessing it. The present invention effectively solves the performance bottleneck and scalability problems by constructing a complex attribute tree and embedding path labels, while protecting user privacy and reducing the risk of trust single point failure. This method allows data owners to encrypt and control data access based on user attributes rather than identities, improves computing efficiency, and enhances data security through policy hiding technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0033] Figure 1 is a flow chart of a method according to an embodiment of the present invention;

[0034] Figure 2 A schematic diagram of constructing a property tree according to an embodiment of the present invention;

[0035] Figure 3 It is an embedding process diagram of an embodiment of the present invention;

[0036] Figure 4 A schematic diagram of secret acquisition according to an embodiment of the present invention;

[0037] Figure 5 A schematic diagram of a logic AND operation according to an embodiment of the present invention;

[0038] Figure 6 A logical OR operation diagram of an embodiment of the present invention;

[0039] Figure 7 Schematic diagram of threshold calculation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0041] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0042] Embodiment 1

[0043] like Figure 1-7 As shown, this embodiment provides an attribute-based encrypted access tree attribute assignment method based on secret sharing and reversible embedding, including the following steps:

[0044] Define different access strategies by building a property tree;

[0045] Split the secret to obtain subkeys, and associate each subkey with a leaf node of the attribute tree;

[0046] When a user requests access to a secret, verify whether the user's attributes satisfy the access policy, and if so, the user obtains a subkey corresponding to the user's attributes;

[0047] The subkey is recovered through a secret sharing scheme, and the decrypted data is obtained and accessed.

[0048] Furthermore, the structure of the tree in this embodiment is as follows: Figure 2 , define each node (including root node, intermediate node, leaf node) as Node, where

[0049]

[0050] Each node selects a sub-key generation function f (selected from formulas (3), (4), and (5)) according to its own strategy Strategy(n,t), and assigns the attribute value x of the embedded information to the child node. i and subkey y i , the child node set is NodeList, and the child node generation function is:

[0051] NodeList=Gen(n,t,f) (2)

[0052] In the generation of NewNodeList, the node Node is constructed according to the embedding method until Condition: i ≥ n, and the constructed child node i is greater than the strategy number n, that is, after all subtrees of the current node are generated, the child node generation function formula (2) is jumped out, and the new node is placed in the child node set to be processed NodeList, and the first node of NodeList is popped out. If the strategy Strategy is (0,0), it is a leaf node, and the first node of NodeList is popped out again until NodeList == {}, then the attribute tree is constructed, and the child keys y of all intermediate nodes are deleted. i , only keep the subkeys of leaf nodes. The subkeys of leaf nodes y i and all attribute values ​​x of the nodes on the path from the root node to the leaf node i Together we generate a property secret p i =(y,x1,x2,…,x k )(k is the leaf node depth), thereby constructing the attribute set (p1, p2, ... p i )(i=1,…,d), d is the total number of leaf nodes.

[0053] Furthermore, the key technology for realizing the process of constructing attribute paths based on secret sharing technology is to realize the logical relationship between different attributes. The attributes mainly include the following three logical relationships in the process of constructing the path.

[0054] Logical AND operation Figure 5 , is to select a polynomial according to the strategy (n,n)

[0055] f(x)=S+a1×x+a2×x 2 +…+a n-1 × n-1 (3)

[0056] a i ← R GF(q)\{0}(i=1,2,…k-1), q is a large prime number satisfying q≥u+1.

[0057] Calculate (x1,y1)(x2,y2)...(x n ,y n ), S is the secret. Since this is a polynomial, we need n points (x1,y1)(x2,y2)...(x n ,y n ) is constructed by the Lagrange interpolation formula The secret

[0058] Logical OR operation Figure 6 , is to select a first-order polynomial according to the strategy (n,1)

[0059] f(x)=S+a1×x (4)

[0060] a1← R GF(q)\{0}(i=1), q is a large prime number satisfying q≥u+1.

[0061] Select n different non-zero integers x1, x2, ... x n As the identifier of the share, S is the secret (subkey). By calculating the corresponding y as the secret information of the corresponding node through y=f(x), a total of n shares are generated. The threshold is 1, that is, anyone who holds the secret information can construct it through the Lagrange interpolation formula The secret

[0062] Threshold operation Figure 7 , is to select a polynomial according to the strategy (n, t), where n>t

[0063] f(x)=S+a1×x+a2×x 2 +…+a t-1 × t-1 (5)

[0064] a i ← R GF(q)\{0}(i=1,2,…t-1), q is a large prime number satisfying q≥u+1.

[0065] Calculate (x1,y1)(x2,y2)…(x) from y=f(x) n ,y n ), S is the secret (subkey). This polynomial has only t-1 unknowns, so only t points are needed, namely (x1, y1)(x2, y2)…(x t ,y t ) can be constructed by the Lagrange interpolation formula The secret

[0066] Further, the secret splitting method is as follows:

[0067] The secret s is divided into n unrelated parts, each of which is called a sub-key and is held by a participant. The secret s can only be recovered when at least k sub-keys are held. This scheme is called the (k,n)-secret splitting threshold scheme, where k is called the threshold value of the scheme. The Shamir threshold scheme is a threshold secret splitting scheme based on the Lagrange interpolation formula.

[0068] In this secret sharing scheme, mathematical symbols are used to accurately describe the whole process. First, some basic mathematical symbols and concepts are defined:

[0069] Secret: Let S be the secret.

[0070] Large prime number: Choose a large prime number q.

[0071] Number of subkey holders: Let u be the number of subkey holders.

[0072] Threshold value: Let k be the threshold value, that is, at least k subkeys are needed to recover the secret S.

[0073] Polynomial coefficients: k-1 coefficients a1…a k-1 The selection satisfies a i ← R GF(q)\{0}(i=1,2,…k-1), q is a large prime number satisfying q≥u+1.

[0074] Polynomial: Define the polynomial f(x) = S + a1×x + a2×x 2 +…+a k-1 × k-1 , where S is a constant term.

[0075] Destroy the polynomial: After all subkeys are distributed, destroy the polynomial f(x) and its coefficients a1…a k-1 and the constant term S.

[0076] Now, we can use mathematical notation to represent each user P i The subkeys held are:

[0077] f(x)=(S+a1×x+a2×x 2 +…+a k-1 × k-1 ) mod q and a1, a2…a k-1 , S∈Z q (6)

[0078] Furthermore, a single path can be realized by combining logic gates, which construct different paths under the tree structure. However, when attributes overlap, the same attribute may exist on different policy paths, and the attribute verification cannot be distinguished, resulting in the failure of legal attribute verification. In real life, we may encounter the same attribute for different individuals, which means very different things. For a company's planning documents, only managers and above can view them, or managers and above can view them in the planning department of a subsidiary. Although the attribute "above managers" is the same for the head office and the subsidiary, it has different importance. In the existing scheme, the same path is used, but other attributes are selected for differentiation, but this requires finding other differentiation labels. Therefore, this paper believes that for this attribute, different weights can be given to the two same attributes, that is, the same attribute selects different paths to form a distinction, and no new attributes are needed to mark it. Therefore, the leaf nodes of the same attribute can be constructed at different levels and policy sets on the attribute tree, and different powers can be given through different logical operation policy sets, so as to achieve differentiation of attribute weights in different environments.

[0079] In reality, there are also situations where the same individual has multiple sets of keys. Individuals choose different keys for uploading and decryption based on actual conditions. A laboratory safe requires two people to open. A professor holds two sets of keys, both of which contain the same attribute "professor". These two sets of keys correspond to two plans for opening the laboratory safe. One is to use the first key to open the safe together with the associate professor, and the other is to use the second key to open the safe together with the responsible student. In these two plans, the same attribute plays different roles, so a suitable method is needed to express the power of the attribute.

[0080] The traditional attribute encryption strategy tree lacks an efficient method for processing complex paths. This algorithm proposes an attribute value marking method based on reversible information hiding technology, which can reversibly embed path label information in the attribute ciphertext, and is used to mark when multiple paths have the same attribute. The reversibility of the ciphertext domain reversible information hiding technology ensures that the attribute value after embedding the label can be normally substituted into the secret reconstruction algorithm to recover the ABE key. At the same time, the label information can be accurately extracted from the attribute ciphertext carrying the label, and the correct path is used for attribute policy verification. The main symbols and their meanings are shown in Table 1.

[0081] Table 1

[0082]

[0083]

[0084] Information hiding technology takes advantage of the redundancy of transmitted information and the partial delay in the human perception system, embeds secret information into the carrier information through a specific algorithm, and does not affect the sensory perception of the carrier information, sensory experience and use value, thus achieving "imperceptible" transmission of secret information. If the carrier can be completely restored to its original state, that is, distortion-free recovery, it is called reversible information hiding (RDH). Reversible information hiding mainly means that in the process of embedding hidden information, the carrier information may be damaged to a certain extent, but under normal circumstances, when transmitting secret information, the legitimate receiver can extract the hidden information through the key, and can complete the repair of the distortion of the carrier information, thereby achieving accurate recovery of the original carrier. Through the Shamir threshold scheme, we know that in

[0085]

[0086] a i ← R GF(q)\{0}(i=1,2,…k-1), q is a large prime number satisfying q≥u+1.

[0087] Generate subkey y i During the process, the attribute value x i is a random number.

[0088] This embodiment defines in Represents the concatenation of the previous and next strings, R = Bin (RandomDigital), where RandomDigital is The embedded information P = Bin(i,n) is a n-bit binary number used to represent the subtree position number i. Therefore, it is used to construct y i x i Carry label information randomly.

[0089] Further, the extraction process is:

[0090] All secrets held by each user are Property(p1,p2…p i )(i=1,2…), where p i is the attribute secret. Its specific composition is p i =(y,x1,x2,…,x k )(k is the leaf node depth).

[0091] The function for extracting the embedding label is l i =Extract(n,x i ), where n is the number of digits, x iis the attribute value, and the specific process is to obtain Bin(x i ) after n digits, through l i =Int(x i ) to get the label.

[0092] So for each attribute (x1,x2,…,x k ) can generate subtree label L through (l1=Extract(n,x1),l2=Extract(n,x2)…). After extraction, the user attribute label set is LabelList(L1,L2…), where L i Indicates the attribute tag to be obtained.

[0093] Users who want to obtain secret information jointly hand over their own attribute sets, reconstruct the attribute tree through all label sets, and use StragetyList (Stragety1, Stragety2...) to assign values ​​to corresponding node strategies.

[0094] After constructing the tree, we start from the bottom leaf node of the tree and check whether the number of child nodes of its parent node reaches its Strategy(n,t). If the condition is met, we can construct it through Lagrange interpolation formula (7): The secret of the child This method is iterated until the root node secret information S is recovered.

[0095] Lagrange interpolation formula: Known Function value at k different points The k-1 interpolation polynomial can be constructed as

[0096]

[0097] Use k points (x1,y1)(x2,y2)...(x k ,y k ) is constructed by the Lagrange interpolation formula To calculate the secret, just substitute x=0 to get the secret S.

[0098] The specific implementation is as follows:

[0099] "Smart Insight Technology" is a leading market research and consulting company that focuses on providing clients with in-depth market analysis and strategic advice. The company has a huge database that contains many sensitive and valuable market analysis reports. In order to protect these reports from being accessed by unauthorized personnel, the company uses advanced attribute-based encryption (ABE) technology to ensure data security.

[0100] Recently, "Smart Insight Technology" completed an encrypted market analysis report on "Future Automotive Technology Trends". This report covers key data and insights in multiple cutting-edge fields such as electric vehicles, autonomous driving, and vehicle networking. In order to ensure that this report is only accessed by people with relevant permissions, the company has set up a complex ABE access policy.

[0101] There are now 4 people involved who want to access confidential information. Their details are as follows:

[0102] User A: Senior Project Manager in Market Research Department

[0103] Attributes: Project = P1 (Future Automotive Technology Trend), Safety Level = High, Years of Service = 8 years

[0104] Role description: As the project leader, A has a high demand for the content of the report and is directly involved in the report preparation process.

[0105] User B: A member of the senior analyst team

[0106] Attributes: Position = Senior Analyst, Years of Experience = 5 years

[0107] Role Description: Although B has a short working experience, due to his position as a senior analyst, he is often required to analyze similar reports to support decision making.

[0108] User C: External partner, data analysis expert

[0109] Attributes: Project = P1 (future automotive technology trends), data analysis skills

[0110] Role description: C is invited as an external expert to participate in the data analysis of a specific project and also needs to access the "Future Automotive Technology Trends" report.

[0111] User D: Sales Manager of the Sales Department

[0112] Attributes: Department = Sales, Years of Experience = 12 years

[0113] Role Description: Although D has extensive sales experience, he has no direct connection with the content of the market research department's reports and does not have sufficient authority.

[0114] The property tree is constructed as follows:

[0115] According to the requirements, first pass the secret information S to the root node, and at the same time pass the policy set {"X":(5,3),"X_0":(0,0),"X_1":(3,2),"X_1_0":(0,0),"X_1_1":(0,0),"X_1_2":(0,0),"X_2":(0,0),"X_3":(2,1),"X_3_0":(2,2),"X_3_1":(0,0),"X_3_0_0":(0,0),"X_3_0_1":(0,0)} according to the situation. Construct the Node node according to formula (1), update its policy, and assign the corresponding attribute value x of the embedded information i and subkey y i , according to the needs, iteratively generate new nodes, and finally generate an attribute tree that meets the needs. In the end, various authorized users will obtain the secrets of the corresponding leaf nodes and the attribute value set corresponding to each secret (that is, the attribute value x on all nodes from the root node to the sub-leaf). For example, the node with the node label X_3_1 will obtain the secret 68182140 and the attribute value set [8625,2739], while the node with the node label X_2 will obtain the secret 45100650 and the attribute value set

[9762] .

[0116] The information hiding reversible embedding tag method is as follows:

[0117] The secret representing attribute A is {'X_0_0':[472052214,6897,9056], 'X_3_0_0':[48472694,2739,928,4160]}. The secret is a dictionary. The key of the dictionary refers to the label of the leaf node, which is also the mark used to reconstruct the tree node later. The value of the dictionary is a list. The first element of the list is the secret (y) of the leaf node, and the second value of the list is all the x values ​​from the node to the root node. From the analysis of the results, the result must store the labels of the leaf nodes. At the same time, there is redundancy in multiple x values. From the Shamir threshold scheme, we can know that the x held by each node is a random number generated within a certain range. Therefore, we try to construct a special random number that can also be used to mark the relative position of the tree nodes while satisfying randomness. Our labels mark the node positions according to a structure similar to the Huffman tree. Therefore, we can try to mark the child nodes before generating the random tree. We can mark them in binary. Assuming that we use (bit_num is 4), we can represent 16 child nodes, ensuring that the last four bits of the binary random number of each node correspond to (0000000100100011010001010110011110001001101010111100110111101111). Each time the tree generates a child node, it passes the condition to the random number x in the Shamir algorithm until the condition is met, and then constructs a new child node.

[0118] After optimizing the output secret, we can get the secret representing attribute A as [[472052214,6897,9056],[48472694,2739,928,4160]]. The secret directly embeds the information into the attribute value x of the secret. When recovering, we first recover the label. For example, for the second secret, we can get the last four bits of 2739,928,4160 as '0011', '0000', '0000', so the label corresponding to the second secret should be X_3_0_0. Through the redundancy of x and the correspondence with the layer, the label information is put into x, thereby reducing the storage and transmission costs.

[0119] The secret acquisition method is as follows:

[0120] User A holds the secret [472052214,6897,9056][36934492,6897,2993], user B holds the secret [68182140,2739,8625], user C holds the secret [48472694,2739,928,4160][72699292,2739,928,7537], and user D holds the secret [45100650,9762]. When user A, user C, and user D are ready to review the report together, they submit the secret information they hold together.

[0121] When the secret holders upload the secrets at the same time, the corresponding label set is first generated according to the secret information Property of each secret holder through L=(l1=Extract(n,x1),l2=Extract(n,x2)…), and the root node label is X. Taking user A as an example, the first digit 472052214 is the secret y held by user A in the first attribute, and the last four digits of 6897 are 0001 in binary, which is 1 in decimal, and the last four digits of 9056 are 0000 in binary, which is 0 in decimal. Therefore, after recovery, the label of user A’s first attribute is X_1_0. Similarly, we can know that the label of user A’s second attribute is X_1_2. Similarly, we know that the corresponding labels of user B, user C, and user D are X_3_1, X_3_0_0 and X_3_0_1, X_2. Therefore, according to the label information, we create Node nodes layer by layer, and pass in the attribute value x and secret y to construct the attribute tree. Then, according to the corresponding label of the policy set, we assign the policy content, and then restore it layer by layer from bottom to top using the Lagrange interpolation method. For example, the policy of node X_1 is (3,2), so the leaf nodes X_1_0 and X_2_1 are connected. _1_2, satisfies the strategy, and can obtain the secret y value of X_1 as 31864350, while the node X_3_0 strategy is (2,2), so X_3_0 can recover the secret y as 18628854 by X_3_0 and X_3_1, and the node X_3 strategy is (2,1), so X_3 can be recovered by X_3_0, and the root node strategy is (5,3), now there are X_0, X_1, X_3, so the root node secret can be recovered together as 210.

[0122] Through examples, it can be seen that this method allows data owners to encrypt and control data access based on user attributes rather than identities, improves computing efficiency, and enhances data security through policy hiding technology.

[0123] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for assigning attribute values ​​to attribute-based encrypted access trees based on secret sharing and reversible embedding, characterized in that: The following steps are involved: Define different access strategies by building a property tree; Split the secret to obtain subkeys, and associate each subkey with a leaf node of the attribute tree; When a user requests access to a secret, verify whether the user's attributes satisfy the access policy, and if so, the user obtains a subkey corresponding to the user's attributes; The subkey is recovered through a secret sharing scheme, and the decrypted data is obtained and accessed.

2. The attribute assignment method of attribute-based encrypted access tree based on secret sharing and reversible embedding according to claim 1 is characterized in that: The method for constructing the attribute tree comprises: Construct child nodes Node according to the embedding method until the number of constructed child nodes is greater than the number of strategies, complete the generation of all subtrees of the current node, then jump out of the child nodes to generate NodeList = Gen (n, t, f), put the new node into the child node set to be processed NodeList, pop up the first node of NodeList, if the strategy Strategy is (0,0), it is a leaf node, and then pop up the first node of NodeList until NodeList = = {}, the attribute tree construction is completed; Where Gen(n,t,f) represents the child node generation function.

3. The attribute assignment method of attribute-based encrypted access tree based on secret sharing and reversible embedding according to claim 2 is characterized in that: The attribute tree includes a root node, an intermediate node and a leaf node, and the root node, the intermediate node and the leaf node are all constructed as Node; In the formula, Represents the concatenation of the previous and next strings, R = Bin (RandomDigital), where RandomDigital is Random sampling in, q is a large prime number, P represents the embedded information, and n represents the number of embedded valid bits.

4. The attribute assignment method of attribute-based encrypted access tree based on secret sharing and reversible embedding according to claim 3 is characterized in that: Each node in the attribute tree selects a subkey generation function according to a policy, and the subkey generation function includes: f(x)=S+a1×x+a2×x 2 +…+a n-1 ×x n-1 ; f(x)=S+a1×x; f(x)=S+a1×x+a2×x 2 +…+a t-1 ×x t-1 ; In the formula, S represents secret, a1 represents satisfying a i ← R A random integer of GF(q)\{0}(i=1,2,…k-1), where q is a large prime number satisfying q≥u+1, u represents the number of key holders, and x represents the attribute value.

5. The attribute assignment method of attribute-based encrypted access tree based on secret sharing and reversible embedding according to claim 1 is characterized in that: The attribute assignment method further includes: When leaf nodes with the same attribute are constructed at different levels and policy sets on the attribute tree, path labels are embedded in the user's attributes through reversible information hiding technology.

6. The attribute assignment method of attribute-based encrypted access tree based on secret sharing and reversible embedding according to claim 1 is characterized in that: Methods to obtain decrypted data include: Assign policy content according to the corresponding label of the policy set, and then restore it layer by layer from bottom to top using the Lagrange interpolation method.

7. The attribute assignment method of attribute-based encrypted access tree based on secret sharing and reversible embedding according to claim 6 is characterized in that: The expression of Lagrange interpolation method is: In the formula, k represents the threshold value, x j represents the attribute value of the jth user, x l Represents the attribute value of the lth user.

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