Method, device and computer program product for anonymizing data

Abstract

A method, apparatus, and computer program product for anonymizing data within a database on a server are provided. Data acquired from the vehicle is stored in a database of the server. And removing the vehicle identification number from the data in the database. At least one particular parameter included in the data within the database is altered to generate anonymized data. A user is provided with access to the anonymized data. One or more files for simulation are generated using the anonymized data.

Description

Technical Field

[0001] The present disclosure relates to a method, apparatus, and computer program product for anonymizing data in a database on a server. Background Art

[0002] Market demand for intelligent driving features is growing, and safety is a key factor in gaining customer trust in intelligent driving. Safety testing includes on-site testing, general road performance verification, and virtual verification in the early stages of development. The degree of simulation in virtual scenarios determines the comprehensiveness of safety performance verification for advanced driver assistance systems (ADAS) and autonomous driving systems. The current development process for ADAS and autonomous driving systems involves MIL (model in the loop), SIL (software in the loop), HIL (hardware in the loop), DIL (driver in the loop), and VIL (whole vehicle in the loop). Driving scenario libraries are a crucial component of the development process and are implemented throughout. Therefore, it is crucial to establish comprehensive scenarios that closely resemble real-world traffic conditions.

[0003] Autonomous vehicle (AV) systems are complex and require a reliable testing and validation framework to support engineers. Well-defined processes and infrastructure can be used for software development to avoid errors in the code and maintain quality over time, especially for a large developer base. Automatic regressions captured through continuous integration are an integral part of ensuring overall reliability by regularly testing the relevant functions of the software. The dynamic content of the scenarios used in virtual test drive simulations can be described using OpenScenario files. OpenScenario provides data models, specifications and examples related to describing dynamic content in driving simulations. OpenScenario is used for driving simulations, traffic simulations, virtual development, testing and validation of driver assistance features, automated and autonomous driving. OpenScenario files describe entities that move on or interact with the road. The dynamic content of the scenario includes information such as the movement of vehicles, pedestrians, infrastructure, edge devices, and traffic entities such as bicycles.

[0004] Scenario files in the OpenScenario format have a variety of uses, including use in continuous integration (CI) testing and simulation in local / cloud environments. Through continuous integration, iterations can support the construction of the system and the release of deployment artifacts to the artifact repository. For example, the Market Data Collection (MDC) server stores data acquired by the vehicle's sensors while driving. In order to generate OpenScenario files for simulation, access to the data is required. However, the data in the database on the MDC server includes confidential L4 (highly confidential) data such as timestamp information, namely PII (Personally Identifiable Information). PII is any information related to an individual, including any information that can be used to identify or track an individual's identifying information, and any other information that is linked to or can be linked to an individual. Therefore, the L4 data in the MDC database can only be accessed by users with special permissions, and OpenScenario files cannot be generated based on data containing PII. Summary of the Invention

[0005] In at least one embodiment, a method for anonymizing data in a database on a server includes: storing data obtained from a vehicle in the database; removing a vehicle identification number from the data in the database; and changing at least one specific parameter included in the data in the database to generate anonymized data.

[0006] In at least one embodiment, a device for anonymizing data includes: a memory storing computer-readable instructions; and a processor connected to the memory, the processor being configured to execute the computer-readable instructions to perform the following actions: removing a vehicle identification number from data in a database stored on a server; and changing at least one specific parameter included in the data in the database to generate anonymized data.

[0007] In at least one embodiment, a computer program product includes a computer program, wherein when the computer program is executed by a processor, the computer program causes the processor to perform the following actions: store data obtained from a vehicle in a database; remove the vehicle identification number from the data in the database; and change at least one specific parameter included in the data in the database to generate anonymized data. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The present invention will be best understood by reading the following detailed description using the accompanying drawings. It should be noted that, according to industry practice, the various features are not drawn to scale. In fact, the dimensions of the various features may be increased or decreased to make the description more clear.

[0009] Figure 1 is a flow diagram of a process associated with the generation and use of simulation files of at least one embodiment.

[0010] Figure 2 is an overview of data anonymization in accordance with at least one embodiment.

[0011] Figure 3 This is a diagram illustrating the operation of a vehicle data API (Application Programming Interface) in at least one embodiment.

[0012] Figure 4 is a flow chart of a method of anonymizing data to generate a simulation file in accordance with at least one embodiment.

[0013] Figure 5 is a high-level functional block diagram of a processor-based system of at least one embodiment. DETAILED DESCRIPTION

[0014] The embodiments described in this specification record examples of various features that realize the provided subject matter. In order to simplify the present disclosure, examples related to constituent elements, values, actions, materials, configurations or similar things are recorded below. Of course, these are examples and are not intended to be limiting. Other constituent elements, values, actions, materials, configurations or similar things can be assumed. For example, the formation of a first feature above or on a second feature in the following description includes an embodiment in which the first feature and the second feature are directly in contact and formed, and an embodiment in which another feature is formed between the first feature and the second feature in a manner that the first feature and the second feature cannot directly contact each other. In addition, the present disclosure repeats reference numerals and / or reference characters in various examples. The purpose of this repetition is to simplify and clarify, rather than to stipulate the relationship between the various embodiments and / or configurations described.

[0015] In addition, for ease of description, spatially relative terms such as "below," "below," "below," "above," "above," and similar terms are used in this specification to describe the relationship of an element or feature to other elements or features as shown in the figures. Spatially relative terms are intended to include various orientations of the device when in use or in operation, in addition to the orientations depicted in the figures. The spatially relative descriptions used in this specification should be interpreted similarly if the device has different orientations (rotated 90 degrees or other orientations).

[0016] Terms such as "user equipment," "mobile station," "mobile," "mobile device," "subscriber station," "subscriber device," "access terminal," "terminal," "headset," and similar terms refer to wireless devices used by subscribers or users of wireless communication services to receive or transmit data, control, voice, video, speech, gaming, data streams, or signaling flows. These terms are used interchangeably in the subject specification and associated drawings. Terms such as "access point," "base station," "Node B," "enhanced Node B (eNode B)," "next generation Node B (gNB)," "enhanced gNB (en-gNB)," "Home eNodeB (HNB)," "Home Access Point (HAP)," and similar terms refer to wireless network components or devices that provide and receive data, control, voice, video, speech, gaming, data streams, or signaling flows to and from user equipment (UE).

[0017] In at least one embodiment, a method for anonymizing data in a database on a server includes: storing data obtained from a vehicle in a database on the server; removing a vehicle identification number from the data in the database; and changing at least one specific parameter included in the data in the database to generate anonymized data.

[0018] Embodiments described herein provide a method that offers one or more advantages. For example, a vehicle data application programming interface (API) anonymizes data stored in a database on a server by converting highly confidential data into anonymized and protected data by modifying at least one specific parameter contained in the data within the database.

[0019] Figure 1 is a flow diagram of a process associated with the generation and use of simulation file 100 in accordance with at least one embodiment.

[0020] exist Figure 1 In the process, reports / data from the test vehicle are obtained (110). Simulation files and other files are generated based on the reports obtained from the test vehicle (120). Based on the files, test engineers and application developers can use the simulation platform 130 to test the application in a closed-loop software-in-the-loop (SIL) test without access to the actual vehicle. The simulation platform 130 is used to simulate sensors and real data for the test vehicle and its surrounding virtual environment.

[0021] The reports / data from the test vehicles are stored as data in a database on a server such as a Market Data Collection (MDC) server. The data can be raw data or pre-processed data. The data is acquired by the vehicle's sensors while driving. However, the data in the database on the server includes confidential (highly confidential) data such as timestamp information, i.e., PII (Personally Identifiable Information). PII is any information related to an individual, including any information that can be used to identify or track an individual's identifying information, as well as any other information that is linked to or can be linked to an individual. Therefore, the confidential data in the database can only be accessed by users with special permissions, and simulation files such as OpenScenario files cannot be generated based on data containing PII. In order to generate simulation files, in at least one embodiment, the vehicle identification number is removed from the data in the database, and at least one specific parameter contained in the data in the database is changed to generate anonymized data. Requests related to data acquisition are received from the vehicle data application programming interface (API).

[0022] Figure 2 is a schematic diagram of data anonymization 200 according to at least one embodiment.

[0023] exist Figure 2In this example, confidential data 210 containing personally identifiable information is obtained from a vehicle and stored as data 212, such as hashed data, on a server 214. Data 212 can be raw data or pre-processed data. Data 212 on server 214 is data captured by the vehicle's sensors while driving and is not processed through a data lens 216 before being provided to server 214. Data lens 216 enables authorized users 218 to retrieve, search, and interact with data 212 on server 214. The vehicle API has access to data 212. In the context of autonomous driving technology, "vehicle" is a term used to describe a self-driving vehicle equipped with sensors, cameras, and other technologies that enable it to perceive its environment and make decisions. Therefore, the term "vehicle" in this context refers to the vehicle being egocentric or self-referential, meaning that it primarily perceives the world from its own perspective. The vehicle's sensors and cameras focus on detecting objects and obstacles in its immediate surroundings, which is used to provide safe navigation. Authorization thresholds for authorized users 218 are determined by the confidentiality of the data. For example, some users have access to data on server 214 via the vehicle API. Before anonymization, data 212 on server 214 includes a combination of GPS (Global Positioning System) location or coordinate data, a timestamp, and vehicle identification information (ID) that can identify a specific user. To make anonymized data 232 available, data without personally identifiable information (PII) is provided to users 240 who do not have access authorization. Thus, users 240 who do not have access authorization can issue requests related to a subset of data 212 within the database on server 214. Vehicle data API 218 processes event data 216 in a manner that anonymizes the data on server 214 to generate anonymized data 232. Data 212 can be raw data or data that has been processed before anonymization. Anonymized data is data 242 that has been anonymized and protected, and does not include the vehicle identification number (VIN), absolute time, and video / images.

[0024] Without the vehicle data API 218 for anonymizing the data 212 , namely the highly confidential data 220 , the data 212 on the server 214 still has an absolute time stamp, so users cannot use the data to generate files without a high level of access authorization.

[0025] Removing the user's vehicle ID from data 212 makes identification of the user difficult, but identification of the user is still possible based on the location and time stamp in data 212. For example, GPS location can be used together with a time stamp to identify a user passing through a specific area, potentially putting the user's information at risk.

[0026] Therefore, to generate a file, at least one embodiment provides a vehicle data API 218. The vehicle data API 218 retrieves data 212 and converts the data 212 on the server 214 into anonymized data 232 by changing at least one specific parameter contained in a subset of the data 212 on the server 214. A request for retrieving data from the server 214 is received from the vehicle data API 218. The vehicle data API 218 imports the data 212 imported from the test vehicle via the vehicle API. Thus, the vehicle data API 218 enables a user to find and use desired anonymized data 232.

[0027] The vehicle identification number is removed from data 212. Data 212 is anonymized by changing at least one specific parameter in data 212 within server 214 to generate anonymized data 232. Highly confidential data 220 is changed to anonymized data 232 to reduce access restrictions for the user. The change in at least one specific parameter included in the subset of data 212 includes changing the timestamp value of the initial frame from the frames in the data, and setting the timestamp value of the initial frame (e.g., the first event) in the subset of data 212 to time 0 when the next frame in at least one subset of the data has a relative offset from the initial frame. Therefore, when the user does not have access rights to confidential data, the user's permissions can be reduced.

[0028] Anonymized data 232 is generated using the remaining GPS coordinates, which provide information related to the vehicle passing through a specific time and location. Anonymized data 232 is generated using data on the vehicle's movement and location. Anonymized data 232 is generated using data on the vehicle's movement and location, including speed data, acceleration data, latitude data, longitude data, heading data, and relative time offset. Vehicle data API 218 provides access to the vehicle's movement and location data. Generated anonymized data 232 may include one or more of weather data or terrain data.

[0029] The anonymized data 232 is used to generate scenario data, which is used to generate simulation data 234 associated with a file 236. The file 236 is stored in a database (DB) 238. Therefore, users without access authorization can access the data in the DB 238, while only users with access authorization can access the data 212 in the server 214. Figure 2As shown in FIG, the process of acquiring data related to a new dataset or API and associating it with highly confidential data 220 typically takes 1 to 3 months 250. The process of generating anonymized data 230 without PII typically takes 1 to 2 weeks 260. However, those skilled in the art will appreciate that these time frames are provided as examples, and the embodiments described herein are not limited to the time frames disclosed herein.

[0030] Figure 3 is an operational diagram of the vehicle data API 300 according to at least one embodiment.

[0031] exist Figure 3 In the example embodiment, the vehicle API 310 provides access to data on the movement and position of the vehicle (312). Figure 3 Vehicle 330 is shown relative to other vehicles 332, 334, 336. The data regarding the vehicle's motion and position includes vehicle speed 320, vehicle acceleration 322, vehicle location 324 (e.g., latitude and longitude coordinates of the vehicle), vehicle heading 326 (e.g., yaw, yaw rate, pitch, and roll data associated with the vehicle), and relative time offset 328.

[0032] The participant data API 340 provides data ( 342 ) related to objects surrounding the vehicle (eg, other cars, pedestrians, infrastructure, edge devices, etc.). Figure 3 Vehicle 360 ​​is shown, and data corresponding to other vehicles 362, 364, and 366 (participants 370) is obtained through participant data API 340. Data regarding objects surrounding the vehicle and obtained through participant data API 340 includes relative positions 350 of surrounding vehicles, orientations (e.g., yaw) 352 of surrounding vehicles, relative speeds 354 of surrounding vehicles, relative accelerations 356 of surrounding vehicles, and similar data.

[0033] The data obtained from the test vehicle through the vehicle API 310 and the participant data API 340 is stored in a database on the server. The data stored on the server can be raw data or pre-processed data. However, the data in the database on the server includes confidential data such as timestamp information, namely PII (Personally Identifiable Information). PII is any information related to an individual, including any information that can be used to identify or track an individual's identifying information, as well as any other information that is linked to or can be linked to an individual. Therefore, the confidential data in the server's database can only be accessed by users with special permissions, and files cannot be generated based on data containing PII. The event data of at least one embodiment in the database on the server is anonymized data obtained by changing at least one specific parameter contained in a subset of the data in the database on the server to generate a file for simulation. A request related to data acquisition of a subset of the data in the database on the server is received from the vehicle data API 380.

[0034] Connected cars or autonomous vehicles (AVs) use wireless communication technologies to exchange information with other vehicles, edge devices, and infrastructure. Other vehicles, edge devices, and infrastructure provide vehicle sensor data and various road and surrounding information related to autonomous driving. For example, AVs can receive data from other vehicles, edge devices, and infrastructure wirelessly. As described above, the vehicle API 310 provides access to data about the vehicle's movement and position (312), and the participant data API 340 provides data related to objects around the vehicle (e.g., other cars, pedestrians, infrastructure, edge devices, etc.) (342).

[0035] Sensor data acquired by AVs, as well as data from other vehicles and infrastructure, can be used by AVs for autonomous driving. Other vehicles and infrastructure that transmit data to AVs are collectively referred to as edge devices. Sensors in AVs include radar, LiDAR (laser radar), GPS, cameras, and similar devices. Furthermore, sensor data acquired by AVs and data from edge devices can be sent to servers such as MDC servers. Data is sent from edge devices to AVs, and the data sent by AVs can use 5G (5th Generation Mobile Communication Technology) New Radio (NR), 4G (4th Generation Mobile Communication Technology) Long Term Evolution (LTE), LTE-A (Long Term Evolution-Advanced), Worldwide Interoperability for Microwave Access (WiMAX), IEEE802.11, Wi-Fi Wireless Local Area Network (WLAN), Unlicensed LTE (LTE-U), Licensed Assisted Access (LAA), Cellular Device-to-Device (D2D), Vehicle-to-Everything (V2X), Bluetooth, General Packet Radio Service (GPRS), and Wideband Code Division Multiple Access (WCDMA). Multiple Access) or other wireless communication technologies and other wireless protocols are sent wirelessly.

[0036] The vehicle data API 380 anonymizes data from the vehicle API 310 and the participant data API 340 (382). The vehicle data API 380 provides a standardized and documented data model (384) and abstracts complex, diffuse data patterns (386). The vehicle data API 380 improves data quality (388) by selecting the best available sensor data (e.g., yaw, yaw rate, SPI (Serial Peripheral Interface), and CAN (Controller Area Network)).

[0037] Refer again Figure 2 The vehicle data API 218 anonymizes the data 212 from the server 214 to generate anonymized data 232. As a result, the absolute time of the event is not derivable. Therefore, other time-related information cannot be used to infer specific user data because the anonymized data is not sufficient to identify the user or the exact time when the event occurred.

[0038] The removal of timestamps and vehicle IDs enables the user to be anonymized, and the simulation can use frames with a time offset, i.e., delta time. GPS location data can be used to regenerate the vehicle's trajectory. Thus, based on the anonymized data, the simulation team uses file 236 to generate a specification describing what happened to the vehicle, e.g., accurately reproducing what the vehicle would do in real life. Anonymized data 232 anonymizes data 212 from server 214 so that it cannot be traced back to the user.

[0039] Geographic location is important for simulations that use geographic data to determine the overall trajectory shape, so removing or altering location data is inappropriate. The generated anonymized data 232 includes geographic context information. Other factors relevant to the simulation include weather. Another factor is the specific terrain, which can affect the overall shape of the trajectory. Therefore, instead of removing the timestamp, the GPS location could be altered. However, this is more complex than providing anonymization by removing the timestamp information.

[0040] The goal of the simulation is to analyze how the vehicle responds to certain situations. Absolute GPS coordinates are used to correlate geographic contextual information, such as weather. When processing absolute GPS coordinates, external data, such as rain data, can be included in conjunction with the vehicle's own sensed data. When the data is anonymized via the vehicle data API 218 to generate anonymized data 232, weather data can be accessed because it resides in a database maintained by the server 214.

[0041] Anonymized data 232 is used to generate simulation data 234 for generating a file 236, such as a simulation file. File 236 is stored in a database (DB) 238. Therefore, users without access authorization can access the data in DB 238, while only authorized users can access data 212 (L4 data) on server 214. Anonymized data 232 is data 242 that has been anonymized and protected.

[0042] Figure 4 4 is a flow chart diagram of a method of anonymizing data to generate a simulation file in accordance with at least one embodiment.

[0043] exist Figure 4 The method starts (S402) and stores the data acquired from the vehicle in a database on the server (S410). Figure 2 Confidential data 210 containing personal identification information is obtained from the vehicle and stored as data 212, such as hashed data, on a server 214. Data 212 may be raw data or pre-processed data. Data 212 on the server 214 is data acquired by sensors on the vehicle while driving and has not been processed by a data lens 216 before being provided to the server 214.

[0044] Receive a request related to data acquisition from the user (S420). Figure 2 , receives a request for acquiring data from the server 214 from the vehicle data API 218. The vehicle data API 218 imports the data 212 imported from the test vehicle via the vehicle API. Thus, the vehicle data API 218 enables the user to find and use the desired anonymized data 232.

[0045] Remove the vehicle identification number from the data (S430). Figure 2 , remove the vehicle identification number from the data.

[0046] Reference Figure 3 The data acquired from the test vehicle via the vehicle API 310 and the participant data API 340 is stored in a database on the server. The data stored on the server can be raw data or pre-processed data. However, the data in the server database includes confidential data such as timestamp information, namely PII (Personally Identifiable Information). PII is any information related to an individual, including any information that can be used to identify or track an individual, as well as any other information that is linked or linkable to an individual. Therefore, the confidential data in the server database can only be accessed by users with special permissions, and files cannot be generated based on data containing PII.

[0047] At least one specific parameter included in at least one subset of the data is changed to generate anonymized data (S440). Figure 2 The vehicle data API 218 imports the data 212 imported from the test vehicle via the vehicle API. Thus, the vehicle data API 218 enables a user to find and use desired anonymized data 232. The vehicle identification number is removed from the data. The data 212 is anonymized by changing at least one specific parameter in the data 212 within the server 214 to generate anonymized data 232. Highly confidential data 220 is changed to anonymized data 232 to reduce access restrictions for the user. The change in at least one specific parameter included in the subset of data 212 includes changing the timestamp value of the initial frame from the frames in the data, and setting the timestamp value of the initial frame (e.g., the first event) in the subset of data 212 to time 0 when the next frame in at least one subset of the data has a relative offset from the initial frame. Thus, when the user does not have access rights to confidential data, user permissions can be reduced. The remaining GPS coordinates are used to generate anonymized data 232, which provide information related to the vehicle passing through a specific time and location. Anonymized data 232 is generated using vehicle motion and position data. Anonymized data 232 is generated using vehicle motion and position data including speed data, acceleration data, latitude data, longitude data, heading data, and relative time offset. Vehicle data API 218 provides access to vehicle motion and position data. The generated anonymized data 232 may include one or more of weather data and terrain data. The generated anonymized data 232 includes geographic context information. Other factors relevant to the simulation include weather. Another factor is the specific terrain, which can affect the overall shape of the trajectory. Therefore, the GPS location can be altered instead of removing the timestamp. However, this is more complex than providing anonymization by removing the timestamp information. The goal of the simulation is to analyze how the vehicle responds to certain specific situations. Absolute GPS coordinates are used to associate geographic context information, such as weather. When processing absolute GPS coordinates, external data related to the vehicle's own sensed data, such as rain data, can be included. When the vehicle data API 218 anonymizes the data to generate anonymized data 232, weather data is accessible because it is stored in a database maintained by server 214.

[0048] Providing user access to at least one anonymized subset of the data (S450). Figure 2 In order to make the anonymized data 232 available, the data without personally identifiable information (PII) is provided to the user 240 who does not have access authorization. Therefore, the user 240 who does not have access authorization can issue a request related to data acquisition of the data 212 in the database in the server 214.

[0049] At least one anonymized subset of the data is used to generate a simulation file (S460). Figure 2 The anonymized data 232 is used to generate simulation data, which is used to generate simulation data 234 associated with a file 236, such as a simulation file. The file 236 is stored in a database (DB) 238. Based on the anonymized data, the simulation team uses the file 236 to generate a specification that describes what happens to the vehicle, for example, accurately reproducing what the vehicle would do in real life.

[0050] Then, the process ends (S470).

[0051] At least one embodiment of a method for anonymizing data in a database on a server includes: storing data obtained from a vehicle in a database on the server; removing a vehicle identification number from the data in the database; and changing at least one specific parameter included in the data in the database to generate anonymized data.

[0052] Figure 5 is a high-level functional block diagram of a processor-based system 500 in accordance with at least one embodiment.

[0053] In at least one embodiment, processing circuitry 500 anonymizes data to generate a simulation file for a vehicle test simulation. Processing circuitry 500 implements anonymization of data for generating the simulation file using processor 502. Processing circuitry 500 also includes a non-transitory computer-readable storage medium 504 for anonymizing data to generate the simulation file. In particular, non-transitory computer-readable storage medium 504 stores instructions 506, i.e., instructions 506 encoded in the form of computer program code, which are executed by processor 502 to cause processor 502 to perform actions to anonymize data to generate the simulation file. Execution of instructions 506 by processor 502 (at least in part) represents an application to implement at least a portion of the methods described herein (processes and / or methods described below) according to one or more embodiments.

[0054] The processor 502 is electrically connected to a non-transitory computer-readable storage medium 504 via a bus 508. The processor 502 is electrically connected to an input / output (I / O) interface 510 via the bus 508. A network interface 512 is also electrically connected to the processor 502 via the bus 508. The network interface 512 is connected to a network 514, so that the processor 502 and the non-transitory computer-readable storage medium 504 are connected to external components via the network 514. The processor 502 is configured to execute instructions 506 encoded on the non-transitory computer-readable storage medium 504 so as to enable the use of the processing circuit 500 to perform at least a portion of a process and / or method. In one or more embodiments, the processor 502 may be a central processing unit (CPU), a multiprocessor, a distributed processing system, an application-specific integrated circuit (ASIC), and / or a suitable processing unit.

[0055] Processing circuit 500 includes an I / O interface 510. I / O interface 510 is connected to external circuitry. In one or more embodiments, I / O interface 510 includes a keyboard, keypad, mouse, trackball, touchpad, touch screen, and / or cursor direction keys for transmitting information and instructions to processor 502.

[0056] The processing circuit 500 further includes a network interface 512 connected to the processor 502. The processing circuit 500 can communicate with a network 514 connected to one or more other computer systems via the network interface 512. The network interface 512 includes a wireless network interface such as Bluetooth, Wi-Fi, Worldwide Interoperability for Microwave Access (WiMAX), General Packet Radio Service (GPRS), or Wide Area Code Division Multiple Access (WCDMA), or a wired network interface such as Ethernet, Universal Serial Bus (USB), or Institute of Electrical and Electronics Engineers (IEEE) 864.

[0057] Processing circuit 500 is configured to receive information via I / O interface 510. The information received via I / O interface 510 includes one or more of instructions, data, design rules, cell libraries, and / or other parameters processed by processor 502. The information is transmitted to processor 502 via bus 508. Processing circuit 500 is configured to receive information related to a user interface (UI) via I / O interface 510. Information (e.g., confidential data / anonymized data) 522 is stored in non-transitory computer-readable storage medium 504, which serves as UI 520.

[0058] In one or more embodiments, one or more non-transitory computer-readable storage media 504 (in compressed or uncompressed form) stores instructions 506 that can be used to program a computer, processor, or other electronic device to perform a process or method described herein. The one or more non-transitory computer-readable storage media 504 include one or more electronic storage media, magnetic storage media, optical storage media, quantum storage media, or the like.

[0059] For example, the non-transitory computer-readable storage medium 504 may include, but is not limited to, a hard drive, a floppy disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, a magnetic or optical card, a solid-state memory device, or other types of physical media suitable for storing electronic instructions. In one or more embodiments using optical disks, the one or more non-transitory computer-readable storage media 504 include a compact disc read-only memory (CD-ROM), a compact disc recordable / rewritable (CD-R / W), and / or a digital video disk (DVD).

[0060] In one or more embodiments, the non-transitory computer-readable storage medium 504 stores instructions 506 configured to cause the processor 502 to perform at least a portion of a process and / or method for anonymizing data to generate a simulation file. In one or more embodiments, the non-transitory computer-readable storage medium 504 also stores information such as an algorithm that facilitates performing at least a portion of the process and / or method for anonymizing data to generate a simulation file.

[0061] Therefore, in at least one embodiment, processor 502 executes instructions 506 stored on one or more non-transitory computer-readable storage media 504, which anonymize data to generate a simulation file. Processor 502 retrieves confidential data 532 from a vehicle. Processor 502 stores confidential data 532 in a database on server 530. Confidential data 532 may be raw data or pre-processed data. Processor 502 presents vehicle data API 586 for accessing confidential data 532 within the database on server 530. Processor 502 executes request 540 related to data retrieval. Based on request 540 related to data retrieval, processor 502 removes the vehicle identification number from data 532 and alters at least one specific parameter in data 522, thereby generating anonymized data 580. The anonymized subset of data 580 includes at least one of GPS coordinate data 581 providing the time and location of the vehicle, data 582 of the vehicle's motion and location (e.g., speed data, acceleration data, latitude data, longitude data, heading data, and relative time offset), a trajectory 583 of the vehicle, weather data or terrain data 584, or geographic context information 585. Processor 502 uses anonymized data 580 to generate a file 570 for simulation based on the anonymized data. Processor 502 obtains a timestamp value 550 for an initial frame and then sets the initial frame to time 0, with the next frame having a relative offset relative to the initial frame (560).

[0062] Processor 502 uses display 590 to present user interface (UI) 592, which displays confidential data / anonymized data 594. UI 592 enables the user to generate anonymized data 580 by changing at least one parameter included in confidential data 532.

[0063] The embodiments described herein provide a method that offers one or more advantages. For example, a vehicle data API converts highly confidential data into anonymized and protected data by modifying at least one specific parameter contained in the data, thereby anonymizing data stored in a database on a server to generate simulation files.

[0064] The solution of this specification is, for example, a method [1] for anonymizing data in a database on a server by using a processor, wherein the method [1] includes: storing data obtained from a vehicle in a database on the server; removing a vehicle identification number from the data in the database; and changing at least one specific parameter contained in the data in the database to generate anonymized data.

[0065] [2]: The method described in [1] also includes: using anonymized data to generate one or more files for simulation.

[0066] [3]: The method of any one of [1] or [2] further includes: receiving a request related to data acquisition; and providing access to anonymized data.

[0067] [4]: In the method described in [3], receiving a request related to data acquisition includes receiving a request from an application programming interface (API) having access to the server.

[0068] [5]: In the method described in any one of [1] to [4], at least one specific parameter includes a timestamp value.

[0069] [6]: In the method described in [5], the change of the timestamp value includes: changing the timestamp value of the initial frame from the frames in the subset of data, and setting the timestamp value of the initial frame to time 0 when the next frame in the subset of data has a relative offset with respect to the initial frame.

[0070] [7]: In the method described in any one of [1] to [6], the generation of anonymized data includes using data on the movement and position of the vehicle to generate the anonymized data, the data on the movement and position including at least one of speed data, acceleration data, latitude data, longitude data, heading data or relative time offset.

[0071] The solution of this specification is based on a device [8] for anonymizing data in a database on a server, wherein the device [8] includes: a memory storing computer-readable instructions; and a processor connected to the memory, the processor being configured to execute the computer-readable instructions to perform the following actions: removing a vehicle identification number from the data in the database stored on the server; and changing at least one specific parameter contained in the data in the database to generate anonymized data.

[0072] [9]: In the device described in [8], the processor is further configured to: use the anonymized data to generate one or more files for simulation.

[0073]

[10] : In the device described in [8] or [9], the processor is further configured to: receive a request related to data acquisition; and provide access to anonymized data.

[0074]

[11] : In the device described in

[10] , the processor is further configured to: receive a request related to data acquisition from an application programming interface (API) having access to a database on the server.

[0075]

[12] : In the apparatus of any one of [8] to

[11] , at least one specific parameter includes a timestamp value.

[0076]

[13] : In the device described in any one of [8] to

[12] , the data stored in the database includes a subset of data, and the processor is further configured to: change the timestamp value of the initial frame from the frames in the subset of data, and set the timestamp value of the initial frame to time 0 when the next frame in the subset of data has a relative offset with respect to the initial frame, thereby changing the timestamp value.

[0077]

[14] : In the device described in any one of [8] to

[13] , the processor is further configured to: generate anonymized data using data on the movement and position of the vehicle, thereby generating anonymized data, the data on the movement and position including at least one of speed data, acceleration data, latitude data, longitude data, heading data or relative time offset.

[0078] The solution of this specification is based on a computer program product

[15] comprising a computer program, which, when executed by a processor, causes the processor to perform actions including: storing data obtained from a vehicle in a database on a server; removing the vehicle identification number from the data in the database; and changing at least one specific parameter contained in the data in the database to generate anonymized data.

[0079]

[16] : The computer program product described in

[15] also includes: using anonymized data to generate files for simulation.

[0080]

[17] : In the computer program product described in any one of

[15] or

[16] , it also includes: receiving a request related to data acquisition; and providing access to anonymized data.

[0081]

[18] : In the computer program product of any one of

[15] to

[17] , at least one specific parameter includes a timestamp value.

[0082]

[19] : In the computer program product described in

[18] , the change of the timestamp value includes: in the subset of data, changing the timestamp value of the initial frame from the frames in the subset of data, and setting the timestamp value of the initial frame to time 0 when the next frame in the subset of data has a relative offset relative to the initial frame.

[0083]

[20] : In the computer program product described in any one of

[15] to

[19] , the generation of the anonymized data includes using data on the movement and position of the vehicle to generate the anonymized data, the data on the movement and position including at least one of speed data, acceleration data, latitude data, longitude data, heading data or relative time offset.

[0084] Different instances of these programs can be executed on any number of different computer systems, or can be distributed among these computer systems. Therefore, although specific steps are described as being performed by specific devices, software programs, processes, or entities, this is not necessarily the case. Those skilled in the art will appreciate various alternative implementations.

[0085] Furthermore, those skilled in the art will readily appreciate that the above techniques can be applied in a variety of devices, environments, and contexts. Although the embodiments are described using terminology specific to structural features or methodological behaviors, the subject matter defined in the appended claims is not necessarily limited to the specific features or behaviors described. Rather, the specific features and behaviors are disclosed as exemplary ways of implementing the claims. A computer program product including the computer program of the above embodiments may also be stored on a storage medium or distributed via a communication link.

Claims

1. A method for anonymizing data is a method for anonymizing data in a database on a server using a processor, comprising: Storing the data obtained from the vehicle in a database on the server; removing a vehicle identification number from said data in said database; as well as At least one specific parameter included in the data in the database is changed to generate anonymized data.

2. The method according to claim 1, further comprising: The anonymized data is used to generate one or more files for simulation.

3. The method according to claim 1 or 2, further comprising: Receive requests related to data acquisition; as well as Providing access to the anonymized data.

4. The method according to claim 3, wherein: The receiving of the request related to the data acquisition includes receiving the request from an application programming interface (API) having access to the database on the server.

5. The method according to any one of claims 1 to 4, wherein The change of the at least one specific parameter includes a change timestamp value.

6. The method according to claim 5, wherein: The change of the timestamp value includes: in a subset of data, changing the timestamp value of an initial frame from the frames in the subset of data, and setting the timestamp value of the initial frame to time 0 when the next frame in the subset of data has a relative offset with respect to the initial frame.

7. The method according to any one of claims 1 to 6, wherein The generating of the anonymized data includes generating the anonymized data using data of movement and position of the vehicle, the movement and position data including at least one of speed data, acceleration data, latitude data, longitude data, heading data, or relative time offset.

8. A device for anonymizing data, which is a device for anonymizing data in a database on a server, comprising: a memory storing computer-readable instructions; and a processor connected to the memory, The processor is configured to execute the computer-readable instructions to: removing the vehicle identification number from the data stored in the database on the server; and At least one specific parameter included in the data in the database is changed to generate anonymized data.

9. The apparatus according to claim 8, wherein The processor is further configured to use the anonymized data to generate one or more files for simulation.

10. The apparatus according to claim 8 or 9, wherein The processor is further configured to: Receive requests related to data access; and Providing access to said anonymized data.

11. The apparatus according to claim 10, wherein The processor is further configured to receive the request related to the data acquisition from an application programming interface (API) having access to the database on the server.

12. The apparatus according to any one of claims 8 to 11, wherein The at least one specific parameter includes a timestamp value.

13. The apparatus according to any one of claims 8 to 12, wherein The data stored in the database includes a subset of data, and the processor is further configured to: change the timestamp value of an initial frame from the frames in the subset of data, and set the timestamp value of the initial frame to time 0 when the next frame in the subset of data has a relative offset with respect to the initial frame, thereby changing the at least one specific parameter.

14. The apparatus according to any one of claims 8 to 13, wherein The processor is further configured to generate the anonymized data using data of the vehicle's movement and position, the data comprising at least one of speed data, acceleration data, latitude data, longitude data, heading data, or relative time offset.

15. A computer program product comprising a computer program, wherein when the computer program is executed by a processor, the computer program causes the processor to perform actions, the actions comprising: Storing the data obtained from the vehicle in a database on the server; removing a vehicle identification number from said data in said database; as well as At least one specific parameter included in the data in the database is changed to generate anonymized data.

16. The computer program product of claim 15, further comprising: The anonymized data is used to generate files for simulation.

17. The computer program product according to claim 15 or 16, further comprising: Receive requests related to data acquisition; as well as Providing access to said anonymized data.

18. The computer program product according to any one of claims 15 to 17, wherein: The at least one specific parameter includes a timestamp value.

19. The computer program product of claim 18, wherein: The change of the timestamp value includes: in a subset of data, changing the timestamp value of an initial frame from the frames in the subset of data, and setting the timestamp value of the initial frame to time 0 when the next frame in the subset of data has a relative offset with respect to the initial frame.

20. The computer program product according to any one of claims 15 to 19, wherein: The generating of the anonymized data includes generating the anonymized data using data of movement and position of the vehicle, the movement and position data including at least one of speed data, acceleration data, latitude data, longitude data, heading data, or relative time offset.

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