User location privacy protection method and system based on homomorphic encryption

Abstract

The invention relates to the technical field of information security, and discloses a user location privacy protection method and system based on homomorphic encryption, and the system comprises a service provider database label module, a database SHE encryption processing module, a request receiving SJS protocol analysis module, a dual-server cloud model analysis module, and a user service request information acquisition module. The method comprises the following steps: generating a public key PK and a private key SK according to a database containing a user position data set by using an SHE encryption algorithm to encrypt the database, outsourcing the public key PK and the private key SK to a cloud platform A, outsourcing the encrypted database and the public key PK to a cloud platform B, analyzing POI recommendation based on user social influence and geographical influence, establishing an SJS protocol, and sending the POI recommendation to a user. The cloud platform is combined with the SJS protocol to carry out cooperative query, and an attacker cannot obtain the original position information of the user in the encryption transmission process, so that the possibility of data leakage is reduced.

Description

Technical Field

[0001] The present invention relates to the field of information security technology, and more particularly to a method and system for protecting user location privacy based on homomorphic encryption. Background Art

[0002] With the rapid development of technologies such as the Internet, big data, and artificial intelligence, the collection, storage, and use of personal information have become easier, but the risk of privacy leakage has also increased. For example, emerging technology products such as social media, smart homes, and wearable devices may become channels for privacy leakage while bringing convenience. The popularization of Internet of Things devices makes every link in the data supply chain a potential weak link for privacy leakage. For example, smart bracelets, smart home devices, etc. continuously collect users' location information. Once this information is leaked, it may bring serious privacy and security problems to users.

[0003] With the frequent occurrence of privacy leakage incidents, the public's attention to privacy protection has been continuously improved. Users have begun to pay more attention to how their personal information is collected, used, and shared, and show strong disgust for privacy violations. This trend prompts enterprises and institutions to be more cautious when collecting and using user information, and at the same time promotes the development and application of privacy protection technologies. Encryption technology is an important means to protect information security. With the continuous development of encryption technology, it provides technical support for location privacy protection methods based on encryption.

[0004] However, traditional encryption technologies have some limitations in protecting user location privacy. For example, traditional encryption methods often need to decrypt the data before querying and analyzing it, and attackers may invade during the data decryption process, which increases the risk of data leakage and cannot effectively protect user location privacy. Summary of the Invention

[0005] To overcome the above-mentioned defects of the prior art, the present invention provides a user location privacy protection system based on homomorphic encryption to solve the problems existing in the above background art.

[0006] The present invention provides the following technical solutions: A user location privacy protection system based on homomorphic encryption, including: a service provider database tagging module, a database SHE encryption processing module, a request receiving SJS protocol analysis module, a dual-server cloud model analysis module, and a user service request information acquisition module;

[0007] The service provider database tagging module forms a database containing a set of user location data based on the check-in data of each user, and transmits the database to the database SHE encryption processing module;

[0008] The database SHE encryption processing module uses the SHE encryption algorithm to generate a public key PK and a private key SK to encrypt the database, and outsources the encrypted database, the generated public key PK and private key SK to cloud platform A, and outsources the encrypted database and the generated public key PK to cloud platform B;

[0009] The request receiving SJS protocol analysis module is used to receive the query request issued by the user, analyze the POI recommendation based on the user's social influence and geographical influence, establish the SJS protocol, and transmit the result to the dual-server cloud model analysis module;

[0010] The dual-server cloud model analysis module receives the query request transmitted by the request receiving SJS protocol analysis module, and transmits the user query request to cloud platform A and cloud platform B respectively. The cloud platforms cooperate in the query in combination with the SJS protocol, obtain the cooperative query result and transmit it to the user service request information acquisition module;

[0011] The user service request information acquisition module receives the cooperative query results of cloud platform A and cloud platform B in the dual-server cloud model analysis module, and decrypts the cooperative query results with the private key SK.

[0012] Preferably, in the service provider database label module, the user's original check-in data is obtained through the API interface to generate user dynamic labels, including: basic information: user ID, device ID, and check-in timestamp, location information: longitude and latitude coordinates and location accuracy, environmental information: network type and IP address;

[0013] Establish a unique user identifier and combine it with the user dynamic label to generate a database containing the user location data set.

[0014] Preferably, in the database SHE encryption processing module, the specific content of encrypting the database with the SHE encryption algorithm to generate the public key PK and the private key SK is as follows:

[0015] Key generation: Given the security parameter K M 、K r 、K L 、K p and K q , the key generation algorithm sets the message space to M, where Then, randomly select a K L bit random number L and a K p bit prime number p, and finally generate a secret key SK = {p, L} and the message space M;

[0016] Encryption algorithm: According to the given secret key SK, encrypt the message m ∈ M in the following way:

[0017] c = (r × L + m)(1 + r' × p) mod N, where N represents a preset large integer and is used as a modulus for operations, and both represent random numbers, and c represents the encrypted information;

[0018] Decryption algorithm: Based on the given secret key SK, decrypt the message c in the following manner:

[0019] m' = (c mod p) mod L, where m' represents the decrypted information.

[0020] Preferably, in the request receiving SJS protocol analysis module, the specific content of analyzing POI recommendations based on user social influence and geographical influence, establishing the SJS protocol, and transmitting the result to the dual-server cloud model analysis module is as follows:

[0021] Analyze POI recommendations based on user social influence and geographical influence using the collaborative filtering method based on friends. The calculation formula is: where F i represents the set of friends of user u i , user u k is a friend of user u i , c k,j represents the check-in behavior of user u k at p j , SI k,i represents the social influence weight of user u k on user u i ;

[0022] Among them, the calculation formula for the social influence weight of user u k on user u i is: SI k,i = ξ × Jac(F k , F i ) + (1 - ξ) × Jac(L k , L i ), where ξ ∈ [0, 1] represents an adjustable parameter, F k and F i respectively represent the set of friend lists of user u k and user u i , L k and L i respectively represent the set of POIs visited by user u k 0 and user u i . If ξ = 0, the prediction result depends on the geographical influence between users. If ξ = 0, the prediction result depends on the social influence between users;

[0023] Establish the SJS protocol for POI recommendation based on user social influence and geographical influence, and transmit the SJS protocol to the dual-server cloud model analysis module for joint execution by Cloud Platform A and Cloud Platform B.

[0024] Preferably, in the user service request application receiving module, a query request sent by the user is received, an encrypted query request is generated based on an encryption algorithm, and two encrypted vectors [X] and [Y] are formed according to the encrypted query request.

[0025] Preferably, in the dual-server cloud model analysis module, the query request transmitted by the SJS protocol analysis module is received and the user query request is respectively transmitted to Cloud Platform A and Cloud Platform B. The cloud platforms perform collaborative queries in combination with the SJS protocol, and the specific content of the collaborative query results is as follows:

[0026] Cloud Platform A receives the generated public key PK and private key SK. Cloud Platform B receives the generated public key PK and the two encrypted vectors [X] and [Y] formed by the encrypted query request, where X = (x1, x2, x3,..., x n ), Y = (y1, y2, y3,..., y n ), n represents the total number of key nodes for the encrypted request to form the encrypted vector, and i represents the key node number for the encrypted request to form the encrypted vector;

[0027] Cloud Platform B generates two random numbers r1 and r2 according to the encryption algorithm of the encrypted query request and the two encrypted vectors [X] and [Y], and transmits the random numbers r1 and r2 to Cloud Platform A;

[0028] Cloud Platform A receives the random numbers r1 and r2, decrypts the random numbers r1 and r2 using the private key SK, and calculates where f represents the output value of Cloud Platform A receiving the random numbers r1 and r2, s represents the scalar factor, and f is transmitted to Cloud Platform B;

[0029] Cloud Platform B receives the output value of Cloud Platform A and calculates where h represents the output value of Cloud Platform B. Cloud Platform B obtains the collaborative query result based on the calculated h value.

[0030] Preferably, the user service request information acquisition module receives the collaborative query results of Cloud Platform A and Cloud Platform B in the dual-server cloud model analysis module, and the specific content of decrypting the collaborative query results using the private key SK is as follows:

[0031] The dual-server cloud model analysis module transmits the collaborative query results of Cloud Platform A and Cloud Platform B to the user service request information acquisition module in an encrypted form through a secure channel;

[0032] The user service request information acquisition module receives the encrypted collaborative query result, obtains the private key SK, which is paired with the public key PK pre-stored in cloud platform A and cloud platform B for asymmetric decryption, and transmits the decrypted collaborative query to the user side.

[0033] A method for protecting user location privacy based on homomorphic encryption includes the following steps:

[0034] Step S01: Form a database containing a set of user location data based on the check-in data of each user;

[0035] Step S02: Use the SHE encryption algorithm to generate a public key PK and a private key SK to encrypt the database, and outsource the encrypted database, the generated public key PK and private key SK to cloud platform A, and outsource the encrypted database and the generated public key PK to cloud platform B;

[0036] Step S03: Receive the query request issued by the user, analyze the POI recommendation based on the user's social influence and geographical influence, and establish the SJS protocol;

[0037] Step S04: Transmit the user query request to cloud platform A and cloud platform B respectively. The cloud platforms perform collaborative queries in combination with the SJS protocol to obtain the collaborative query result;

[0038] Step S05: Receive the collaborative query results of cloud platform A and cloud platform B in the dual-server cloud model analysis module, and decrypt the collaborative query results with the private key SK.

[0039] The technical effects and advantages of the present invention:

[0040] The present invention constitutes a user location privacy protection system based on homomorphic encryption by providing a service provider database tagging module, a database SHE encryption processing module, a request receiving SJS protocol analysis module, a dual-server cloud model analysis module, and a user service request information acquisition module, thereby realizing the privacy protection of user location information;

[0041] Form a database containing a set of user location data based on the check-in data of the user, use the SHE encryption algorithm to generate a public key PK and a private key SK to encrypt the database, and outsource the encrypted database, the generated public key PK and private key SK to cloud platform A, and outsource the encrypted database and the generated public key PK to cloud platform B, effectively ensuring the privacy of the data;

[0042] Receive the query request sent by the user, analyze the POI recommendation based on the user's social influence and geographical influence, establish the SJS protocol, and the cloud platform collaborates to query in combination with the SJS protocol to obtain the collaborative query result, making it impossible for attackers to obtain the user's original location information, further reducing the possibility of data leakage, and realizing the privacy protection of the user's location information. Brief Description of the Drawings

[0043] Figure 1 It is a schematic structural diagram of a user location privacy protection system based on homomorphic encryption.

[0044] Figure 2 It is a schematic flow diagram of a user location privacy protection method based on homomorphic encryption. Detailed Embodiment

[0045] Next, the technical solutions in the present invention will be clearly and completely described in conjunction with the accompanying drawings in the present invention. In addition, the forms of each structure described in the following embodiments are only examples. A user location privacy protection method and system based on homomorphic encryption involved in the present invention are not limited to the structures described in the following embodiments. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0046] As Figure 1 shown, the present invention provides a user location privacy protection system based on homomorphic encryption, including: a service provider database tagging module, a database SHE encryption processing module, a request receiving SJS protocol analysis module, a dual-server cloud model analysis module, and a user service request information acquisition module;

[0047] The service provider database tagging module forms a database containing the user location data set according to the check-in data of each user, and transmits the database to the database SHE encryption processing module;

[0048] The database SHE encryption processing module uses the SHE encryption algorithm to generate a public key PK and a private key SK to encrypt the database, and outsources the encrypted database and the generated public key PK and private key SK to cloud platform A, and outsources the encrypted database and the generated public key PK to cloud platform B;

[0049] The request receiving SJS protocol analysis module is used to receive the query request sent by the user, analyze the POI recommendation based on the user's social influence and geographical influence, establish the SJS protocol, and transmit the result to the dual-server cloud model analysis module;

[0050] The dual-server cloud model analysis module receives the query request transmitted by the SJS protocol analysis module and transmits the user query request to cloud platform A and cloud platform B respectively. The cloud platform performs collaborative query in combination with the SJS protocol, obtains the collaborative query result and transmits it to the user service request information acquisition module;

[0051] The user service request information acquisition module receives the collaborative query results of cloud platform A and cloud platform B in the dual-server cloud model analysis module, and decrypts the collaborative query results using the private key SK.

[0052] In this embodiment, it should be specifically noted that the service provider database tag module obtains the user's original check-in data through the API interface to generate a user dynamic tag, including: basic information: user ID, device ID and check-in timestamp, location information: latitude and longitude coordinates and location accuracy, and environmental information: network type and IP address;

[0053] A unique user ID is created and combined with user dynamic tags to generate a database containing a collection of user location data.

[0054] In this embodiment, it should be specifically explained that, in the database SHE encryption processing module, the specific contents of using the SHE encryption algorithm to generate the public key PK and the private key SK to encrypt the database are as follows:

[0055] Key generation: Given a security parameter K M , K r , K L , K p and K q , the key generation algorithm sets the message space to M, where Then, randomly select a K L A random number L of bits and a K p The prime number p of bits finally generates a secret key SK = {p, L} and a message space M;

[0056] Encryption algorithm: Based on a given secret key SK, encrypt the message m∈M as follows:

[0057] c=(r×L+m)(1+r′×p)mod N, where N represents a preset large integer, which is used as the modulus for calculation. and Both represent random numbers, and c represents encrypted information;

[0058] Decryption algorithm: Based on the given secret key SK, decrypt the message c as follows:

[0059] m′=(c mod p) mod L, where m′ represents the decrypted information.

[0060] In this embodiment, it should be specifically noted that in the request receiving SJS protocol analysis module, the analysis of POI recommendations based on user social influence and geographical influence, the establishment of the SJS protocol, and the transmission of the results to the dual-server cloud model analysis module are as follows:

[0061] Analyze POI recommendations based on user social influence and geographical influence using the collaborative filtering method based on friends. The calculation formula is: Where F i represents the set of friends of user u i . User u k is a friend of user u i . c k,j represents the check-in behavior of user u k at p j . SI k,i represents the social influence weight of user u k on user u i ;

[0062] Among them, the calculation formula for the social influence weight of user u k on user u i is: SI k,i = ξ × Jac(F k , F i ) + (1 - ξ) × Jac(L k , L i ), where ξ ∈ [0, 1] represents an adjustable parameter. F k and F i respectively represent the set of friend lists of user u k and user u i . L k and L i respectively represent the set of POIs visited by user u k and user u i . If ξ = 0, the prediction result depends on the geographical influence between users. If ξ = 0, the prediction result depends on the social influence between users;

[0063] Establish the SJS protocol for POI recommendations based on user social influence and geographical influence, and transmit the SJS protocol to the dual-server cloud model analysis module for joint execution by cloud platform A and cloud platform B.

[0064] In this embodiment, it should be specifically noted that in the dual-server cloud model analysis module, the query request transmitted by the request receiving SJS protocol analysis module is received and transmitted to cloud platform A and cloud platform B respectively. The cloud platforms perform collaborative queries in combination with the SJS protocol to obtain the collaborative query results as follows:

[0065] Cloud platform A receives the generated public key PK and private key SK, and cloud platform B receives the two encrypted vectors [X] and [Y] formed by the generated public key PK and the encrypted query request, where X = (x1, x2, x3,..., x n ), Y = (y1, y2, y3,..., y n ), n represents the total number of key nodes for the encrypted request to form an encrypted vector, and i represents the key node number for the encrypted request to form an encrypted vector;

[0066] Cloud platform B generates two random numbers r1 and r2 based on the encryption algorithm of the encrypted query request and the two encrypted vectors [X] and [Y], and transmits the random numbers r1 and r2 to cloud platform A;

[0067] Cloud platform A receives the random numbers r1 and r2, decrypts the random numbers r1 and r2 using the private key SK, and calculates where f represents the output value of cloud platform A receiving the random numbers r1 and r2, s represents a scalar factor, and f is transmitted to cloud platform B;

[0068] Cloud platform B receives the output value of cloud platform A and calculates where h represents the output value of cloud platform B, and cloud platform B obtains the collaborative query result based on the calculated h value.

[0069] In this embodiment, it should be specifically noted that the user service request information acquisition module receives the collaborative query results of cloud platforms A and B in the dual-server cloud model analysis module, and the specific content of decrypting the collaborative query results using the private key SK is as follows:

[0070] The dual-server cloud model analysis module transmits the collaborative query results of cloud platforms A and B to the user service request information acquisition module in an encrypted form through a secure channel;

[0071] The user service request information acquisition module receives the encrypted collaborative query results, obtains the private key SK, which is paired with the public key PK pre-stored in cloud platforms A and B for asymmetric decryption, and transmits the decrypted collaborative query to the user terminal.

[0072] As Figure 2 shown, in this embodiment, it should be specifically noted that a method for protecting user location privacy based on homomorphic encryption includes the following steps:

[0073] Step S01: Form a database containing a set of user location data based on the check-in data of each user;

[0074] Step S02: Use the SHE encryption algorithm to generate a public key PK and a private key SK to encrypt the database, and outsource the encrypted database, the generated public key PK, and the private key SK to cloud platform A, and outsource the encrypted database and the generated public key PK to cloud platform B;

[0075] Step S03: Receive the query request sent by the user, analyze the POI recommendation based on the user's social influence and geographical influence, and establish the SJS protocol;

[0076] Step S04: Transmit the user's query request to cloud platform A and cloud platform B respectively. The cloud platforms perform collaborative queries in combination with the SJS protocol to obtain the collaborative query results;

[0077] Step S05: Receive the collaborative query results of cloud platform A and cloud platform B in the dual-server cloud model analysis module, and decrypt the collaborative query results with the private key SK.

[0078] In this embodiment, it should be specifically noted that the main difference between this embodiment and the prior art is that this embodiment constitutes a user location privacy protection system based on homomorphic encryption by providing a service provider database label module, a database SHE encryption processing module, a request receiving SJS protocol analysis module, a dual-server cloud model analysis module, and a user service request information acquisition module, so as to realize the privacy protection of user location information;

[0079] Form a database containing the user location data set based on the user's check-in data, use the SHE encryption algorithm to generate a public key PK and a private key SK to encrypt the database, and outsource the encrypted database, the generated public key PK, and the private key SK to cloud platform A, and outsource the encrypted database and the generated public key PK to cloud platform B, effectively ensuring the privacy of the data;

[0080] Receive the query request sent by the user, analyze the POI recommendation based on the user's social influence and geographical influence, and establish the SJS protocol. The cloud platforms perform collaborative queries in combination with the SJS protocol to obtain the collaborative query results, so that attackers cannot obtain the user's original location information, further reducing the possibility of data leakage and realizing the privacy protection of user location information.

[0081] Finally: The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0082] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the said claims.

Claims

1. A user location privacy protection system based on homomorphic encryption, characterized in that: Including: A service provider database tagging module, a database SHE encryption processing module, a request receiving SJS protocol analysis module, a dual-server cloud model analysis module, and a user service request information acquisition module; The service provider database tagging module forms a database containing a user location data set based on the check-in data of each user, and transmits the database to the database SHE encryption processing module; The database SHE encryption processing module uses the SHE encryption algorithm to generate a public key PK and a private key SK to encrypt the database, and outsources the encrypted database, the generated public key PK, and the private key SK to cloud platform A, and outsources the encrypted database and the generated public key PK to cloud platform B; The request receiving SJS protocol analysis module is used to receive a query request issued by a user, analyze POI recommendations based on user social influence and geographical influence, establish an SJS protocol, and transmit the result to the dual-server cloud model analysis module; The dual-server cloud model analysis module receives the query request transmitted by the request receiving SJS protocol analysis module, and transmits the user query request to cloud platform A and cloud platform B respectively. The cloud platforms perform a collaborative query in combination with the SJS protocol, and obtain a collaborative query result and transmit it to the user service request information acquisition module; The user service request information acquisition module receives the collaborative query results of cloud platform A and cloud platform B in the dual-server cloud model analysis module, and decrypts the collaborative query results with the private key SK.

2. The user location privacy protection system based on homomorphic encryption according to claim 1, wherein: In the service provider database tagging module, user original check-in data is obtained through an API interface to generate user dynamic tags, including: basic information: user ID, device ID, and check-in timestamp, location information: longitude and latitude coordinates and location accuracy, environmental information: network type and IP address; A user unique identifier is established and combined with the user dynamic tags to generate a database containing a user location data set.

3. The user location privacy protection system based on homomorphic encryption according to claim 1, wherein: In the database SHE encryption processing module, the specific content of using the SHE encryption algorithm to generate a public key PK and a private key SK to encrypt the database is as follows: Key Generation: Given security parameter K M , K r , K L , K p and K q , the key generation algorithm sets the message space to M, where Then, randomly select a K L -bit random number L and a K p -bit prime number p, and finally generate a secret key SK = {p, L} and the message space M; Encryption algorithm: According to the given secret key SK, encrypt the message m∈M in the following way: c = (r × L + m)(1 + r′ × p) mod N, where N represents a preset large integer and is used as a modulus for operations, and both represent random numbers, and c represents the encrypted information; Decryption algorithm: According to the given secret key SK, decrypt the message c in the following way: m′ = (c mod p) mod L, where m′ represents the decrypted information.

4. The user location privacy protection system based on homomorphic encryption according to claim 1, characterized in that: In the request receiving SJS protocol analysis module, the specific content of analyzing POI recommendations based on user social influence and geographical influence, establishing an SJS protocol, and transmitting the result to the dual-server cloud model analysis module is as follows: Analysis of POI recommendation based on user social influence and geographical influence using a friend-based collaborative filtering method. The calculation formula is as follows: Where F i represents the set of friends of user u i , and user u k is a friend of user u i . c k,j represents the check-in behavior of user u k at p j . SI k,i represents the social influence weight of user u k on user u i . Among them, user u k For user u i The calculation formula for the social influence weight is: SI k,i = ξ × Jac(F k , F i ) + (1 - ξ) × Jac(L k , L i ), where ξ ∈ [0, 1] represents an adjustable parameter, F k and F i respectively represent the set of friend lists of user u k and user u i , L k and L i respectively represent the set of POIs visited by user u k and user u i . If ξ = 0, the prediction result depends on the geographical influence between users. If ξ = 0, the prediction result depends on the social influence between users; An SJS protocol is established based on POI recommendations based on user social influence and geographical influence, and the SJS protocol is transmitted to cloud platform A and cloud platform B in the dual-server cloud model analysis module for joint execution.

5. The user location privacy protection system based on homomorphic encryption according to claim 1, characterized in that: In the dual-server cloud model analysis module, the specific content of receiving the query request transmitted by the request receiving SJS protocol analysis module, and transmitting the user query request to cloud platform A and cloud platform B respectively, and the cloud platforms performing a collaborative query in combination with the SJS protocol to obtain a collaborative query result is as follows: Cloud platform A receives the generated public key PK and private key SK. Cloud platform B receives the generated public key PK and two encrypted vectors [X] and [Y] formed by the encrypted query request, where X = (x1, x2, x3,..., x n ), Y = (y1, y2, y3,..., y n ), n represents the total number of key nodes for the encrypted request to form the encrypted vector, and i represents the key node number for the encrypted request to form the encrypted vector; Cloud platform B generates two random numbers r1 and r2 based on the encryption algorithm of the encrypted query request and two encryption vectors [X] and [Y], and transmits the random numbers r1 and r2 to cloud platform A; Cloud platform A receives random numbers r1 and r2, decrypts the random numbers r1 and r2 using the private key SK, and calculates where f represents the output value of cloud platform A receiving random numbers r1 and r2, s represents the scalar factor, and f is transmitted to cloud platform B; Cloud platform B receives the output value of cloud platform A and calculates where h represents the output value of cloud platform B, and cloud platform B obtains the collaborative query result based on the calculated h value.

6. The user location privacy protection system based on homomorphic encryption according to claim 1, characterized in that: The user service request information acquisition module receives the collaborative query results of cloud platform A and cloud platform B in the dual-server cloud model analysis module. The specific content of decrypting the collaborative query results with the private key SK is as follows: The dual-server cloud model analysis module transmits the collaborative query results of cloud platform A and cloud platform B to the user service request information acquisition module in an encrypted form through a secure channel; The user service request information acquisition module receives the encrypted collaborative query results, obtains the private key SK, which is paired with the public key PK pre-stored in cloud platform A and cloud platform B for asymmetric decryption, and transmits the decrypted collaborative query to the user terminal.

7. A method for protecting user location privacy based on homomorphic encryption, which is used for a system for protecting user location privacy based on homomorphic encryption according to any one of claims 1-6 above, characterized in that: It includes the following steps: Step S01: Form a database containing the user location data set based on the check-in data of each user; Step S02: Use the SHE encryption algorithm to generate a public key PK and a private key SK to encrypt the database, and outsource the encrypted database, the generated public key PK and private key SK to cloud platform A, and outsource the encrypted database and the generated public key PK to cloud platform B; Step S03: Receive the query request sent by the user, analyze the POI recommendation based on the user's social influence and geographical influence, and establish the SJS protocol; Step S04: Transmit the user query request to cloud platform A and cloud platform B respectively. The cloud platforms perform collaborative queries in combination with the SJS protocol to obtain the collaborative query results; Step S05: Receive the collaborative query results of cloud platform A and cloud platform B in the dual-server cloud model analysis module, and decrypt the collaborative query results with the private key SK.

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