Privacy data protection method, apparatus, device, and computer storage medium

Abstract

The embodiment of the present application relates to the technical field of computer data processing, and discloses a privacy data protection method, device and equipment and computer storage medium, the method comprises: obtaining an original query request; the original query request includes the real moving track and request data of a user; a target query request is generated according to a target moving track and request data; the target moving track is determined from a plurality of false moving tracks corresponding to the real moving track according to track similarity; the response data corresponding to the target query request is determined; the target query result is determined according to the response data, and the target query result is returned to the user. Through the above manner, the security of the privacy data is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer data processing technology, specifically to a method, apparatus, device, and computer storage medium for protecting privacy data. Background Technology

[0002] With the continuous development of mobile technology and the rapid development of wireless technology, LBS (Location Based Service) is being used more and more widely in the mobile Internet and the Internet of Things, and has penetrated into the daily work and life of many enterprises and individuals.

[0003] More and more enterprises are using cloud servers to provide data services to users. However, as data volume increases, cloud servers may experience problems such as computing latency and slow transmission. Furthermore, LSPs (Location-based Service Providers) require users to provide their location information to publish corresponding query results, which exposes personal location privacy to the risk of third-party attacks and data leakage. Therefore, it is necessary to protect users' location privacy data. In the process of implementing this invention, the inventors of this application discovered that the existing technology has a low level of security in protecting privacy data, resulting in low security for privacy data. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a privacy data protection method, apparatus, device, and computer storage medium to solve the problem of low security of privacy data in the prior art.

[0005] According to one aspect of the present invention, a privacy data protection method is provided, the method comprising:

[0006] Obtain the original query request; the original query request includes the user's actual movement trajectory and request data;

[0007] A target query request is generated based on the target movement trajectory and the request data; the target movement trajectory is determined from multiple fake movement trajectories corresponding to the real movement trajectory based on trajectory similarity;

[0008] Determine the response data corresponding to the target query request;

[0009] The target query result is determined based on the response data, and the target query result is returned to the user.

[0010] In one alternative approach, the actual movement trajectory includes multiple actual trajectory points; the method further includes:

[0011] Determine the reachable location set corresponding to each of the real trajectory points; the reachable location set includes multiple query hotspot locations corresponding to the real trajectory points.

[0012] The false movement trajectory is obtained by constructing an undirected graph based on the set of reachable locations.

[0013] In one alternative approach, the false movement trajectory includes multiple false trajectory points; the method further includes:

[0014] The number of false trajectory points is compared with the number of true trajectory points to obtain the comparison result;

[0015] When the comparison results are the same, the distances corresponding to each pair of trajectory points are determined; the pair of trajectory points includes false trajectory points and true trajectory points with the same trajectory point order.

[0016] The trajectory similarity is determined based on the distance between all the trajectory point pairs.

[0017] In an optional embodiment, the method further includes: when the comparison results are different, calculating a first distance between each of the false trajectory points and each of the real trajectory points respectively;

[0018] The nearest false trajectory point is determined from the false trajectory points based on the first distance;

[0019] The farthest real trajectory point is determined from the real trajectory points based on the first distance corresponding to the nearest false trajectory point;

[0020] The trajectory similarity is determined based on the first distance corresponding to the farthest true trajectory point.

[0021] In an alternative approach, the method further includes: splitting the response data according to a secret sharing algorithm to obtain multiple sub-secret data;

[0022] Data restoration is performed based on the multiple sub-secret data to obtain the target query result.

[0023] In an optional embodiment, the method further includes: splitting the response data using an LBS server to obtain multiple sub-secret data;

[0024] Each of the sub-secret data is sent to multiple edge servers connected to the LBS server.

[0025] In an optional manner, the method further includes: decrypting the sub-secret data through each of the edge servers to obtain multiple decrypted sub-secret data;

[0026] Data is restored based on all the decrypted sub-secret data to obtain the target query result.

[0027] According to another aspect of the present invention, a privacy data protection device is provided, comprising:

[0028] The acquisition module is used to acquire the original query request; the original query request includes the user's actual movement trajectory and request data;

[0029] The generation module is used to generate a target query request based on the target movement trajectory and the request data; the target movement trajectory is determined from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity;

[0030] The determination module is used to determine the response data corresponding to the target query request;

[0031] The return module is used to determine the target query result based on the response data and return the target query result to the user.

[0032] According to another aspect of the present invention, a privacy data protection device is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0033] The memory is used to store at least one executable instruction that causes the processor to perform operations as described in the privacy data protection method.

[0034] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing at least one executable instruction that causes a privacy data protection device to perform the operation of the privacy data protection method as described above.

[0035] This invention obtains an original query request, which includes the user's actual movement trajectory and request data. Then, a target query request is generated based on the target movement trajectory and request data. The target movement trajectory is determined from multiple fake movement trajectories corresponding to the actual movement trajectory based on trajectory similarity, thereby effectively protecting the user's actual movement trajectory from being leaked and making it difficult to reverse engineer. Then, the response data corresponding to the target query request is determined. The target query result is determined based on the response data, and finally, the target query result is returned to the user.

[0036] Unlike existing technologies that lack correlation analysis between false and real trajectories, making it easier to reverse-engineer the real trajectory from the false trajectory, which could compromise the security of users' location privacy data, this invention improves the security of privacy data by determining the target movement trajectory from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity, and replacing the real movement trajectory in the query request with the target movement trajectory.

[0037] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0038] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0039] Figure 1 A flowchart illustrating the privacy data protection method provided in an embodiment of the present invention is shown;

[0040] Figure 2 A schematic diagram of the privacy data protection device provided in an embodiment of the present invention is shown;

[0041] Figure 3 A schematic diagram of the privacy data protection device provided in an embodiment of the present invention is shown. Detailed Implementation

[0042] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0043] Figure 1 A flowchart illustrating a privacy data protection method provided by an embodiment of the present invention is shown. This method is executed by a computer processing device or a server. The computer processing device may include devices such as mobile phones, tablets, and laptops, and the server may be a single server or a cluster of multiple servers. Figure 1 As shown, the method includes the following steps:

[0044] Step 10: Obtain the original query request; the original query request includes the user's actual movement trajectory and request data.

[0045] In one embodiment of the present invention, the original query request can be used to request a geolocation service. The actual movement trajectory is the user's movement trajectory during the request process. The request data includes the user's location information, the request timestamp, the unique identifier corresponding to the requested service, and the information the user is interested in. The location information may include the user's latitude and longitude, postal code, address, and other information at a certain time.

[0046] In another embodiment of the invention, the original query request may be received by the edge server corresponding to the user.

[0047] Step 20: Generate a target query request based on the target movement trajectory and the request data; the target movement trajectory is determined from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity.

[0048] In one embodiment of the present invention, the false movement trajectory can be a preset trajectory or a trajectory fitted based on the real movement trajectory. The trajectory similarity can be determined based on the distance between each trajectory point in the real movement trajectory and the false movement trajectory.

[0049] In another embodiment of the present invention, the determination of the target movement trajectory and the generation of the target query request can be completed by the edge server in step 10. The target query request can be obtained by the edge server through encryption of the target movement trajectory and the request data.

[0050] In one embodiment of the present invention, the actual movement trajectory includes multiple actual trajectory points; the actual trajectory points are arranged in the order of their appearance in the trajectory. The order of appearance is determined based on the appearance time of each trajectory point.

[0051] Step 20 further includes step 201: determining the reachable location set corresponding to each of the actual trajectory points. This reachable location set includes multiple query hotspot locations corresponding to the actual trajectory points. In this embodiment of the invention, the query hotspot locations are preset locations that frequently report query requests.

[0052] This involves determining the reachability between the actual trajectory point and each nearby query hotspot location, filtering the query hotspot locations based on the reachability, and obtaining the reachable location set corresponding to each actual trajectory point.

[0053] In one embodiment of the present invention, the hotspot location r is queried. h1 With the true trajectory point r m The reachability Arr between them can be calculated using the following formula:

[0054]

[0055] Among them, tm and t n The user is at the actual trajectory point r. m and the true trajectory point r n The time difference between the corresponding request times, S max For users in r m With r n The maximum speed of movement between two points, D(Li, Ln), is the true trajectory point r. m To find the hotspot location r h1 The distance between them.

[0056] In one embodiment of the present invention, if Arr < 1, it means that the actual trajectory point and the query hot spot location are not reachable, and the query hot spot location with a reachability of not less than 1 is added to the reachable location set.

[0057] Step 202: Construct an undirected graph based on the set of reachable locations to obtain the false movement trajectory.

[0058] In one embodiment of the present invention, the true trajectory point r is obtained. m With the true trajectory point r n The corresponding reachable candidate sets are Gm(g1, g2...gm) and Gn(g1, g2...gn). Construct undirected graphs for Gm and Gn. For each node in the undirected graph, establish a set containing all nodes directly connected to that node (excluding the node itself). For each node directly connected to the starting node, solve for all paths from it to the ending node, thus obtaining r. m With r n The set of paths between the starting and ending nodes can be summed to obtain all paths from the starting node to the ending node, i.e., the set of false movement trajectories.

[0059] In one embodiment of the present invention, the false movement trajectory includes multiple false trajectory points; the determination of trajectory similarity further includes:

[0060] Step 203: Compare the number of false trajectory points with the number of true trajectory points to obtain the comparison result.

[0061] In one embodiment of the present invention, considering that the number of trajectory points contained in the real movement trajectory and the false movement trajectory may be different, it is necessary to determine the mapping method between the distance between trajectories and the distance between trajectory points according to whether the number of trajectory points is the same.

[0062] Step 204: When the comparison results are the same, determine the distances corresponding to each pair of trajectory points; the pair of trajectory points includes false trajectory points and real trajectory points with the same trajectory point order.

[0063] In one embodiment of the present invention, there exists A1-A N These N+1 real trajectory points and B1-B N These N+1 false trajectory points form a pair of trajectory points A1 and B1, where N represents the order of the trajectory points.

[0064] Step 205: Determine the trajectory similarity based on the distance between all the trajectory point pairs.

[0065] In one embodiment of the present invention, the distances of all trajectory point pairs are summed to obtain a trajectory distance score, and the trajectory similarity is determined based on the trajectory distance score.

[0066] In one embodiment of the present invention, the smaller the trajectory distance score, the greater the trajectory similarity, and the trajectory similarity can be the reciprocal of the trajectory distance score, etc.

[0067] Considering that when the number of real trajectory points differs from the number of false movement trajectories, it is impossible to directly determine the trajectory similarity based on the sum of the distances between trajectory pairs with the same trajectory point order, therefore, in another embodiment of the present invention, when the comparison results are different, step 203 further includes:

[0068] Step 206: Calculate the first distance between each of the false trajectory points and each of the real trajectory points.

[0069] In one embodiment of the present invention, the calculation of the first distance can adopt a preset distance metric, such as Euclidean distance. When there are a real trajectory points and b false trajectory points, there are ab / 2 first distances in total.

[0070] Step 207: Determine the nearest false trajectory point from the false trajectory points based on the first distance.

[0071] In one embodiment of the present invention, the false trajectory point with the smallest first distance is determined as the nearest false trajectory point.

[0072] Step 208: Determine the farthest real trajectory point from the real trajectory points based on the first distance corresponding to the nearest false trajectory point.

[0073] In one embodiment of the present invention, a first distance is determined between the nearest false trajectory point and each real trajectory point, and the real trajectory point with the largest first distance from the nearest false trajectory point is determined as the farthest real trajectory point.

[0074] Step 209: Determine the trajectory similarity based on the first distance corresponding to the farthest true trajectory point.

[0075] In one embodiment of the present invention, the first distance between the farthest true trajectory point and the nearest false trajectory point is determined as the trajectory distance score, and then the trajectory similarity is determined based on the trajectory distance score.

[0076] By quantifying the correlation between fake movement trajectories used to protect users' real location privacy and their real movement trajectories through trajectory similarity, the system not only protects users' real location privacy from being leaked during transmission, but also increases the difficulty of reverse mining users' real movement trajectories from fake movement trajectories, thereby improving the security of privacy data.

[0077] Step 30: Determine the response data corresponding to the target query request.

[0078] In one embodiment of the present invention, a target query request is sent to an LBS server via an edge server, and the LBS server responds to the target query request to obtain response data. The response data may be data associated with the target's movement trajectory corresponding to the determined request data.

[0079] Step 40: Determine the target query result based on the response data and return the target query result to the user.

[0080] In one embodiment of the present invention, since the response data is associated with the user's location privacy, in order to improve the security of the user's privacy data, a secret sharing method can be adopted in the process of returning the response data to the user. The response data is split into multiple blocks and sent to multiple edge servers respectively. Each edge server decrypts the received block data and forwards it to the user terminal. Finally, the user terminal reconstructs the data from all the received block data to obtain the target query result and returns it to the user. While returning the real result required by the user, the location privacy data can only be cracked when multiple block data are available at the same time, which increases the difficulty of third-party attacks and improves the security of privacy data.

[0081] Therefore, in another embodiment of the present invention, step 40 further includes:

[0082] Step 401: The response data is split according to the secret sharing algorithm to obtain multiple sub-secret data.

[0083] In one embodiment of the present invention, the response data is split by an LBS server, and each sub-secret data includes a data index, which can be used to query the corresponding sub-secret data.

[0084] In one embodiment of the present invention, step 401 further includes: step 4011: splitting the response data through an LBS server to obtain multiple sub-secret data.

[0085] In one embodiment of the present invention, the LBS server splits the response data according to a secret sharing algorithm to obtain multiple sub-secret data. The secret sharing algorithm may be the Shamir algorithm.

[0086] Step 4012: Send each of the sub-secret data to multiple edge servers connected to the LBS server.

[0087] In one embodiment of the present invention, each edge server receives a sub-secret data. Distributing the sub-secret data across the various edge servers increases the difficulty for third parties to crack the code, while also shifting the computational burden of data encryption and decryption from the central server to decentralized processing, thereby improving data processing efficiency.

[0088] Step 402: Perform data restoration based on the multiple sub-secret data to obtain the target query result.

[0089] In one embodiment of the present invention, the restoration of sub-secret data may include first decrypting the received sub-secret data by the edge server, forwarding the decrypted data to the user's corresponding terminal, and then restoring all the received sub-secret data according to the data reconstruction algorithm in the secret sharing algorithm to obtain the target query result.

[0090] Therefore, in one embodiment of the present invention, step 402 further includes:

[0091] Step 4021: Decrypt the sub-secret data through each of the edge servers to obtain multiple decrypted sub-secret data.

[0092] In one embodiment of the present invention, an edge server decrypts the received sub-secret data to obtain decrypted sub-secret data, and sends the decrypted sub-secret data to the user's corresponding terminal. This ensures that only a certain number of edge servers can cooperate to calculate or recover the privacy location data, while fewer than this certain number of edge servers cannot obtain the relevant data, thereby improving the security of privacy-related data.

[0093] Step 4022: Restore the data based on all the decrypted sub-secret data to obtain the target query result.

[0094] In one embodiment of the present invention, after receiving all the decrypted sub-secret data, the user's corresponding terminal reconstructs the decrypted sub-secret data according to the Shamir algorithm to obtain the target query result.

[0095] The privacy data protection method provided in this invention obtains an original query request, which includes the user's real movement trajectory and request data. Then, a target query request is generated based on the target movement trajectory and request data. The target movement trajectory is determined from multiple fake movement trajectories corresponding to the real movement trajectory based on trajectory similarity, thereby effectively protecting the user's real movement trajectory from being leaked and making it difficult to reverse engineer. Then, the response data corresponding to the target query request is determined. The target query result is determined based on the response data, and finally, the target query result is returned to the user.

[0096] Unlike existing technologies that lack correlation analysis between false and real trajectories, making it easier to reverse-engineer the real trajectory from the false trajectory, which could compromise the security of users' location privacy data, the privacy data protection method provided in this invention determines the target movement trajectory from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity, and replaces the real movement trajectory in the query request with the target movement trajectory, thereby improving the security of privacy data.

[0097] Figure 2 A schematic diagram of the privacy data protection device provided in an embodiment of the present invention is shown. Figure 2 As shown, the device 50 includes: an acquisition module 501, a generation module 502, a determination module 503, and a return module 504.

[0098] The acquisition module 501 is used to acquire the original query request; the original query request includes the user's actual movement trajectory and request data.

[0099] The generation module 502 is used to generate a target query request based on the target movement trajectory and the request data; the target movement trajectory is determined from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity;

[0100] The determining module 503 is used to determine the response data corresponding to the target query request;

[0101] The return module 504 is used to determine the target query result based on the response data and return the target query result to the user.

[0102] In one optional approach, the actual movement trajectory includes multiple actual trajectory points; the generation module 502 is used to: determine the reachable location set corresponding to each of the actual trajectory points; the reachable location set includes multiple query hotspot locations corresponding to the actual trajectory points;

[0103] The false movement trajectory is obtained by constructing an undirected graph based on the set of reachable locations.

[0104] In one alternative approach, the false movement trajectory includes multiple false trajectory points; the generation module 502 is used to:

[0105] The number of false trajectory points is compared with the number of true trajectory points to obtain the comparison result;

[0106] When the comparison results are the same, the distances corresponding to each pair of trajectory points are determined; the pair of trajectory points includes false trajectory points and true trajectory points with the same trajectory point order.

[0107] The trajectory similarity is determined based on the distance between all the trajectory point pairs.

[0108] In an alternative approach, the generation module 502 is configured to: calculate a first distance between each of the false trajectory points and each of the real trajectory points when the comparison results are different;

[0109] The nearest false trajectory point is determined from the false trajectory points based on the first distance;

[0110] The farthest real trajectory point is determined from the real trajectory points based on the first distance corresponding to the nearest false trajectory point;

[0111] The trajectory similarity is determined based on the first distance corresponding to the farthest true trajectory point.

[0112] In an alternative approach, the return module 504 is also used for:

[0113] The response data is split according to the secret sharing algorithm to obtain multiple sub-secret data;

[0114] Data restoration is performed based on the multiple sub-secret data to obtain the target query result.

[0115] In an alternative approach, the return module 504 is also used for:

[0116] The response data is split using an LBS server to obtain multiple sub-secret data items;

[0117] Each of the sub-secret data is sent to multiple edge servers connected to the LBS server.

[0118] In an alternative approach, the return module 504 is also used for:

[0119] The sub-secret data is decrypted by each of the edge servers to obtain multiple decrypted sub-secret data.

[0120] Data is restored based on all the decrypted sub-secret data to obtain the target query result.

[0121] The specific working process of the privacy data protection device provided in this embodiment of the invention is largely the same as the specific method steps in the above method embodiment, and will not be repeated here.

[0122] The privacy data protection device provided in this embodiment of the invention obtains an original query request, which includes the user's real movement trajectory and request data. Then, it generates a target query request based on the target movement trajectory and request data. The target movement trajectory is determined from multiple fake movement trajectories corresponding to the real movement trajectory based on trajectory similarity, thereby effectively protecting the user's real movement trajectory from being leaked and making it difficult to reverse engineer. Then, it determines the response data corresponding to the target query request. Based on the response data, it determines the target query result and finally returns the target query result to the user.

[0123] Unlike existing technologies that lack correlation analysis between false and real trajectories, making it easier to reverse-engineer the real trajectory from the false trajectory, which could compromise the security of users' location privacy data, the privacy data protection device provided in this invention determines the target movement trajectory from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity, and replaces the real movement trajectory in the query request with the target movement trajectory, thereby improving the security of privacy data.

[0124] Figure 3 The diagram shows a schematic of the privacy data protection device provided in an embodiment of the present invention. The specific embodiments of the present invention do not limit the specific implementation of the privacy data protection device.

[0125] like Figure 3 As shown, the privacy data protection device may include: a processor 602, a communications interface 604, a memory 606, and a communications bus 608.

[0126] The processor 602, communication interface 604, and memory 606 communicate with each other via communication bus 608. Communication interface 604 is used to communicate with other network elements such as clients or other servers. The processor 602 executes program 610, specifically performing the relevant steps described in the above-described embodiment of the method for protecting privacy data.

[0127] Specifically, program 610 may include program code, which includes computer-executable instructions.

[0128] Processor 602 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The privacy data protection device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0129] Memory 606 is used to store program 610. Memory 606 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0130] Specifically, program 610 can be called by processor 602 to cause the privacy data protection device to perform the following operations:

[0131] Obtain the original query request; the original query request includes the user's actual movement trajectory and request data;

[0132] A target query request is generated based on the target movement trajectory and the request data; the target movement trajectory is determined from multiple fake movement trajectories corresponding to the real movement trajectory based on trajectory similarity;

[0133] Determine the response data corresponding to the target query request;

[0134] The target query result is determined based on the response data, and the target query result is returned to the user.

[0135] In one alternative approach, the actual movement trajectory includes multiple actual trajectory points; the program 610 is invoked by the processor 602 to cause the privacy data protection device to perform the following operations:

[0136] Determine the reachable location set corresponding to each of the real trajectory points; the reachable location set includes multiple query hotspot locations corresponding to the real trajectory points.

[0137] The false movement trajectory is obtained by constructing an undirected graph based on the set of reachable locations.

[0138] In one alternative approach, the false movement trajectory includes multiple false trajectory points; the program 610 is invoked by the processor 602 to cause the privacy data protection device to perform the following operations:

[0139] The number of false trajectory points is compared with the number of true trajectory points to obtain the comparison result;

[0140] When the comparison results are the same, the distances corresponding to each pair of trajectory points are determined; the pair of trajectory points includes false trajectory points and true trajectory points with the same trajectory point order.

[0141] The trajectory similarity is determined based on the distance between all the trajectory point pairs.

[0142] In an alternative manner, the program 610 is invoked by the processor 602 to cause the privacy data protection device to perform the following operations:

[0143] When the comparison results are different, the first distance between each false trajectory point and each real trajectory point is calculated respectively.

[0144] The nearest false trajectory point is determined from the false trajectory points based on the first distance;

[0145] The farthest real trajectory point is determined from the real trajectory points based on the first distance corresponding to the nearest false trajectory point;

[0146] The trajectory similarity is determined based on the first distance corresponding to the farthest true trajectory point.

[0147] In an alternative manner, the program 610 is invoked by the processor 602 to cause the privacy data protection device to perform the following operations:

[0148] The response data is split according to the secret sharing algorithm to obtain multiple sub-secret data;

[0149] Data restoration is performed based on the multiple sub-secret data to obtain the target query result.

[0150] In an alternative manner, the program 610 is invoked by the processor 602 to cause the privacy data protection device to perform the following operations:

[0151] The response data is split using an LBS server to obtain multiple sub-secret data items;

[0152] Each of the sub-secret data is sent to multiple edge servers connected to the LBS server.

[0153] In an alternative manner, the program 610 is invoked by the processor 602 to cause the privacy data protection device to perform the following operations:

[0154] The sub-secret data is decrypted by each of the edge servers to obtain multiple decrypted sub-secret data.

[0155] Data is restored based on all the decrypted sub-secret data to obtain the target query result.

[0156] The specific working process of the privacy data protection device provided in this embodiment of the invention is largely the same as the specific method steps in the above method embodiment, and will not be repeated here.

[0157] The privacy data protection device provided in this embodiment of the invention obtains an original query request, which includes the user's real movement trajectory and request data. Then, it generates a target query request based on the target movement trajectory and request data. The target movement trajectory is determined from multiple fake movement trajectories corresponding to the real movement trajectory based on trajectory similarity, thereby effectively protecting the user's real movement trajectory from being leaked and making it difficult to reverse engineer. Then, it determines the response data corresponding to the target query request. Based on the response data, it determines the target query result and finally returns the target query result to the user.

[0158] Unlike existing technologies that lack correlation analysis between false and real trajectories, making it easier to reverse-engineer the real trajectory from the false trajectory, which could compromise the security of users' location privacy data, the privacy data protection device provided in this invention determines the target movement trajectory from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity, and replaces the real movement trajectory in the query request with the target movement trajectory, thereby improving the security of privacy data.

[0159] This invention provides a computer-readable storage medium storing at least one executable instruction that, when executed on a privacy data protection device, causes the privacy data protection device to perform the privacy data protection method in any of the above method embodiments.

[0160] Specifically, the executable instructions can be used to cause the privacy data protection device to perform the following operations:

[0161] Obtain the original query request; the original query request includes the user's actual movement trajectory and request data;

[0162] A target query request is generated based on the target movement trajectory and the request data; the target movement trajectory is determined from multiple fake movement trajectories corresponding to the real movement trajectory based on trajectory similarity;

[0163] Determine the response data corresponding to the target query request;

[0164] The target query result is determined based on the response data, and the target query result is returned to the user.

[0165] In one alternative approach, the actual movement trajectory includes multiple actual trajectory points; the executable instructions can specifically be used to cause the privacy data protection device to perform the following operations:

[0166] Determine the reachable location set corresponding to each of the real trajectory points; the reachable location set includes multiple query hotspot locations corresponding to the real trajectory points.

[0167] The false movement trajectory is obtained by constructing an undirected graph based on the set of reachable locations.

[0168] In one alternative approach, the spoofed movement trajectory includes multiple spoofed trajectory points; the executable instructions cause the privacy data protection device to perform the following operations:

[0169] The number of false trajectory points is compared with the number of true trajectory points to obtain the comparison result;

[0170] When the comparison results are the same, the distances corresponding to each pair of trajectory points are determined; the pair of trajectory points includes false trajectory points and true trajectory points with the same trajectory point order.

[0171] The trajectory similarity is determined based on the distance between all the trajectory point pairs.

[0172] In an alternative approach, the executable instructions cause the privacy data protection device to perform the following operations:

[0173] When the comparison results are different, the first distance between each false trajectory point and each real trajectory point is calculated respectively.

[0174] The nearest false trajectory point is determined from the false trajectory points based on the first distance;

[0175] The farthest real trajectory point is determined from the real trajectory points based on the first distance corresponding to the nearest false trajectory point;

[0176] The trajectory similarity is determined based on the first distance corresponding to the farthest true trajectory point.

[0177] In an alternative approach, the executable instructions cause the privacy data protection device to perform the following operations:

[0178] The response data is split according to the secret sharing algorithm to obtain multiple sub-secret data;

[0179] Data restoration is performed based on the multiple sub-secret data to obtain the target query result.

[0180] In an alternative approach, the executable instructions cause the privacy data protection device to perform the following operations:

[0181] The response data is split using an LBS server to obtain multiple sub-secret data items;

[0182] Each of the sub-secret data is sent to multiple edge servers connected to the LBS server.

[0183] In an alternative approach, the executable instructions cause the privacy data protection device to perform the following operations:

[0184] The sub-secret data is decrypted by each of the edge servers to obtain multiple decrypted sub-secret data.

[0185] Data is restored based on all the decrypted sub-secret data to obtain the target query result.

[0186] The specific working process of the computer storage medium provided in this embodiment of the invention is largely the same as the specific method steps in the above method embodiments, and will not be repeated here.

[0187] The computer storage medium provided in this embodiment of the invention obtains an original query request, which includes the user's actual movement trajectory and request data. Then, it generates a target query request based on the target movement trajectory and request data. The target movement trajectory is determined from multiple fake movement trajectories corresponding to the actual movement trajectory based on trajectory similarity, thereby effectively protecting the user's actual movement trajectory from being leaked and making it difficult to reverse engineer. Then, it determines the response data corresponding to the target query request. Based on the response data, it determines the target query result and finally returns the target query result to the user.

[0188] Unlike existing technologies that lack correlation analysis between false and real trajectories, making it easier to reverse-engineer the real trajectory from the false trajectory, which could compromise the security of users' location privacy data, the computer storage medium in this invention determines the target movement trajectory from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity, and replaces the real movement trajectory in the query request with the target movement trajectory, thereby improving the security of privacy data.

[0189] This invention provides a privacy data protection device for performing the above-described privacy data protection method.

[0190] This invention provides a computer program that can be invoked by a processor to cause a privacy data protection device to execute the privacy data protection method in any of the above method embodiments.

[0191] This invention provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions that, when executed on a computer, cause the computer to perform the privacy data protection method in any of the above method embodiments.

[0192] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, the embodiments of the present invention are not directed to any particular programming language. It should be understood that the content of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0193] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0194] Similarly, it should be understood that, in order to streamline the invention and aid in understanding one or more of the various aspects of the invention, features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the above description of exemplary embodiments of the invention. However, this disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim.

[0195] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0196] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A method for protecting privacy data, characterized in that, The method includes: Obtain the original query request; the original query request includes the user's actual movement trajectory and request data; the actual movement trajectory includes multiple actual trajectory points; Determine the reachable location set corresponding to each of the real trajectory points; the reachable location set includes multiple query hotspot locations corresponding to the real trajectory points; construct an undirected graph based on the reachable location set to obtain a false movement trajectory; A target query request is generated based on the target movement trajectory and the request data; the target movement trajectory is determined from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity; the false movement trajectory includes multiple false trajectory points; the number of false trajectory points is compared with the number of real trajectory points to obtain a comparison result; when the comparison result is the same, the distances corresponding to each pair of trajectory points are determined; each pair of trajectory points includes false trajectory points and real trajectory points with the same trajectory point order; the trajectory similarity is determined based on the distances of all the trajectory point pairs; when the comparison result is different, a first distance is calculated between each false trajectory point and each real trajectory point; the nearest false trajectory point is determined from the false trajectory points based on the first distance; the farthest real trajectory point is determined from the real trajectory points based on the first distance corresponding to the nearest false trajectory point; the trajectory similarity is determined based on the first distance corresponding to the farthest real trajectory point. Determine the response data corresponding to the target query request; The target query result is determined based on the response data, and the target query result is returned to the user.

2. The method according to claim 1, characterized in that, The step of determining the target query result based on the response data and returning the target query result to the user includes: The response data is split according to the secret sharing algorithm to obtain multiple sub-secret data; Data restoration is performed based on the multiple sub-secret data to obtain the target query result.

3. The method according to claim 2, characterized in that, The secret sharing of the response data yields multiple sub-secret data, including: The response data is split using an LBS server to obtain multiple sub-secret data items; Each of the sub-secret data is sent to multiple edge servers connected to the LBS server.

4. The method according to claim 3, characterized in that, The step of restoring the data based on the multiple sub-secret data to obtain the target query result includes: The sub-secret data is decrypted by each of the edge servers to obtain multiple decrypted sub-secret data. Data is restored based on all the decrypted sub-secret data to obtain the target query result.

5. A privacy data protection device, characterized in that, The device includes: The acquisition module is used to acquire the original query request; the original query request includes the user's actual movement trajectory and request data; the actual movement trajectory includes multiple actual trajectory points; A module for determining the reachable location set corresponding to each of the real trajectory points; the reachable location set includes multiple query hotspot locations corresponding to the real trajectory points; and a module for constructing an undirected graph based on the reachable location set to obtain the false movement trajectory. A generation module is used to generate a target query request based on the target movement trajectory and the request data; the target movement trajectory is determined from multiple false movement trajectories corresponding to the real movement trajectory based on trajectory similarity; the false movement trajectory includes multiple false trajectory points; the number of false trajectory points is compared with the number of real trajectory points to obtain a comparison result; when the comparison result is the same, the distances corresponding to each pair of trajectory points are determined; each pair of trajectory points includes false trajectory points and real trajectory points with the same trajectory point order; the trajectory similarity is determined based on the distances of all the pair of trajectory points; when the comparison result is different, a first distance is calculated between each false trajectory point and each real trajectory point; the nearest false trajectory point is determined from the false trajectory points based on the first distance; the farthest real trajectory point is determined from the real trajectory points based on the first distance corresponding to the nearest false trajectory point; the trajectory similarity is determined based on the first distance corresponding to the farthest real trajectory point. The determination module is used to determine the response data corresponding to the target query request; The return module is used to determine the target query result based on the response data and return the target query result to the user.

6. A privacy data protection device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the operation of the privacy data protection method as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The storage medium stores at least one executable instruction, which, when executed on the privacy data protection device, causes the privacy data protection device to perform the operation of the privacy data protection method as described in any one of claims 1-4.

Images