A privacy-preserving spatiotemporal contact tracing method
By converting location information into a three-dimensional spatial coordinate system and adopting the Paillier encryption algorithm, combined with a two-dimensional multi-layer tree structure and dual-server collaborative computing, the difficult problems of trajectory comparison and calculation in spatiotemporal contact tracing are solved, and a balance between security and availability is achieved.
Patent Information
- Application Number
- CN202311491115.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-11-10
- Publication Date
- 2025-09-30
- Estimated Expiration
- 2043-11-10
AI Technical Summary
Existing technologies cannot achieve the availability of encrypted trajectories while ensuring data security, especially in spatiotemporal contact tracing, and cannot effectively perform trajectory comparison and calculation operations.
By converting the location information into a three-dimensional spatial coordinate system and adopting the Paillier encryption algorithm, a two-dimensional multi-layer tree structure is established, and the trajectory comparison algorithm is calculated collaboratively by dual servers to achieve comparison and tracing of the encrypted trajectory.
It achieves efficient trajectory comparison and tracing while ensuring data security, reduces the complexity and computational overhead of dense distance calculation, and meets the needs of large-scale applications.
Smart Images
Figure CN117688599B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the fields of cloud computing and privacy computing, and in particular to a privacy-preserving spatiotemporal contact tracing method. Background Art
[0002] Homomorphic encryption is a type of encryption method with unique properties. The decrypted data produced by homomorphic encryption is identical to the original, unencrypted data processed using the same method. Homomorphic encryption not only provides security but also, to a certain extent, ensures the availability of encrypted data.
[0003] Spatiotemporal contact tracing methods involve multiple key technologies. During the collection and analysis of spatiotemporal contact data, user data involves private personal information. Leakage of this information can cause significant distress to individuals and raise legal compliance issues. Data encryption methods designed with symmetric cryptography offer high security. However, encrypted tracings cannot be compared or used for computational operations, rendering contact tracing impossible and impairing usability. Unfortunately, no effective solution currently offers both security and usability. Summary of the Invention
[0004] To solve the technical problems existing in the prior art, the present invention provides a privacy-preserving spatiotemporal contact tracing method. The present invention can collaboratively calculate and query the user's contact with sensitive groups through dual servers based on a trajectory comparison algorithm. It can perform calculation operations such as comparison on encrypted trajectories to achieve the function of tracing contacts, and has security and usability.
[0005] The present invention can be achieved by adopting the following technical solutions:
[0006] A privacy-preserving spatiotemporal contact tracing method, comprising:
[0007] Collect the user's location information through the user terminal device, convert the location information into a three-dimensional space coordinate system, and obtain the encoded location trajectory information;
[0008] Encrypt the encoded location trajectory information and upload it to the server;
[0009] Obtain the encrypted trajectory information of sensitive people and establish a two-dimensional multi-layer tree structure based on the encrypted trajectory information of sensitive people;
[0010] Based on a two-dimensional multi-layer tree structure and the encrypted trajectory information uploaded by the query user, dual servers collaborate to calculate the contact situation between the query user and sensitive groups according to the trajectory comparison algorithm and output the contact tracing results.
[0011] Specifically, the user's location information includes longitude, latitude, and altitude information of the location.
[0012] Specifically, the converting and encoding the position trajectory information into a three-dimensional space coordinate system specifically includes: converting and encoding the position information into a three-dimensional space coordinate system to obtain x, y, and z coordinates according to the following formula, and obtaining the encoded position information based on the x, y, and z coordinates:
[0013] a=6378245.0
[0014] e 2 =0.00669342162296594323
[0015]
[0016] x=(n+alt)cos lat cos long
[0017] y=(n+alt)cos lat sin long
[0018] z=(n(1-e 2 )+alt)sin lat
[0019] loc=[x,y,z,x 2 ,y 2 ,z 2 ]
[0020] Among them, lat represents latitude, long represents longitude, alt represents height, n represents an intermediate value, x, y, z represent the converted three-dimensional coordinates, and loc represents the encoded location information
[0021] Specifically, encrypting the encoded location trajectory information and uploading it to the cloud server includes:
[0022] Encrypting the encoded position trajectory information, using the Paillier encryption algorithm to encrypt each value in the three-dimensional position coordinates to form encrypted position trajectory information;
[0023] Upload the encrypted location trajectory information to the server and wait for the server to complete contact tracing and return the results.
[0024] Specifically, the server side establishes a two-dimensional multi-layer tree structure based on the encrypted location information of sensitive people, including: the server side classifies the trajectory information of sensitive people according to time, performs a tree building operation on the location in each time slice, connects the location information of each person to form a trajectory, and the trees established in all time slices together constitute a two-dimensional multi-layer tree structure.
[0025] Specifically, performing a tree building operation on the position in each time slice includes:
[0026] Establish horizontally, select the center point of the time slice and randomly select a position as the center point among all the positions of a certain time slice.
[0027] For other positions in the time slice, calculate the distance between each position and the center point in turn, sort the positions in the time slice according to the distance between each position and the center point, and obtain a one-dimensional tree of the distance dimension;
[0028] Establish vertically,connect the positions of the same trajectory in different time slices, and sort them by time to obtain a one-dimensional tree in the time dimension;
[0029] According to the location information, the one-dimensional tree of the distance dimension and the one-dimensional tree of the time dimension are merged to obtain a two-dimensional tree structure.
[0030] Specifically, the trajectory comparison algorithm includes a comparison algorithm in a horizontal tree and a clipping algorithm in a vertical tree. The comparison algorithm in the horizontal tree includes the following steps:
[0031] The server compares each position in the trajectory uploaded by the user with the horizontal tree of the corresponding time slice;
[0032] Calculate the center distance, and calculate the distance between the user position and the center position of the horizontal tree of the corresponding time slice.
[0033] Obtaining positions to be compared in the horizontal tree. Since positions in the horizontal tree are sorted by distance, several adjacent positions in the horizontal tree are obtained based on the distance between the user position and the center position of the horizontal tree in the corresponding time slice. These positions are defined as the positions to be compared in the horizontal tree.
[0034] Compare positions: compare the user's position with positions that may be in contact with the user's position. If the distance between them is less than the set threshold, it is determined that there is contact and the contact result is returned.
[0035] The pruning algorithm in a vertical tree consists of the following steps:
[0036] When comparing the location uploaded by the querying user with the location to be compared in the horizontal tree, if the distance between the location uploaded by the querying user and the location to be compared in the horizontal tree exceeds a set threshold, the information of the vertical tree is used to mark the adjacent location in the tree as not requiring comparison.
[0037] Compared with the prior art, the present invention achieves the following beneficial effects:
[0038] This invention provides a privacy-preserving spatiotemporal contact tracing method. By innovatively proposing a trajectory information encoding method, real-time location information is converted and encoded into a three-dimensional spatial coordinate system, resulting in encoded location trajectory information. This overcomes the high complexity and computational overhead of dense distance calculations. A two-dimensional, multi-layered tree structure further reduces unnecessary computational overhead, meeting the needs of large-scale applications. Based on the two-dimensional, multi-layered tree and the encrypted trajectory information uploaded by the query user, dual servers collaborate using a trajectory comparison algorithm to calculate the user's contact with sensitive individuals and output contact tracing results. Computational operations such as comparison of the encrypted trajectories enable contact tracing, ensuring both security and usability. BRIEF DESCRIPTION OF THE DRAWINGS
[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.
[0040] Figure 1 1 is a flow chart of a privacy-preserving spatiotemporal contact tracing method according to an embodiment of the present invention;
[0041] Figure 2 Schematic diagram of an application system in an embodiment of the present invention. DETAILED DESCRIPTION
[0042] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It is obvious that the embodiments described are only some embodiments of the present invention, not all embodiments, and the implementation of the present invention is not limited to these. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.
[0043] Example 1:
[0044] The technical problem to be solved by the present invention is the problem of privacy-preserving spatiotemporal contact tracing calculation. The trajectory information is encrypted based on homomorphic encryption technology, and the ciphertext has computable characteristics, providing a theoretical basis for subsequent calculations. However, in practical applications, there are technical difficulties due to the high overhead of ciphertext calculation. The present invention proposes a three-dimensional coordinate conversion method and a position information encoding method, which greatly reduces the amount of calculation of the ciphertext trajectory distance. At the same time, for large-scale application scenarios, a two-dimensional multi-layer tree structure is designed, and an optimized tracing algorithm is designed. Based on the above optimized tracing algorithm, the present invention establishes a spatiotemporal contact tracing fast calculation system that also includes distributed multi-server privacy protection. Among them, the distributed multi-server provides storage of ciphertext trajectories and tracing calculation-related operations. The user-end device is responsible for interacting with the user, recording and encoding trajectory information, encrypting trajectory information and uploading, and other operations.
[0045] like Figure 1 As shown, the present invention provides a privacy-preserving spatiotemporal contact tracing fast calculation method, which includes the following steps:
[0046] S1. Encode trajectory information: collect the user's real-time location information through the user terminal device to obtain location trajectory information, and convert the location trajectory information into a three-dimensional space coordinate system.
[0047] like Figure 2 Figure 2 shows a schematic diagram of an application system in an embodiment of the present invention. Users use devices such as mobile phones and smartwatches to collect their own location trajectory information, which is then encoded and encrypted and uploaded to dual servers. The servers collaborate to execute a privacy-preserving spatiotemporal contact tracing algorithm and output the tracing results. This includes establishing horizontal and vertical two-dimensional tree structures based on the trajectory information of sensitive individuals, as well as performing horizontal comparison and vertical pruning of user trajectory information based on the two-dimensional tree structure.
[0048] Specifically, the user's real-time location information, including longitude, latitude, and altitude, is collected through the user's terminal device. To efficiently calculate distance, this location information is converted and encoded into a three-dimensional spatial coordinate system using the following formula, resulting in x, y, and z coordinates. Distance calculations in longitude and latitude coordinates involve calculating distances on an elliptical surface, while distance calculations in the three-dimensional xyz coordinate system are simpler and more efficiently implemented in the dense state algorithm.
[0049] The position trajectory information is converted and encoded into a three-dimensional space coordinate system, specifically including: converting the position information into a three-dimensional space coordinate system to obtain x, y, and z coordinates using the following formula, and obtaining encoded position information based on the x, y, and z coordinates:
[0050] a=6378245.0
[0051] e 2=0.00669342162296594323
[0052]
[0053] x=(n+alt)cos lat cos long
[0054] y=(n+alt)cos lat sin long
[0055] z=(n(1-e 2 )+alt)sin lat
[0056] loc=[x,y,z,x 2 ,y 2 ,z 2 ]
[0057] Among them, lat represents latitude, long represents longitude, alt represents altitude, n represents an intermediate value, x, y, and z represent the converted three-dimensional coordinates, and loc represents the encoded location information. Users need to encode all location information in this step.
[0058] S2. Encrypt the encoded location trajectory information and upload it to the cloud server.
[0059] S2.1 encrypts the encoded position trajectory information and uses the Paillier encryption algorithm to encrypt each value in the three-dimensional position coordinates to form the encrypted position trajectory information. The Paillier encryption algorithm is expressed as:
[0060]
[0061] Among them, m represents the number to be encrypted, r is a randomly generated random number, g, N represents the public key, and the public key is publicly obtained by the server.
[0062] S2.2 is uploaded to the server. After the user completes the encryption of all location information, it uploads the encrypted location trajectory information to the server and waits for the server to complete the contact tracing and return the results.
[0063] The encryption step and the upload step are formally expressed as:
[0064]
[0065] in, Indicates the encrypted location information, encrypt([x,y,z,x 2 ,y 2 ,z 2 ]) indicates that the location is encrypted using homomorphic encryption operations, Indicates uploading a file to the server.
[0066] S3. Obtain the encrypted trajectory information of the sensitive population, and establish a two-dimensional multi-layer tree structure based on the encrypted trajectory information of the sensitive population.
[0067] After receiving the encrypted trajectory information uploaded by all users, the server divides the user's encrypted trajectory information into trajectory information for sensitive groups and trajectory information for non-sensitive groups. Sensitive groups can be defined differently depending on the actual application field. The server obtains the encrypted location information of sensitive groups and establishes a two-dimensional multi-layer tree structure based on this encrypted location information. The trajectory information of sensitive groups is used to build the two-dimensional multi-layer tree structure in this step, while the trajectory information of non-sensitive groups is used to compare and trace the user's encrypted trajectory information in step S4. Because the trajectory information used to build the two-dimensional tree is pre-obtained from sensitive groups and can be reused, this step can be performed offline before step 1, improving system execution speed.
[0068] Specifically, the server builds a two-dimensional, multi-layered tree structure based on the encrypted location information of sensitive individuals. The server categorizes the sensitive individuals' trajectory information by time, builds a tree for each time slice, and naturally connects each person's location information to form a trajectory. The trees built across all time slices together form a two-dimensional, multi-layered tree structure. This two-dimensional, multi-layered tree structure is then used for subsequent contact tracing queries between other users' trajectories and the trajectories contained in the tree.
[0069] Establishing a two-dimensional multi-layer tree structure is formally expressed as:
[0070]
[0071] Among them, tree represents the established two-dimensional multi-layer tree. Indicates encrypted location information, Indicates that all encrypted location information is used for tree building.
[0072] Specifically, the process of performing the tree building operation on the position in each time slice includes:
[0073] Establish horizontally, select the center point of the time slice and randomly select a position from all the positions in a time slice as the center point. For other positions in the time slice, calculate the distance from each position to the center point in turn, and sort the positions in the time slice according to the distance from each position to the center point to obtain a one-dimensional tree of the distance dimension.
[0074] The horizontal establishment is formally expressed as:
[0075]
[0076] in, Represents all encrypted location information in time slice ime1, Indicates that the encrypted location information is sorted by distance. Represents the horizontally ordered array of encrypted position information.
[0077] Establish vertically, connect the positions of the same trajectory in different time slices, and sort them by time to obtain a one-dimensional tree in the time dimension.
[0078] Since the trajectory information consists of a series of locations sorted by time, that is, sorted by time, a one-dimensional tree of the time dimension is obtained. The vertical establishment is formally expressed as:
[0079]
[0080] in, express All encrypted location information, Indicates that the encrypted location information is sorted by time. Represents the established vertically ordered array of encrypted location information.
[0081] According to the location information, the one-dimensional tree of the distance dimension and the one-dimensional tree of the time dimension are merged to obtain a two-dimensional tree structure.
[0082] Since the "one-dimensional tree of distance dimension" and the "one-dimensional tree of time dimension" obtained in the above steps are obtained according to different sorting of positions, the two trees are merged according to the position information to obtain a two-dimensional tree structure.
[0083] Building a two-dimensional multi-layer tree is formally expressed as:
[0084]
[0085] in Represents the horizontal ordered array established under all time slices, The vertical ordered array established by all participants represents the total number of nodes, and the horizontal and vertical ordered arrays together form a two-dimensional multi-layer tree.
[0086] S4. Based on the two-dimensional multi-layer tree and the encrypted trajectory information uploaded by the query user, the two servers collaboratively calculate the contact situation between the query user and the sensitive population according to the trajectory comparison algorithm and output the contact tracing results.
[0087] Because the present invention utilizes Paillier homomorphic encryption, a dual-server architecture is employed to calculate encrypted trajectory information. This dual-server architecture comprises two servers: one responsible for collecting and calculating trajectory information, and the other assisting in trajectory calculation. Upon receiving the user's uploaded trajectory, the server compares it with a previously generated two-dimensional, multi-layered tree of sensitive population trajectories. If the user's trajectory comes into contact with a sensitive population in the tree, the system outputs a contact tracing result. Specifically, the output contact tracing result includes the encrypted contact location, the encrypted contact occurrence time, and the encrypted contact trajectory number.
[0088] This process is formally expressed as:
[0089]
[0090] Among them, result represents the calculated contact result, Indicates querying the encrypted trajectory information uploaded by the user, tree is a two-dimensional multi-layer tree of sensitive groups, and compare indicates the trajectory comparison algorithm.
[0091] In detail, the trajectory comparison algorithm includes a comparison algorithm in the horizontal tree and a pruning algorithm in the vertical tree, where:
[0092] The comparison algorithm in the horizontal tree consists of the following steps:
[0093] The server compares each position in the trajectory uploaded by the user with the horizontal tree of the corresponding time slice;
[0094] Calculate the center distance, and calculate the distance between the user position and the center position of the horizontal tree of the corresponding time slice.
[0095] Obtaining positions to be compared in the horizontal tree. Since positions in the horizontal tree are sorted by distance, several adjacent positions in the horizontal tree are obtained based on the distance between the user position and the center position of the horizontal tree corresponding to the time slice. The several positions are defined as the positions to be compared in the horizontal tree. The positions to be compared in the horizontal tree are positions that may be in contact with the user position.
[0096] Compare positions. The user's position is compared one by one with the positions in the horizontal tree to be compared. If the distance between them is less than the set threshold, it is determined to be in contact and a contact result is returned. Other positions in the tree do not need to be compared with the user's position, saving a lot of comparison time.
[0097] The comparison algorithm in the horizontal tree is formally expressed as:
[0098]
[0099]
[0100]
[0101] in, represents a horizontal tree, Indicates the encrypted location of the query user. Indicates the distance d between the user's encrypted position and the horizontal tree. Indicates that the locations that may be in contact are extracted based on the calculated distance d. It means comparing the encrypted location of the querying user with each possible contact location to determine whether they are in contact and obtain the result.
[0102] The pruning algorithm in a vertical tree consists of the following steps:
[0103] The pruning algorithm in the vertical tree is formally expressed as:
[0104]
[0105]
[0106] in, They represent the location in the tree and the location uploaded by the query user, respectively. Threshold represents the threshold set by the system. Indicates that the distance between the location in the tree and the location uploaded by the query user is greater than the threshold set by the system. Indicates that the information in the vertical tree is used to mark adjacent positions in the tree as not requiring comparison.
[0107] Because the locations in trajectory information are continuous, the distance between locations at adjacent times cannot exceed a certain threshold. Therefore, based on the pruning algorithm in the vertical tree, when comparing the user's location with locations in the tree, if the distance between two locations exceeds a set threshold, the threshold is selected based on the actual situation. In this case, their trajectories in adjacent time periods cannot intersect. In this case, based on the ordering of the vertical tree, the two adjacent locations are marked as not requiring comparison. The algorithm skips these marked locations during execution, saving a significant amount of comparison time.
[0108] In summary, this invention provides a privacy-preserving spatiotemporal contact tracing method. By innovatively proposing a trajectory information encoding method, real-time location information is converted and encoded into a three-dimensional spatial coordinate system, resulting in encoded location trajectory information. This overcomes the high computational complexity and overhead of dense distance calculations. A two-dimensional, multi-layered tree structure further reduces unnecessary computational overhead, meeting the needs of large-scale applications. Based on the two-dimensional, multi-layered tree and the encrypted trajectory information uploaded by the query user, dual servers collaborate using a trajectory comparison algorithm to calculate the user's contact with sensitive individuals and output contact tracing results. Computational operations such as comparison of the encrypted trajectories enable contact tracing, ensuring both security and usability.
[0109] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be considered as equivalent replacement methods and are included in the scope of protection of the present invention.
Claims
1. A privacy-preserving spatiotemporal contact tracing method, characterized in that: The following steps are involved: Collect the user's location information through the user terminal device, convert the user's location information into a three-dimensional space coordinate system, and obtain the encoded location trajectory information; Encrypt the encoded location trajectory information and upload it to the server; Obtain the encrypted trajectory information of sensitive people and establish a two-dimensional multi-layer tree structure based on the encrypted trajectory information of sensitive people; Based on a two-dimensional multi-layer tree structure and the encrypted trajectory information uploaded by the query user, the two servers collaboratively calculate the contact situation between the query user and sensitive groups according to the trajectory comparison algorithm and output the contact tracing results; The trajectory comparison algorithm includes a comparison algorithm in the horizontal tree and a pruning algorithm in the vertical tree, wherein: The comparison algorithm in the horizontal tree consists of the following steps: The server compares each position in the trajectory uploaded by the user with the horizontal tree of the corresponding time slice; Calculate the center distance, which is the distance between the user position and the center position of the horizontal tree of the corresponding time slice; Obtaining positions to be compared in the horizontal tree. Since positions in the horizontal tree are sorted by distance, several adjacent positions in the horizontal tree are obtained based on the distance between the user position and the center position of the horizontal tree in the corresponding time slice. These positions are defined as the positions to be compared in the horizontal tree. Compare positions: compare the user's position with positions that may be in contact with the user's position. If the distance between them is less than the set threshold, it is determined that there is contact and the contact result is returned. The pruning algorithm in a vertical tree consists of the following steps: When comparing the location uploaded by the querying user with the location to be compared in the horizontal tree, if the distance between the location uploaded by the querying user and the location to be compared in the horizontal tree exceeds a set threshold, the information of the vertical tree is used to mark the adjacent location in the tree as not requiring comparison.
2. A privacy-preserving spatiotemporal contact tracing method according to claim 1, characterized in that: The user's location information includes: longitude, latitude and altitude information of the location.
3. A privacy-preserving spatiotemporal contact tracing method according to claim 1, characterized in that: The converting and encoding the user's location information into a three-dimensional space coordinate system to obtain the encoded location trajectory information specifically includes: converting and encoding the location information into a three-dimensional space coordinate system to obtain x, y, and z coordinates using the following formula, and obtaining the encoded location information based on the x, y, and z coordinates: ； ； ； ； ； ； ； Among them, lat represents latitude, long represents longitude, alt represents altitude, n represents an intermediate value, x, y, z represent the converted three-dimensional coordinates, and loc represents the encoded location information.
4. The privacy-preserving spatiotemporal contact tracing method according to claim 1, characterized in that: The step of encrypting the encoded position trajectory information and uploading it to the server includes: Encrypting the encoded position trajectory information, using the Paillier encryption algorithm to encrypt each value in the three-dimensional position coordinates to form encrypted position trajectory information; Upload the encrypted location trajectory information to the server and wait for the server to complete contact tracing and return the results.
5. The privacy-preserving spatiotemporal contact tracing method according to claim 1, characterized in that: The method of establishing a two-dimensional multi-layer tree structure based on the encrypted trajectory information of sensitive people includes: the server classifies the trajectory information of sensitive people according to time, performs a tree building operation on the position in each time slice, connects the position information of each person to form a trajectory, and the trees built in all time slices together form a two-dimensional multi-layer tree structure.
6. A privacy-preserving spatiotemporal contact tracing method according to claim 5, characterized in that: The performing of the tree building operation on the position in each time slice includes: Establish horizontally, select the center point of the time slice and randomly select a position as the center point among all the positions of a certain time slice. For other positions in the time slice, calculate the distance between each position and the center point in turn, sort the positions in the time slice according to the distance between each position and the center point, and obtain a one-dimensional tree of the distance dimension; Establish vertically,connect the positions of the same trajectory in different time slices, and sort them by time to obtain a one-dimensional tree in the time dimension; According to the location information, the one-dimensional tree of the distance dimension and the one-dimensional tree of the time dimension are merged to obtain a two-dimensional tree structure.