CN117972795A - Secure retrieval method and device for secret space keywords based on exclusive or filter - Google Patents

Abstract

The invention belongs to the technical field of data security, and particularly relates to a secure retrieval method and device for a secret space keyword based on an exclusive or filter. The method comprises the following steps: the data owner end builds a security tree index based on the security exclusive OR filter and the geographic hash code, encrypts the space text data set by using a secret key, and uploads the security tree index and the encrypted space text data set to the cloud server end; giving a query by a user terminal, generating a trapdoor based on the query, and uploading the trapdoor to a cloud server terminal; the cloud server searches the target space object in the security tree index according to the trapdoor, and returns a result set formed by ciphertext of the target space object to the user side; and the user side inquires complete ciphertext information according to the result set, and decrypts the ciphertext information by using the key to obtain plaintext information. The invention realizes the return of the space text data information which the user expects to inquire in a certain space range, provides privacy protection and improves the accuracy of the inquiry result.

Description

Method and device for secure retrieval of keywords in secret space based on XOR filter

Technical Field

The present invention belongs to the technical field of data security, and more specifically, relates to a method and device for secure retrieval of keywords in a secret space based on an XOR filter.

Background technique

With the popularity of mobile Internet and GPS devices, spatial text data is widely used in various services such as location-based services and personalized query services. There is a typical query in spatial text databases, namely Boolean Range Query, which takes into account spatial geometric range and text keywords. It can give a query range and a set of text keywords of spatial objects, and users can retrieve all spatial objects that meet the requirements from the spatial text dataset.

More and more data owners choose to outsource their data services to cloud computing for cost savings and service flexibility. However, the data and services outsourced to cloud computing need to be privacy protected. Currently, many spatial keyword query solutions that support privacy protection use Bloom filters for encoding when designing indexes.

Chinese patent document CN117349878A discloses a privacy protection method for keyword search and multi-dimensional range query in smart medical care. Medical institutions index their medical data through the index tree R-tree and outsource it to the cloud server to provide data query services. The dual cloud servers have powerful computing power and storage space to store outsourced encrypted data and jointly provide multi-dimensional range query services for authorized users. Authorized users need to perform keyword search and multi-dimensional range query entities. When the authorized user registers in the system, the system will send the identity ID and hash message authentication code to the authorized user for privacy calculation of the query data later. When encoding the multi-dimensional data, the Bloom filter BF is used to encode it. This method ensures the security and reliability of the multi-dimensional range query service provided by the cloud server, while meeting the query requirements of the diversity of multi-dimensional range queries.

Chinese patent document CN111935141A discloses a single inadvertent anti-link query system and method for confidential data, which is applied to a network environment composed of multiple data upload modules, multiple data request modules and a data cloud storage module; the data upload module calculates the security tree index of the data, and uploads it to the data cloud storage module together with the encrypted data and shares the key with some data upload modules; the data request module generates a query token, submits the token to the data cloud storage module, waits for the data to be sent back and decrypts the matching data, otherwise it waits for valid data; the data cloud storage module receives the security tree index and encrypted data from the data upload module, receives the token from the data request module, uses the token to search the security tree index and returns the query result, otherwise it returns a null value; wherein, the data uploader initializes an empty indistinguishable Bloom filter Bn, and sets so that the kth prefix prk in a set of prefixes Sn and a random number rn are embedded in the Bloom filter Bn, and the data uploader submits the security tree index composed of the Bloom filter Bn and the random number rn and the encrypted data to the data cloud storage party. The method can protect the privacy of the data requester from being infringed by the untrusted data cloud storage party.

However, Bloom filters need to store the results of multiple hash functions, which takes up a lot of space and has a high misjudgment rate, which may lead to inaccurate query results.

Summary of the invention

The present invention aims to overcome at least one defect of the above-mentioned prior art and provide a dense spatial keyword security retrieval method based on XOR filter, which is used to return the spatial text data information that the user expects to query within a certain spatial range and provide privacy protection, while improving the accuracy of the query results.

The invention also discloses a device loaded with a secret space keyword security retrieval method based on an XOR filter.

The detailed technical scheme of the present invention is as follows:

A method for secure retrieval of keywords in a secret space based on an XOR filter, the method comprising:

S1. The data owner constructs a secure XOR filter and builds a secure tree index based on the secure XOR filter and geo-hash encoding, using the key Encrypting the spatial text data set, and uploading the security tree index and the encrypted spatial text data set to the cloud server;

S2. User-side query , based on the query/> Generate a trapdoor/> , and the trapdoor Upload to the cloud server, where the query/> ,/> Indicates the location information of the query point, /> Indicates query keyword information, /> Indicates the spatial range of the query point;

S3, the cloud server side according to the trap door Search the target space object in the security tree index/> , and will be represented by the target space object/> The ciphertext/> The result set is composed of Return to the user end;

S4: The user terminal determines the result set Query complete ciphertext information/> , and use the key The ciphertext information/> Decrypt and get the plaintext information.

Preferably, according to the present invention, in step S1, constructing a secure XOR filter specifically includes:

S10, will gather The elements in are mapped to the safe XOR filter /> In, we get:

(2);

In formula (2), For the collection/> Security XOR filter, /> is an XOR filter, /> is a random number;

S11. Gather The elements in are added to the array in sequence /> In this case, each element Generate three sets of hash functions respectively/> 、/> and/> , based on the hash function/> 、/> and/> , calculate the element/> The corresponding three hash values are: 、/> and/> ; where /> ,/> Represents a collection /> length;

S12, based on each element The three hash values of /> 、/> and/> , the element /> Put into array /> At the corresponding position, the array /> Iterate to find the list containing only one element/> Position, and initialize a queue, the element/> Subscript /> Join the queue;

S13, taking out the stored index from the head of the queue and from the array /> Get the subscript Corresponding elements/> , and then use/> The form is recorded into a stack, and at the same time from the array /> Remove elements from /> , when the array /> It appears again in the same directory containing only one element /> , place the element /> Subscript /> Add to the queue until the array /> No more elements appear at the position of /> , and then continue to take out the stored indexes from the queue in turn/> , and repeat the above steps until the queue is empty;

S14. Create an array A new array of the same length is created, and the initial values of the new array are all filled with random values, and the records are taken out one by one from the top of the stack. , calculation element/> /> Identify the value and put the /> The flag value is updated to the security XOR filter /> middle;

S15. Find each element The three hash values of /> 、/> and/> In and its subscript/> If the two hash values are inconsistent, get the secure XOR filter /> The two hash values are used as subscripts in the The identification value is XORed and finally in the security XOR filter/> Update the XOR operation result in .

Preferably, according to the present invention, in step S1, the expression for constructing the security tree index is:

(3);

In formula (3), is a safe tree index,/> It is spatial text data;

The construction of a secure tree index based on a secure XOR filter and a geographic hash code specifically includes:

S16, using the random character distribution method, according to the geographic hash code of the spatial text data, the spatial object is Generate leaf nodes in the form of and construct a tree index of plain text, where, /> A unique identifier representing a spatial object. A cluster of prefix codes representing the geohash codes of spatial objects. A set of keywords representing spatial objects;

S17, encrypt the constructed tree index of the plaintext, and use a pseudo-random counter in the non-leaf node Generate a pseudo-random number seed/> , and then use the pseudo-random number seed/> Generated by /> The assigned character set corresponds to /> value and map it to the secure XOR filter /> In Chinese, that is:

(4);

In formula (4), is a safe XOR filter for non-leaf nodes,/> is an XOR filter, Indicates the character set corresponding to /> value;

In the leaf node, use the key For spatial objects/> Encrypt and get the space object/> The ciphertext , using a pseudo-random number seed/> The prefix encoding cluster of geo-hashed codes/> All prefix codes included generate corresponding /> value, and all generated /> Values are mapped to safe XOR filters /> In Chinese, that is:

(5);

In formula (5), A secure XOR filter for prefix encoding clusters, /> is an XOR filter, /> Prefix code cluster representing geographic hash code/> All prefix codes included correspond to/> value;

And, in the leaf nodes, use the pseudo-random number seed Set keyword /> All keywords in the above code generate corresponding /> Value, and mapped to the security XOR filter /> In Chinese, that is:

(6);

In formula (6), A safe XOR filter for keywords, /> is an XOR filter, /> Indicates a keyword set/> All keywords in the corresponding /> value.

According to a preferred embodiment of the present invention, in step S1, the key is used Encrypt the spatial text dataset, specifically:

(7);

In formula (7), is the encrypted spatial text dataset, /> It is a spatial text dataset, including spatial data and text data./> is the key.

According to a preferred embodiment of the present invention, in step S2, based on the query Generate a trapdoor/> ,Specifically:

(8);

In formula (8), For trapdoor, /> Indicates the location information of the query point, /> Indicates query keyword information, /> Indicates the spatial range of the query point;

Among them, for the location information of the query point , converting the query coordinates into geographic hash codes and sparsely according to the given spatial range/> , calculate the corresponding prefix code/> , using a pseudo-random number seed/> Calculate the prefix code/> Its own/> Value/> And prefix encoding/> For each character in /> Value/> :

(9);

In formula (9), Encode the prefix /> Its own/> Value, /> Indicates prefix encoding Middle/> Characters/> Value, /> Indicates prefix code/> For each character in /> A collection of values, /> Indicates prefix code/> The character length of

For query keyword information , using a pseudo-random number seed/> Calculate the keyword set separately/> All keywords in /> Value, expressed as /> :

(10);

In formula (10), Indicates a keyword set/> All keywords in /> A collection of values, Indicates a keyword set/> Middle/> Keywords/> Value, /> Represents a keyword set The number of keywords in .

According to a preferred embodiment of the present invention, in step S3, the result set The expression is:

(11);

In formula (11), Indicates a trapdoor, /> Represents a safe tree index;

The cloud server end according to the trap door Searching for a target spatial object in the secure tree index , specifically including:

S31, traversing the prefix code For each character in /> Value/> The collection of components /> , search the security tree index for the /> Value/> Existing security XOR filters/> The corresponding non-leaf nodes to determine the search range;

S32, find all leaf nodes within the search range, and determine the prefix code in each leaf node Is it in the security XOR filter/> If it is in, continue to judge its keyword set/> Are all keywords in the security XOR filter/> If so, the spatial object stored in the leaf node is determined as the target spatial object/> , and the target space object/> The ciphertext/> Add result set /> middle.

According to the preferred embodiment of the present invention, in step S4, a key is used The ciphertext information/> Decryption, specifically:

(12);

In formula (12), is the plaintext information obtained after decryption,/> Indicates the complete ciphertext information found according to the result set,/> is the key.

In another aspect of the present invention, a device for implementing a method for secure keyword retrieval in a secret space based on an XOR filter is provided, the device comprising a data owner end, a user end, and a cloud server end, wherein:

The data owner is used to construct a secure XOR filter and to construct a secure tree index based on the secure XOR filter and the geographic hash code, using the key Encrypting the spatial text data set, and uploading the security tree index and the encrypted spatial text data set to the cloud server;

The client is used to give a query , based on the query/> Generate a trapdoor/> , and the trapdoor Upload to the cloud server; and use it according to the result set/> Query complete ciphertext information/> , and use the key /> The ciphertext information/> Decrypt and obtain the plaintext information;

The cloud server is used to Search the target space object in the security tree index/> , and will be represented by the target space object/> The ciphertext/> The result set is composed of Return to the user.

In another aspect of the present invention, there is also provided an electronic device, comprising:

at least one processor; and

A memory storing instructions, which, when executed by the at least one processor, enables the at least one processor to execute the encrypted space keyword security retrieval method based on XOR filter as described above.

In another aspect of the present invention, a machine-readable storage medium is provided, which stores executable instructions, and when the instructions are executed, the machine executes the encrypted space keyword security retrieval method based on XOR filter as described above.

Compared with the prior art, the present invention has the following beneficial effects:

(1) The present invention provides a method for secure retrieval of keywords in a dense space based on an XOR filter, which combines a secure XOR filter and a geographic hash code to construct a secure tree index, and uploads it to a cloud server, so that the cloud server can query spatial objects with higher accuracy and less memory usage during query processing.

(2) In the present invention, the user end can use the result set returned by the cloud server end to Query complete ciphertext information , and use the key /> For this ciphertext information/> Decryption is performed to obtain plaintext information, thereby completing the query of spatial keywords. This process enables efficient and accurate retrieval of spatial objects that meet the user's query conditions on the cloud server side without leaking any information, ensuring data privacy and achieving efficient search while ensuring strong security.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is an execution flow chart of the method for secure keyword retrieval in a secret space based on an XOR filter according to the present invention.

FIG2 is a comparison diagram of the misjudgment rates of the XOR filter and the Bloom filter in Example 1 of the present invention as the amount of inserted data increases at the same filter length.

FIG. 3 is a time chart of index generation in Embodiment 1 of the present invention.

Detailed ways

The present disclosure is further described below in conjunction with the accompanying drawings and embodiments.

It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present disclosure belongs.

It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and/or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and/or combinations thereof.

In the absence of conflict, the embodiments in the present disclosure and the features in the embodiments may be combined with each other.

Embodiment 1,

Referring to FIG. 1 , this embodiment provides a method for secure keyword retrieval in a secret space based on an XOR filter, the method comprising:

S1. The data owner constructs a secure XOR filter and builds a secure tree index based on the secure XOR filter and geo-hash encoding, using the key The spatial text data set is encrypted, and the security tree index and the encrypted spatial text data set are uploaded to the cloud server.

In this embodiment, the key The data owner uses security parameters/> Generated, the key /> It is used to encrypt spatial text data. The key generation is expressed as follows:

(1).

XOR filter is a data structure used to efficiently check whether an element exists in a set, and is usually used in high-performance data storage and retrieval systems. The design of XOR filter is inspired by Bloom filter, but it shows higher accuracy and lower memory usage in some aspects. Compared with Bloom filter, XOR filter is superior in terms of false positive rate and space efficiency. In this embodiment, in the XOR filter construction stage, all the values of the array are filled with random numbers when it is initialized, which can enhance the security of the XOR filter.

In this embodiment, in step S1, constructing a secure XOR filter specifically includes:

S10, will gather The elements in are mapped to the safe XOR filter /> In this case, we can get:

(2);

In formula (2), For the collection/> Security XOR filter, /> is an XOR filter, /> Is a random number.

S11. Building a secure XOR filter When , first set the collection /> The elements in are added to the array in sequence /> In this case, each element Generate three sets of hash functions respectively/> 、/> and/> , based on the three sets of hash functions generated/> 、/> and/> , calculate the element/> The corresponding three hash values are: 、/> and/> ; where /> ,/> Represents a collection /> length.

Here, using three hash functions can minimize the number of memory accesses required to achieve space advantage.

S12. Then, according to each element The three hash values of /> 、/> and/> , the element /> Put into array /> At the corresponding position, the array /> Iterate to find the list containing only one element/> Position, and initialize a queue, the element/> Subscript /> Join the queue.

S13, then, take out the stored index from the head of the queue and from the array /> Get the subscript in/> Corresponding elements/> , and then use/> The form is recorded into a stack, and at the same time from the array /> Remove elements from /> ; When array /> It appears again in the same directory containing only one element /> , place the element /> Subscript Add to the queue until the array /> No more elements appear at the position of /> ; After that, continue to take out the stored indexes from the queue in turn/> , and repeat the above steps until the queue is empty.

S14. Create an array Create a new array of equal length, and fill the initial values of the new array with random values, and take out the records one by one from the top of the stack of records. , calculation element/> /> Identification value, /> The identifier value represents the element/> The unique identifier of the The flag value is updated to the security XOR filter /> middle.

S15. Find each element The three hash values of /> 、/> and/> In and its subscript/> If the two hash values are inconsistent, get the secure XOR filter /> The two hash values are used as subscripts in the The identification value is XORed and finally in the security XOR filter/> Update the XOR operation result in .

The above is a specific implementation process of constructing a secure XOR filter in this embodiment. Based on the above process, when constructing a secure tree index, this embodiment can construct secure XOR filters for non-leaf nodes of the secure tree index in combination with its application parameters. and secure XOR filters for prefix-coded clusters in leaf nodes/> Safe XOR filter with keyword /> .

Furthermore, in this embodiment, the principle of constructing the security tree index is as follows:

The security tree index includes non-leaf nodes and leaf nodes. First, for the non-leaf nodes of the tree, starting from its root node, each non-leaf node will extend four child nodes downward according to the rules of the quadtree. These four child nodes will randomly assign 8 characters to the child nodes according to the Base32 character set, and then the child nodes will encrypt the characters, that is, map the characters to the corresponding security XOR filter.

Then for the leaf nodes of the tree, each leaf node stores a corresponding space object. Text information, including spatial objects/> ID encoding, geographic hash encoding prefix encoding cluster/> and keyword set/> . Wherein the spatial object/> The id is passed through the key/> Encrypted ciphertext, while geo-hashed prefix-encoded clusters and keyword set/> They will be mapped to their corresponding security XOR filters respectively.

Among them, building a safe tree index can be expressed as follows:

(3);

In formula (3), is a safe tree index,/> It is spatial text data.

Specifically, a secure tree index is constructed based on secure XOR filters and geographic hash coding, including:

S16, using the random character distribution method, according to the geographic hash code of the spatial text data, the spatial object is Generate leaf nodes in the form of and construct a tree index of plain text, where, /> A unique identifier representing a spatial object. A cluster of prefix codes representing the geohash codes of spatial objects. A set of keywords representing spatial objects.

S17, then, encrypt the constructed tree index of the plaintext, and use a pseudo-random counter in the non-leaf node Generate a pseudo-random number seed/> , and then use the pseudo-random number seed/> Generated by /> The assigned character set corresponds to /> value and map it to the secure XOR filter /> In Chinese, that is:

(4);

In formula (4), is a safe XOR filter for non-leaf nodes,/> is an XOR filter, Indicates the character set corresponding to /> value.

In the leaf node, the key is first used For spatial objects/> Encrypt and get the space object/> The ciphertext/> , using a pseudo-random number seed/> The prefix encoding cluster of geo-hashed codes/> All prefix codes included generate corresponding /> value, and all generated /> Values are mapped to safe XOR filters In Chinese, that is:

(5);

In formula (5), A secure XOR filter for prefix encoding clusters, /> is an XOR filter, /> Prefix code cluster representing geographic hash code/> All prefix codes included correspond to/> value.

At the same time, in the leaf node, for the keyword set , using a pseudo-random number seed/> Keyword Set All keywords in the above code generate corresponding /> Value, and mapped to the security XOR filter /> In Chinese, that is:

(6);

In formula (6), A safe XOR filter for keywords, /> is an XOR filter, /> Indicates a keyword set/> All keywords in the corresponding /> value.

When the secure tree index is built, use the key Encrypt the spatial text dataset, that is,

(7);

In formula (7), is the encrypted spatial text dataset, /> It is a spatial text dataset, including spatial data and text data./> is the key.

Finally, the obtained security tree index And all encrypted spatial text data Upload them to the cloud server together.

In this way, the secure tree index structure constructed by combining the secure XOR filter and the geographic hash code is uploaded to the cloud server. During the query processing, the spatial objects can be queried with higher accuracy and less memory usage.

S2. User-side query , based on the query/> Generate a trapdoor/> , and the trapdoor Upload to the cloud server, where the query/> ,/> Indicates the location information of the query point, /> Indicates query keyword information, /> Indicates the spatial extent of the query points.

Specifically, the user gives a query , and based on this query/> Generate a trapdoor/> , which can be expressed by the following formula:

(8).

First, for the location information of the query point , where the query coordinates/> Transformed into a geohash code and based on the given spatial range/> , calculate the corresponding prefix code/> , using a pseudo-random number seed/> Calculate the prefix code/> Its own/> Value/> And prefix encoding/> For each character in /> value , that is:

(9);

In formula (9), Encode the prefix /> Its own/> Value, /> Indicates prefix encoding Middle/> Characters/> Value, /> Indicates prefix code/> For each character in /> A collection of values, /> Indicates prefix code/> The character length of

For query keyword information , using a pseudo-random number seed/> Calculate the keyword set separately/> All keywords in /> Value, expressed as /> , that is:

(10);

In formula (10), Indicates a keyword set/> All keywords in /> A collection of values, Indicates a keyword set/> Middle/> Keywords/> Value, /> Represents a keyword set The number of keywords in .

S3, the cloud server side according to the trap door Search the target space object in the security tree index/> , and will be represented by the target space object/> The ciphertext/> The result set is composed of Return to the user.

That is, when querying, through the trapdoor The prefix encoding hash value in the search range is used to find the leaf nodes in the secure tree index. Each leaf node stores a spatial object, so that the corresponding target spatial object can be found./> At the same time, the hash value of the query keyword can be used to verify whether the leaf node meets the query conditions.

When the cloud server receives the query trap Then, according to the trapdoor/> , in the security tree index Search for target space objects that meet the requirements/> Finally, all searched target space objects that meet the requirements will be The ciphertext/> The result set is composed of The process of returning to the user end can be expressed by the following formula:

(11).

The specific implementation process is as follows:

S31, traversing the prefix code For each character in /> Value/> The collection of components /> , search the security tree index for the /> Value/> Existing security XOR filters/> The corresponding non-leaf nodes are used to determine the search scope.

The specific process is: traversing the prefix code For each character in /> Value/> The collection of components /> , calculate the hash value of each character/> /> The identification value and the three hash values corresponding to each character/> 、/> and/> ; and apply them to the security XOR filter in non-leaf nodes/> XOR the values in the If the identification value is equal, then the hash value of the character is proved/> Safe XOR filter present in non-leaf nodes/> middle.

Based on the above method, each character can be searched in the security tree index. Value/> Existing security XOR filters/> The corresponding non-leaf nodes are used to determine the search range.

After the traversal is completed, it is necessary to continue to check the leaf nodes below the non-leaf nodes that have been searched.

S32, find all leaf nodes within the search range, and determine the prefix code in each leaf node Is it in the security XOR filter/> If it is in, continue to judge its keyword set/> Are all keywords in the security XOR filter/> If so, the spatial object stored in the leaf node is determined as the target spatial object/> , and the target space object/> The ciphertext/> Add result set /> middle.

For each leaf node, first use prefix encoding The hash value of /> Determine the prefix code Is it in the security XOR filter/> If it is not in, then determine the next leaf node; if it is in, then use the hash value of the keyword/> Determine whether each keyword is in the security XOR filter/> If not in its filter/> Then, the next leaf node is determined; if the hash values of all keywords are All in its filter /> In the example, the spatial object stored in the leaf node is determined as the target spatial object/> , and the target space object/> The ciphertext/> Add result set /> In. Finally, after all leaf nodes are judged, the final result set is obtained. Return to the user.

S4: The user terminal determines the result set Query complete ciphertext information/> , and use the key The ciphertext information/> Decrypt and get the plaintext information.

The user receives the result set After that, according to/> The target space object in /> The ciphertext/> Find the complete ciphertext information/> , then use the key /> Decrypt and finally get the plaintext information, that is:

(12);

In formula (12), is the plaintext information obtained after decryption,/> Indicates the complete ciphertext information found according to the result set,/> is the key.

In this way, the query of spatial keywords is completed, and this process efficiently and accurately retrieves spatial objects that meet the user's query conditions on the cloud server side without leaking any information, ensuring data privacy and achieving efficient search while ensuring strong security.

Figure 2 shows a comparison of the false positive rates of Xor Filter and Bloom Filter with the same filter length as the number of inserted data increases. Under the same filter length, the number of inserted data is changed to conduct a comparative analysis of the false positive rates. The results show that with the increase in the number of inserted data, the false positive rate of Bloom filter increases significantly, while the XOR filter maintains a low false positive rate, and the false positive rate has been stable at around 0.4%.

Figure 3 shows an index generation time graph, which is used to demonstrate the time required to construct a security tree index by selecting different amounts of data (10, 1k, 10k, 20k, 50k, 100k). It has good scalability when processing small-scale data.

Embodiment 2,

This embodiment provides a device for implementing a method for secure keyword retrieval in a secret space based on an XOR filter, the device comprising a data owner end, a user end, and a cloud server end, wherein:

The data owner is used to construct a secure XOR filter and to construct a secure tree index based on the secure XOR filter and the geographic hash code, using the key Encrypting the spatial text data set, and uploading the security tree index and the encrypted spatial text data set to the cloud server;

The client is used to give a query , based on the query/> Generate a trapdoor/> , and the trapdoor Upload to the cloud server; and use it according to the result set/> Query complete ciphertext information/> , and use the key /> The ciphertext information/> Decrypt and obtain the plaintext information;

The cloud server is used to Search the target space object in the security tree index/> , and will be represented by the target space object/> The ciphertext/> The result set is composed of Return to the user.

Embodiment 3,

This embodiment also provides an electronic device, including:

at least one processor; and

A memory storing instructions, which, when executed by the at least one processor, enables the at least one processor to execute the encrypted space keyword security retrieval method based on XOR filter as described above.

In this embodiment, the electronic device may include, but is not limited to: personal computers, server computers, workstations, desktop computers, laptop computers, notebook computers, mobile computing devices, smart phones, tablet computers, cellular phones, personal digital assistants (PDAs), handheld devices, messaging devices, wearable computing devices, consumer electronic devices, and the like.

Embodiment 4,

This embodiment also provides a machine-readable storage medium storing executable instructions, which, when executed, enable the machine to execute the above-mentioned method for secure keyword retrieval in a secret space based on an XOR filter.

Specifically, a system or device equipped with a readable storage medium can be provided, on which software program codes that implement the functions of any of the above-mentioned embodiments are stored, and a computer or processor of the system or device can read and execute instructions stored in the readable storage medium.

In this case, the program code itself read from the machine-readable medium can realize the function of any one of the above embodiments, and thus the machine-readable code and the machine-readable storage medium storing the machine-readable code constitute part of this specification.

Examples of readable storage media include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD-RW), magnetic tapes, non-volatile memory cards, and ROMs. Optionally, the program code may be downloaded from a server computer or a cloud via a communication network.

Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

The present invention is described with reference to the flowchart and/or block diagram of the method, device (system), and computer program product according to the embodiment of the present invention. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of the process and/or box in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the technical solution of the present invention, and are not intended to limit the specific implementation methods of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the claims of the present invention shall be included in the protection scope of the claims of the present invention.

Claims (10)

1. A method for secure keyword retrieval in a secret space based on an XOR filter, characterized in that the method comprises: S1. The data owner constructs a secure XOR filter and a secure tree index based on the secure XOR filter and geo-hash encoding, and then uses the key Encrypting the spatial text data set, and uploading the security tree index and the encrypted spatial text data set to the cloud server; S2. User-side query , based on the query/> Generate a trapdoor/> , and the trapdoor/> Upload to the cloud server, where the query/> ,/> Indicates the location information of the query point, /> Indicates query keyword information, /> Indicates the spatial range of the query point; S3, the cloud server side according to the trap door Search the target space object in the security tree index/> , and will be represented by the target space object/> The ciphertext/> The result set is composed of Return to the user end; S4: The user terminal determines the result set Query complete ciphertext information/> , and use the key /> The ciphertext information/> Decrypt and get the plaintext information. 2. The method for secure keyword retrieval in a dense space based on an XOR filter according to claim 1, characterized in that in the step S1, constructing a secure XOR filter specifically comprises: S10, will gather The elements in are mapped to the safe XOR filter /> In, we get: (2); In formula (2), For the collection/> Security XOR filter, /> is an XOR filter, /> is a random number; S11. Gather The elements in are added to the array in sequence /> In this case, each element Generate three sets of hash functions respectively/> 、/> and/> , based on the hash function/> 、/> and/> , calculate the element/> The corresponding three hash values are: 、/> and/> ; where /> ,/> Represents a collection /> length; S12, based on each element The three hash values of /> 、/> and/> , the element /> Place into array At the corresponding position, the array /> Iterate to find the list containing only one element/> Position, and initialize a queue, the element/> Subscript /> Join the queue; S13, taking out the stored index from the head of the queue and from the array /> Get the subscript in/> Corresponding elements/> , and then use/> The form is recorded into a stack, and at the same time from the array /> Remove elements from /> , when the array /> It appears again in the same directory containing only one element /> , place the element /> Subscript /> Add to the queue until the array /> No more elements appear at the position of /> , and then continue to take out the stored indexes from the queue in turn/> , and repeat the above steps until the queue is empty; S14. Create an array A new array of the same length is created, and the initial values of the new array are all filled with random values, and the records are taken out one by one from the top of the stack. , calculation element/> /> Identify the value and put the /> The flag value is updated to the security XOR filter /> middle; S15. Find each element The three hash values of /> 、/> and/> In and its subscript/> If the two hash values are inconsistent, get the secure XOR filter /> The two hash values are used as subscripts in the The identification value is XORed and finally in the security XOR filter/> Update the XOR operation result in . 3. The method for secure keyword retrieval in a dense space based on an XOR filter according to claim 2, characterized in that in step S1, the expression for constructing a secure tree index is: (3); In formula (3), is a safe tree index,/> It is spatial text data; The construction of a secure tree index based on a secure XOR filter and a geographic hash code specifically includes: S16, using the random character distribution method, according to the geographic hash code of the spatial text data, the spatial object is Generate leaf nodes in the form of and construct a tree index of plain text, where, /> A unique identifier representing a spatial object. A cluster of prefix codes representing the geohash codes of spatial objects. A set of keywords representing spatial objects; S17, encrypt the constructed tree index of the plaintext, and use a pseudo-random counter in the non-leaf node Generate a pseudo-random number seed/> , and then use the pseudo-random number seed/> Generated by /> The assigned character set corresponds to /> value and map it to the secure XOR filter /> In Chinese, that is: (4); In formula (4), is a safe XOR filter for non-leaf nodes,/> is an XOR filter, /> Indicates the character set corresponding to /> value; In the leaf node, use the key For spatial objects/> Encrypt and get the space object/> The ciphertext , using a pseudo-random number seed/> The prefix encoding cluster of geo-hashed codes/> All prefix codes included generate corresponding /> value, and all generated /> Values are mapped to safe XOR filters In Chinese, that is: (5); In formula (5), A secure XOR filter for prefix encoding clusters, /> is an XOR filter, /> Prefix code cluster representing geographic hash code/> All prefix codes included correspond to/> value; And, in the leaf nodes, use the pseudo-random number seed Set keyword /> All keywords in the generate corresponding /> Value, and mapped to the security XOR filter /> In Chinese, that is: (6); In formula (6), A safe XOR filter for keywords, /> is an XOR filter, /> Indicates a keyword set/> All keywords in the corresponding /> value. 4. The method for secure keyword retrieval in a secret space based on an XOR filter according to claim 1, characterized in that in step S1, the key is used Encrypt the spatial text dataset, specifically: (7); In formula (7), is the encrypted spatial text dataset, /> It is a spatial text dataset, including spatial data and text data./> is the key. 5. The method for secure keyword retrieval in a dense space based on an XOR filter according to claim 1, characterized in that in step S2, based on the query Generate a trapdoor/> ,Specifically: (8); In formula (8), For trapdoor, /> Indicates the location information of the query point, /> Indicates query keyword information, /> Indicates the spatial range of the query point; Among them, for the location information of the query point , converting the query coordinates into geographic hash codes and sparsely according to the given spatial range/> , calculate the corresponding prefix code/> , using a pseudo-random number seed/> Calculate the prefix code Its own/> Value/> And prefix encoding/> For each character in /> Value/> : (9); In formula (9), Encode the prefix /> Its own/> Value, /> Indicates prefix code/> Middle/> Characters/> Value, /> Indicates prefix code/> For each character in /> A collection of values, Indicates prefix code/> The character length of For query keyword information , using a pseudo-random number seed/> Calculate the keyword set separately/> All keywords in /> Value, expressed as /> : (10); In formula (10), Indicates a keyword set/> All keywords in /> A collection of values, Indicates a keyword set/> Middle/> Keywords/> Value, /> Represents a keyword set The number of keywords in . 6. The method for secure keyword retrieval in a dense space based on an XOR filter according to claim 5, characterized in that in step S3, the result set The expression is: (11); In formula (11), Indicates a trapdoor, /> Represents a safe tree index; The cloud server end according to the trap door Search the target space object in the security tree index/> , specifically including: S31, traversing the prefix code For each character in /> Value/> The collection of components /> , search the security tree index for the /> Value/> Existing security XOR filters/> The corresponding non-leaf nodes to determine the search range; S32, find all leaf nodes within the search range, and determine the prefix code in each leaf node Is it in the security XOR filter/> If it is in, continue to judge its keyword set/> Are all keywords in the security XOR filter/> If so, the spatial object stored in the leaf node is determined as the target spatial object. , and the target space object/> The ciphertext/> Add result set /> middle. 7. The method for secure keyword retrieval in a secret space based on an XOR filter according to claim 1, characterized in that in step S4, a key is used The ciphertext information/> Decryption, specifically: (12); In formula (12), is the plaintext information obtained after decryption,/> Indicates the complete ciphertext information found according to the result set,/> is the key. 8. A device for implementing a secure keyword retrieval method in a secret space based on an XOR filter, characterized in that the device comprises a data owner end, a user end, and a cloud server end, wherein: The data owner is used to construct a secure XOR filter and to construct a secure tree index based on the secure XOR filter and the geographic hash code, using the key Encrypting the spatial text data in the security tree index, and uploading the security tree index and the encrypted spatial text data to a cloud server; The client is used to give a query , based on the query/> Generate a trapdoor/> , and the trapdoor Upload to the cloud server; and use it according to the result set/> Query complete ciphertext information , and use the key /> The ciphertext information/> Decrypt and obtain the plaintext information; The cloud server is used to Searching for a target spatial object in the secure tree index , and will be represented by the target space object/> The ciphertext/> The result set is composed of Return to the user. 9. An electronic device, comprising: at least one processor; and A memory storing instructions, which, when executed by the at least one processor, enables the at least one processor to execute the encrypted space keyword security retrieval method based on an XOR filter as described in any one of claims 1 to 7. 10. A machine-readable storage medium, characterized in that it stores executable instructions, which, when executed, enable the machine to execute the encrypted space keyword security retrieval method based on XOR filter as described in any one of claims 1 to 7.