Information processing system capable of performing secure connection related to automatic driving

Abstract

An information processing system includes a control device as a central brain mounted on a vehicle and an information processing device as a security chip. The information processing apparatus includes: an acquisition unit that acquires a type of data processed by the control apparatus; a determination unit that determines whether the type of the data is critical task data or non-critical task data; and a setting unit that sets the control device to connect the critical task data to a secure private cloud and to connect the non-critical task data to a public cloud.

Description

Technical Field

[0001] The present disclosure relates to an information processing system capable of performing a secure connection related to autonomous driving. Background Art

[0002] Japanese Patent Application Publication No. 2022-035198 describes a vehicle with an autonomous driving function. Summary of the invention

[0003] Problems to be solved by the invention

[0004] In current autonomous vehicles, communication is performed without distinguishing the cloud of the connection target based on the data content of the communication.

[0005] Autonomous driving has data required for autonomous driving itself or data with high urgency (critical mission data), as well as data other than that (non-critical mission data). In addition, the critical mission data may include not only the data required for the autonomous driving of the vehicle itself, but also data that is indispensable for the control of terminals or robots managed by the vehicle. Non-critical mission data includes, for example, natural conversation recognition, image recognition, information retrieval, information inference, and other information acquisition that is not classified as data with high urgency (traffic information, weather information, and entertainment information, etc.). In existing autonomous driving technology, critical mission data and non-critical mission data are handled with the same security level, and autonomous driving may be stopped even if it is attacked from the outside starting with communications that are not required for autonomous driving itself.

[0006] Means of solving problems

[0007] According to the first embodiment of the present disclosure, an information processing system is provided. The information processing system includes a control device as a central brain mounted on a vehicle and an information processing device, wherein the information processing device includes: an acquisition unit that acquires the type of data processed by the control device; a discrimination unit that discriminates whether the type of the acquired data is mission-critical data or non-mission-critical data; and a setting unit that sets the control device to connect the mission-critical data to a secure private cloud and connect the non-mission-critical data to a public cloud.

[0008] The information processing system of the first embodiment further includes a plurality of robots, and the private cloud and the control device, as well as the robots and the control device, are connected in a secure manner.

[0009] According to a first embodiment of the present disclosure, an information processing device is provided. The information processing device is an information processing device in an information processing system including a control device as a central brain mounted on a vehicle and an information processing device, and the information processing device includes: an acquisition unit that acquires the type of data processed by the control device; a determination unit that determines whether the type of the acquired data is mission-critical data or non-mission-critical data; and a setting unit that sets the control device to connect the mission-critical data to a secure private cloud and connect the non-mission-critical data to a public cloud.

[0010] According to a first embodiment of the present disclosure, there is provided a program for causing a computer to function as the above-mentioned information processing apparatus.

[0011] According to the second embodiment of the present disclosure, an information processing system is provided. The above-mentioned information processing system includes a control device and an information processing device as a central brain mounted on a vehicle, and the above-mentioned information processing device includes: an acquisition unit, which acquires data processed by the above-mentioned control device; a discrimination unit, which discriminates whether the type of the above-mentioned data acquired is mission-critical data or non-mission-critical data pre-specified by a user; an identification unit, which, in the above-mentioned discrimination, in the case where the above-mentioned non-mission-critical data is discriminated and the above-mentioned data acquired is undefined data that is not defined in the above-mentioned specification, uses a learned recognition model for identifying the degree to which the data is mission-critical data, and identifies the degree to which the above-mentioned data acquired is mission-critical data; and a setting unit, which sets the above-mentioned control device to connect the above-mentioned mission-critical data to a secure private cloud and connect the above-mentioned non-mission-critical data to a public cloud.

[0012] According to a second embodiment of the present disclosure, in the information processing system, the setting unit is configured to connect the undefined data, which is the acquired data, to the private cloud as the mission-critical data according to the identified degree.

[0013] According to a second embodiment of the present disclosure, in the information processing system, a label requesting identification is specified for the undefined data, and the identification unit identifies the degree only when acquiring the data to which the label requesting identification is assigned.

[0014] According to a second embodiment of the present disclosure, in the above-mentioned information processing system, in the above-mentioned designation, as the types of data judged as the above-mentioned critical mission data, data required for the automatic driving of the above-mentioned vehicle and predetermined data of high urgency are specified, and as the types of data judged as the above-mentioned non-critical mission data, natural conversation recognition, image recognition, information retrieval, information inference and other acquired information that is not classified as the above-mentioned data of high urgency are specified; the data required for the automatic driving of the above-mentioned vehicle includes sensor information related to the driving state required for the automatic driving of the above-mentioned vehicle, and sensor information related to the driving environment; the above-mentioned data of high urgency includes accident information occurring around the above-mentioned vehicle, and predetermined emergency notifications.

[0015] According to a second embodiment of the present disclosure, the above-mentioned information processing system also includes a learning device for learning the above-mentioned learned recognition model, and the above-mentioned learning device takes learning data as input, and uses a machine learning method to learn a recognition model to determine the extent to which the recognition data is mission-critical data. The learning data includes the above-mentioned mission-critical data specified by the user, the above-mentioned non-mission-critical data, and undefined data that is not defined in the non-mission-critical data, as well as weight labels relative to the above-mentioned undefined data.

[0016] According to a second embodiment of the present disclosure, an information processing device is provided. The above-mentioned information processing device is an information processing device in an information processing system including a control device and an information processing device as a central brain mounted on a vehicle, and the information processing device includes: an acquisition unit, which acquires data processed by the above-mentioned control device; a discrimination unit, which discriminates whether the type of the above-mentioned data acquired is mission-critical data or non-mission-critical data pre-specified by a user; an identification unit, which, in the above-mentioned discrimination, in the case where the above-mentioned non-mission-critical data is discriminated and the above-mentioned data acquired is undefined data not defined in the above-mentioned specification, uses a learned recognition model for identifying the degree to which the data is mission-critical data, and identifies the degree to which the above-mentioned data acquired is mission-critical data; and a setting unit, which sets the above-mentioned control device to connect the above-mentioned mission-critical data to a secure private cloud and connect the above-mentioned non-mission-critical data to a public cloud.

[0017] According to a second embodiment of the present disclosure, there is provided a program for causing a computer to function as the above-mentioned information processing apparatus.

[0018] It should be noted that the above summary of the present disclosure does not list all the necessary features of the present disclosure. In addition, sub-combinations of these feature groups may also be the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1One example of the functional configuration of the information processing system of the first embodiment is schematically shown.

[0020] Figure 2 An example of a network configuration according to the present embodiment is schematically shown.

[0021] Figure 3 An example of a network configuration in a vehicle according to the present embodiment is schematically shown.

[0022] Figure 4 Schematically shows the configuration of the robot and the connected communication environment.

[0023] Figure 5 An example of a processing routine executed by the information processing device according to the first embodiment is schematically shown.

[0024] Figure 6 One example of the functional configuration of the information processing system of the second embodiment is schematically shown.

[0025] Figure 7 An example of a processing routine executed by the information processing device according to the second embodiment is schematically shown.

[0026] Figure 8 An example of the hardware configuration of a computer that functions as a central brain, an information processing device, or a plurality of robots is schematically shown. DETAILED DESCRIPTION

[0027] Hereinafter, the present disclosure will be described by way of the embodiments of the present invention, but the following embodiments do not limit the invention according to the claims. In addition, the combination of features described in the embodiments is not necessarily essential to the solution means of the invention.

[0028] The information processing system of this embodiment is a system that connects the critical mission data related to Level 6 autonomous driving to a secure private cloud for processing, and branches the processing of non-critical mission data other than this. As a secure connection method, a virtual private network (VPN) is used. In the information processing system, an information processing device as a security chip is installed, and a branch is set on it to process critical mission data and other data.

[0029] In addition, "Level 6" indicates the level of autonomous driving, which is equivalent to a higher level than Level 5, which indicates fully autonomous driving. Although Level 5 indicates fully autonomous driving, it is at the same level as human driving, but there is still a probability of accidents. Level 6 is a higher level than Level 5, which is equivalent to a level where the probability of accidents is lower than that of Level 5.

[0030] (First Embodiment)

[0031] Figure 1 1 is a schematic diagram of an example of an information processing system 10 according to the first embodiment. The information processing system 10 includes a control device 120 and an information processing device 122 mounted on a vehicle 12 as an autonomous driving vehicle, a private cloud 14, a public cloud 15, and a plurality of robots 18A, 18B, and 18C. The various components of the information processing system 10 are communicatively connected via a communication line 16 such as the Internet. Hereinafter, the components common to each robot are referred to as robots 18. In addition, the private cloud 14 and the public cloud 15 may be inside or outside the information processing system 10.

[0032] The control device 120 is an example of a control device as a central brain mounted on a vehicle. In addition, the control device 120 is hereinafter referred to as the central brain 120.

[0033] Figure 2 1 is a diagram for explaining the communication environment to which the central brain 120 according to the present embodiment is connected. Figure 2 As shown, the central brain 120 can switch between the private cloud 14 and the public cloud 15 as the communication target. For example, the connection between the private cloud 14 and the central brain 120 is realized through a secure connection method, namely VPN. In addition, the central brain 120 is connected to multiple robots 18A, 18B, and 18C through VPN. In addition, a battery (not shown) for operating the central brain 120 in the vehicle 12 is connected to the central brain 12. In addition, the robot 18 is not limited to Figure 2 The humanoid robots shown may also include industrial robots driven on construction sites or in factories.

[0034] Figure 3 1 is a diagram for explaining the structure of the central brain 120 in the vehicle 12. Figure 3 As shown, a plurality of gateways (GateWay) are communicatively connected to the central brain 120. The central brain 120 is connected to an external cloud via a gateway. The central brain 120 is configured to be able to access an external cloud via a gateway. On the other hand, due to the existence of a gateway, the central brain 120 is configured to be inaccessible directly from the outside.

[0035] The central brain 120 performs vehicle control and request processing every 1 billionth of a second. In addition, the central brain 120 processes requests of a plurality of robots 18A, 18B, 18C. In addition, the central brain 120 may be separately configured, in which case, for example, the central brain connected to the private cloud 14 and the central brain connected to the public cloud 15 may be separated.

[0036] Whenever receiving data to be processed, the central brain 120 sends a setting request to the information processing device 122 and makes an inquiry, and receives the setting of the connection target from the information processing device 122. The central brain 120 branches the connection target of the data according to the setting of the connection target, connects the mission-critical data to the private cloud 14, and connects the non-mission-critical data to the public cloud 15.

[0037] In addition, as described above, although it is not possible to access the central brain 120 from the gateway, other devices can be queried from the central brain 120. The central brain 120 can be queried to the central brain of another vehicle.

[0038] The robot 18 is, for example, a robot that can work in the dark kitchen of a fast food restaurant or perform garbage cleaning. A level 6 smart car, that is, a vehicle 12 with a central brain 120, can manage about 100 level 5 robots 18. By managing multiple robots 18 through such a vehicle 12, for example, most of the work performed by blue collar workers or gig workers can be undertaken. In this way, the vehicle 12 with a central brain 120 can perform group intelligence work.

[0039] In order to prevent the robot 18 from being at risk of being hacked, the robot 18 only establishes a VPN connection with the manager of the level 6 central brain 120 through chip-level security.

[0040] Figure 4 This is a schematic diagram of the structure of the robot 18 described above and the communication environment to which it is connected.

[0041] The information processing device 122 as a security chip includes an acquisition unit 140, a determination unit 142, and a setting unit 144. In the information processing system 10, the central brain 120 and the information processing device 122 are separately configured, but the information processing device 122 may be incorporated into the central brain 120.

[0042] The information processing device 122 repeatedly executes Figure 5 The information processing device 122 receives a processing request from the central brain 120 every time it receives data to be processed by the central brain 120, and executes a series of processes in the flowchart in one billionth of a second.

[0043] In step S100 , the acquisition unit 140 acquires the type of data processed by the central brain 120 .

[0044] In step S102, the determination unit 142 determines whether the acquired data is mission-critical data or non-mission-critical data. If determined to be mission-critical data, the process proceeds to step S104, and if determined to be non-mission-critical data, the process proceeds to step S106.

[0045] In step S104 , as the data processed by the central brain 120 is mission-critical data, the setting unit 144 sets the connection target in a manner of connecting to the private cloud 14 .

[0046] In step S106 , as the data processed by the central brain 120 is non-mission-critical data, the setting unit 144 sets the connection target in a manner of connecting to the public cloud 15 .

[0047] In step S108, the setting unit 144 sends the setting of the connection target to the central brain 120. Through the setting of the connection target, the connection target of the data processed by the central brain 120 is allocated. The mission-critical data is connected to the private cloud 14, and the non-mission-critical data is connected to the public cloud 15.

[0048] As described above, the information processing system 10 is capable of achieving safe autonomous driving by more securely protecting mission-critical data.

[0049] (Second Embodiment)

[0050] Next, a second embodiment of the present disclosure will be described. In addition, the same reference numerals are given to the same parts as those of the first embodiment, and the description thereof will be omitted. Figure 6 It is a schematic diagram of an example of the information processing system 10 according to the second embodiment.

[0051] The information processing device 122 of the second embodiment includes an acquisition unit 240 , a determination unit 242 , a recognition unit 244 , and a setting unit 246 .

[0052] The acquisition unit 240 acquires data processed by the control device 120. For example, the acquisition unit 240 acquires data transmitted from various sensors provided in the vehicle 12 and the robot 18. The data acquired by the acquisition unit 240 may be the data itself or metadata that can identify the data itself.

[0053] The determination unit 242 determines whether the data acquired by the acquisition unit 240 is mission-critical data or non-mission-critical data specified in advance by the user. In this embodiment, the mission-critical data and non-mission-critical data are specified by the user. The data related to the specification is stored in the storage unit 250 of the information processing device 122.

[0054] In the determination by the determination unit 242, if it is determined that the data is non-mission-critical data and the data is undefined data that is not defined in the specification, the processing of the identification unit 244 is performed. The identification unit 244 uses the learned recognition model to identify the degree to which the acquired data is mission-critical data (hereinafter referred to as the degree). The learned recognition model is a model for identifying the degree to which the data is mission-critical data, and is learned in advance.

[0055] The setting unit 246 sets the control device 120 so that mission-critical data is connected to the secure private cloud and non-mission-critical data is connected to the public cloud.

[0056] The learning device 224 uses learning data including undefined data and weight labels relative to the undefined data as input, and uses a machine learning method to learn a recognition model for identifying the extent to which data is mission-critical data. Undefined data is data that is neither defined as mission-critical data nor as non-mission-critical data in the user's designation. Details about the undefined data will be described later. The machine learning method used in the learning device 224 can use any learning method such as a deep neural network (DNN) that can learn a model that takes data as input and outputs the extent to which it is mission-critical data.

[0057] Here, the mission-critical data and the non-mission-critical data defined by the user's designation are exemplified. The mission-critical data and the non-mission-critical data described below are defined by the user who is the manager of the information processing system and stored in the storage unit 250 of the information processing device 122 .

[0058] The types of data that can be classified as mission-critical data can be roughly divided into data required for autonomous driving itself and data with high urgency. Then, in the information processing device 122, the user can pre-specify whether the data exemplified below is to be processed as mission-critical data or as non-mission-critical data. Then, the information processing device 122 determines whether it is mission-critical data or non-mission-critical data based on the specification.

[0059] As data required for the automatic driving itself, there are sensor information related to the driving state of the vehicle 12 obtained from various sensors equipped by the vehicle 12, and sensor information related to the driving environment. Sensor information related to the driving state is, for example, vehicle speed information, wheel speed information, yaw rate information, steering information, and braking information. As sensor information related to the driving environment, there is detection information of obstacles on the road, road elements, road resistance, and air resistance. Road elements refer to elements related to the road on which the vehicle is traveling, such as road width, vehicles ahead, oncoming vehicles, speed limits, signals, and signs. In addition, the elements of this information can also be determined based on which sensor is the source of the transmission.

[0060] As data with high urgency, there can be listed accident information occurring around the vehicle 12 extracted from external data such as traffic information or weather information, or emergency notifications sent from the robot 18. Accident information is, for example, information on accidents, disasters, and bad weather occurring within a predetermined distance from the current position of the vehicle 12. The emergency notification sent from the robot 18 is triggered, for example, by the following situations: a failure occurs in the control of the robot 18 itself, the robot 18 detects the occurrence of an accident with high urgency, and the emergency call button provided by the robot 18 is pressed. As accidents with high urgency that the robot 18 can detect, for example, a parade occurs in the activity area of ​​the robot 18, a large number of people flow into the activity area of ​​the robot 18, and a traffic accident in the activity area of ​​the robot 18 can be detected. In addition, as examples of data included in the external data, traffic information or weather information is exemplified, but it is not limited to this, and various information provided outside the information processing system 10 may also be included. For example, city cameras, sensors installed in parking lots, and information from external monitoring systems may be appropriately included in the external data for processing.

[0061] Examples of non-critical mission data are given. Non-critical mission data are natural conversation recognition, image recognition, information retrieval, information inference, and other acquired information that is not classified as data with high urgency. Natural conversation recognition refers to, for example, the voice of a conversation detected by the vehicle 12 or the robot 18. Image recognition refers to the state of the interior of the vehicle and the surrounding scene captured by the camera of the vehicle 12 other than the road on which the vehicle 12 is traveling, or the surrounding scene captured by the camera of the robot 18. Information retrieval refers to, for example, search keywords input into an application or navigation possessed by the vehicle 12. Information inference refers to the calculation results of an application installed in the vehicle 12 or an application of an external service. Other acquired information is external data other than the above-mentioned data with high urgency and data of the robot 18.

[0062] The non-critical task data may include undefined data other than the data in the above examples. That is, in the non-critical task data specified by the user, there are defined data and undefined data as non-critical task data. Although the non-critical task data is specified in advance by the user, it is difficult for the administrator to specify all the data. Therefore, the data not specified by the user is treated as undefined data. The undefined data is conceived to be, for example, the above-mentioned external data or data of the robot 18, data of an external service that newly starts to send and receive data in the information processing system 10, and data of a newly introduced application of the robot 18.

[0063] For undefined data, the information used to identify the data is feature quantized as an input to the recognition model that has been learned. Similarly, the learning data used in the learning of the learning device 224 is also feature quantized for learning. The information identified as undefined data is the information of the data itself and metadata. If it is image data, the information of the data itself is image information such as image size, resolution, and object information in the analyzed image. If it is sound data, the information of the data itself is frequency or transformed text data. If it is sensor data, the information of the data itself is the detection value detected by the sensor. Metadata is information such as the acquisition date and time of the data, location information, and data transmission source.

[0064] The information processing device 122 of the second embodiment repeatedly executes Figure 7 The information processing device 122 receives a processing request from the central brain 120 every time it receives data to be processed by the central brain 120, and executes a series of processes in the flowchart in one billionth of a second.

[0065] In step S200, the acquisition unit 240 acquires data processed by the central brain 120. The data includes both mission-critical data and non-mission-critical data. In addition, the acquisition unit 240 extracts accident information from external data including traffic information or weather information, and extracts emergency notifications from data extracted from the robot 18.

[0066] In step S202, the determination unit 242 determines whether the type of the acquired data is mission-critical data or non-mission-critical data specified in advance by the user. Specifically, the determination unit 242 determines that the data specified by the user as mission-critical data is mission-critical data based on the data related to the designation of the storage unit 250. In addition, the determination unit 242 determines that the data specified by the user as non-mission-critical data is non-mission-critical data. If it is determined to be mission-critical data, the process proceeds to step S210, and if it is determined to be non-mission-critical data, the process proceeds to step S204.

[0067] In step S204, the identification unit 244 determines whether the acquired data is undefined data. If it is undefined data, the process moves to step S206, and if it is not undefined data, the process moves to step S212.

[0068] In step S206 , the recognition unit 244 uses the learned recognition model stored in the storage unit 250 to recognize the extent to which the acquired data is mission-critical data.

[0069] In step S208, the identification unit 244 determines whether the degree of the identified critical task data is above a predetermined threshold value. If the value of the degree is above the threshold value, the process moves to step S2110, and if the value of the degree is not above the threshold value, the process moves to step S212. In addition, the process is not limited to the case where the value of the degree is above the threshold value and the process is processed as critical task data by moving to step S210. For example, the process may temporarily move to step S212, and after setting it as non-critical task data, notify the manager that the value of the degree is above the threshold value, and accept the judgment result from the manager and reset it.

[0070] In step S210 , as the data processed by the central brain 120 is mission-critical data, the setting unit 246 sets the connection target in a manner of connecting to the private cloud 14 .

[0071] In step S212 , as the data processed by the central brain 120 is non-mission-critical data, the setting unit 246 sets the connection target in a manner of connecting to the public cloud 15 .

[0072] In step S214, the setting unit 246 sends the setting of the connection target to the central brain 120. Through the setting of the connection target, the connection target of the data processed by the central brain 120 is allocated. The mission-critical data is connected to the private cloud 14, and the non-mission-critical data is connected to the public cloud 15.

[0073] In addition, before the determination of step S204, a step of determining whether the data is assigned a tag of an identification request may be added. The tag of the identification request is a tag indicating an object of identification that is predetermined in the information processing system 10. In this case, if the data is assigned a tag of an identification request, the process proceeds to step S204, and if the data is not assigned a tag of an identification request, the process proceeds to step S212. Thus, only the data assigned a tag of an identification request is used as the object, and the degree of identification is mission-critical data.

[0074] As described above, the information processing system 10 is capable of achieving safe autonomous driving by more securely protecting mission-critical data.

[0075] Figure 8An example of the hardware configuration of a computer 1200 that functions as a control device 120 (central brain 120), an information processing device 122, or a plurality of robots 18A, 18B, 18C is schematically shown. The program installed in the computer 1200 enables the computer 1200 to function as one or more "parts" of the device involved in the present embodiment, or enables the computer 1200 to perform operations associated with the device involved in the present embodiment or the one or more "parts", and / or enables the computer 1200 to perform the process involved in the present embodiment or the stage of the process. Such a program can be executed by the CPU 1212 to enable the computer 1200 to perform specific operations associated with some or all of the blocks in the flowcharts and block diagrams described in this specification.

[0076] The computer 1200 according to the present embodiment includes a CPU 1212, a RAM 1214, and a graphic controller 1216 connected to each other through a host controller 1210. The computer 1200 also includes a communication interface 1222, a storage device 1224, an input / output unit such as a DVD drive and an IC card drive, which are connected to the host controller 1210 via the input / output controller 1220. The DVD drive may be a DVD-ROM drive and a DVD-RAM drive, etc. The storage device 1224 may be a hard disk drive and a solid state drive, etc. The computer 1200 also includes a ROM 1230 and a conventional input / output unit such as a keyboard, which are connected to the input / output controller 1220 via an input / output chip 1240.

[0077] The CPU 1212 operates according to the programs stored in the ROM 1230 and the RAM 1214 to control each unit. The graphic controller 1216 acquires image data generated by the CPU 1212 from a frame buffer or the like provided in the RAM 1214 or in itself, and causes the image data to be displayed on the display device 1218.

[0078] The communication interface 1222 communicates with other electronic devices via a network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD drive reads programs or data from a DVD-ROM or the like and provides them to the storage device 1224. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0079] The ROM 1230 stores therein a boot program or the like executed by the computer 1200 at startup, and / or a program depending on the hardware of the computer 1200. The input / output chip 1240 may also connect various input / output units to the input / output controller 1220 via a USB port, a parallel port, a serial port, a keyboard port, a mouse port, and the like.

[0080] The program is provided by a computer-readable storage medium such as a DVD-ROM or an IC card. The program is read from the computer-readable storage medium, installed in the storage device 1224, RAM 1214, or ROM 1230, which is also an example of a computer-readable storage medium, and executed by the CPU 1212. The information processing described in these programs is read by the computer 1200, and the program and the aforementioned various types of hardware resources are made to cooperate. The device or method can be configured by realizing the operation or processing of information according to the use of the computer 1200.

[0081] For example, when communication is performed between the computer 1200 and an external device, the CPU 1212 can execute a communication program loaded into the RAM 1214, and instruct the communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 1212, the communication interface 1222 reads the transmission data stored in the transmission buffer provided in the RAM 1214, the storage device 1224, a recording medium such as a DVD-ROM or an IC card, and transmits the read transmission data to the network, or writes the reception data received from the network to the reception buffer provided on the recording medium, etc.

[0082] In addition, the CPU 1212 can cause all or a necessary part of a file or a database stored in an external recording medium such as the storage device 1224, a DVD drive (DVD-ROM), an IC card, etc. to be read into the RAM 1214, and perform various types of processing on the data on the RAM 1214. Next, the CPU 1212 can write the processed data back to the external recording medium.

[0083] Various types of information such as various types of programs, data, tables, and databases can be stored in the recording medium to receive information processing. The CPU 1212 can perform various types of processing on the data read from the RAM 1214, and write the results back to the RAM 1214. The various types of processing include various types of operations, information processing, conditional judgments, conditional bifurcation, unconditional bifurcation, information retrieval / replacement, etc. recorded in various places of the present disclosure and specified by the instruction sequence of the program. In addition, the CPU 1212 can retrieve information in files, databases, etc. in the recording medium. For example, in the case where multiple entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored in the recording medium, the CPU 1212 can retrieve an entry consistent with the condition specifying the attribute value of the first attribute from the multiple entries, and read the attribute value of the second attribute stored in the entry, thereby obtaining the attribute value of the second attribute associated with the first attribute that meets the predetermined condition.

[0084] The program or software module described above may be stored in a computer-readable storage medium on or near the computer 1200. In addition, a recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet may be used as a computer-readable storage medium, thereby providing the program to the computer 1200 via the network.

[0085] The flowcharts and boxes in the block diagrams in this embodiment may represent the stages of the process of performing an operation or the "parts" of the device having the function of performing an operation. Specific stages and "parts" may be implemented by dedicated circuits, programmable circuits supplied together with computer-readable instructions stored on a computer-readable storage medium, and / or processors supplied together with computer-readable instructions stored on a computer-readable storage medium. Dedicated circuits may include digital and / or analog hardware circuits, and may also include integrated circuits (ICs) and / or discrete circuits. Programmable circuits may include reconfigurable hardware circuits such as field programmable gate arrays (FPGAs) and programmable logic arrays (PLAs), which include logical AND, logical OR, logical XOR, logical NAND, logical NOR, and other logical operations, triggers, registers, and storage elements.

[0086] Computer-readable storage media may include any tangible device capable of storing instructions executed by an appropriate device, with the result that a computer-readable storage medium having instructions stored in a tangible device has a product including instructions that can be executed to generate a unit for performing the operations specified in the flowchart or block diagram. Examples of computer-readable storage media include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, etc. More specific examples of the computer-readable storage medium may include a floppy disk (registered trademark) disk, a magnetic disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an electrically erasable programmable read-only memory (EEPROM), a static random access memory (SRAM), a compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), a Blu-ray disc (Blu-ray (registered trademark) Disk), a memory stick, an integrated circuit card, and the like.

[0087] Computer readable instructions may include assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state setting data, or any source code or object code described in any combination of one or more programming languages, wherein the one or more programming languages ​​include object-oriented programming languages ​​such as Smalltalk (registered trademark), JAVA (registered trademark), C++, etc. and traditional procedural programming languages ​​such as the "C" programming language or similar programming languages.

[0088] The computer-readable instructions can be provided to a processor or programmable circuit of a general-purpose computer, a special-purpose computer or other programmable data processing device locally or through a local LAN (Local Area Network, LAN), a wide area network (Wide Area Network, WAN) such as the Internet, etc., so that the processor or programmable circuit of the general-purpose computer, special-purpose computer or other programmable data processing device executes the computer-readable instructions to generate a unit for performing the operations specified in the flowchart or block diagram. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0089] The above embodiments are used to illustrate the technology of the present disclosure, but the technical scope of the present disclosure is not limited to the scope described in the above embodiments. It should be clear to those skilled in the art that various changes or improvements can be made to the above embodiments. It can be seen from the description in the claims that the embodiments with such changes or improvements can also be included in the technical scope of the present disclosure.

[0090] It should be noted that the execution order of each process such as actions, sequences, steps and stages in the devices, systems, programs and methods shown in the claims, specifications and drawings is not specifically indicated as "before", "earlier than", etc., or as long as the output of the previous process is not used in the subsequent process, it can be implemented in any order. Even if the action flow in the claims, specifications and drawings is described using "first", "next", etc. for convenience, it does not mean that it must be implemented in this order.

[0091] The disclosure of Japanese Patent Application No. 2022-166554 filed on October 17, 2022, and the disclosure of Japanese Patent Application No. 2022-184421 filed on November 17, 2022, are all incorporated by reference into this specification. All documents, patent applications, and technical standards described in this specification are incorporated by reference into this specification to the same extent as each document, patent application, and technical standard is specifically and individually incorporated by reference into this specification.

[0092] Description of Reference Numerals

[0093] 10 information processing system; 120 control device; 122 information processing device; 224 learning device; 14 private cloud; 15 public cloud; robot 18 (18A, 18B, 18C); 1200 computer; 1210 host controller; 1212 CPU; 1214 RAM; 1216 graphic controller; 1218 display device; 1220 input / output controller; 1222 communication interface; 1224 storage device; 1230 ROM; 1240 input / output chip

Claims

1. An information processing system, in, The information processing system includes a control device and an information processing device as the central brain mounted on the vehicle. The information processing device comprises: an acquisition unit that acquires a type of data processed by the control device; a determination unit, the determination unit determining whether the acquired data is mission-critical data or non-mission-critical data; and A setting unit configured to set the control device to connect the mission-critical data to a secure private cloud and to connect the non-mission-critical data to a public cloud information processing system.

2. The information processing system according to claim 1, in, Also includes multiple robots, The private cloud and the control device, and the robot and the control device are connected in a secure manner.

3. An information processing device, in, The information processing device is an information processing device in an information processing system including a control device as a central brain mounted on a vehicle and an information processing device, and the information processing device includes: an acquisition unit that acquires a type of data processed by the control device; a determination unit, the determination unit determining whether the acquired data is mission-critical data or non-mission-critical data; and A setting unit configured to set the control device to connect the mission-critical data to a secure private cloud and to connect the non-mission-critical data to a public cloud.

4. A procedure, in, The program is for causing a computer to function as the information processing device according to claim 3.

5. An information processing system, in, The information processing system includes a control device and an information processing device as the central brain mounted on the vehicle. The information processing device comprises: an acquisition unit that acquires data processed by the control device; a determination unit, the determination unit determining whether the type of the acquired data is mission-critical data or non-mission-critical data pre-specified by a user; an identification unit that, in the determination, when the data is determined to be the non-mission-critical data and the acquired data is undefined data that is not defined in the designation, identifies the extent to which the acquired data is the mission-critical data using a learned identification model for identifying the extent to which the data is the mission-critical data; and A setting unit configured to set the control device to connect the mission-critical data to a secure private cloud and to connect the non-mission-critical data to a public cloud.

6. The information processing system according to claim 5, in, The setting unit is configured to connect the acquired undefined data to the private cloud as the mission-critical data according to the degree of recognition.

7. The information processing system according to claim 5, in, specifying a tag identifying the request for the undefined data, The recognition unit recognizes the degree only when the data to which the tag of the recognition request is given is acquired.

8. The information processing system according to claim 5, in, In the designation, as the types of data determined as the mission-critical data, data required for the autonomous driving of the vehicle and predetermined data of high urgency are specified, and as the types of data determined as the non-mission-critical data, natural conversation recognition, image recognition, information retrieval, information inference, and other acquired information that is not classified as the data of high urgency are specified; The data required for the autonomous driving of the vehicle includes sensor information related to the driving state required for the autonomous driving of the vehicle and sensor information related to the driving environment; The high-urgency data includes accident information occurring around the vehicle and a predetermined emergency notification.

9. The information processing system according to claim 5, in, It also includes a learning device for learning the learned recognition model. The learning device takes learning data as input and uses a machine learning method to learn a recognition model for identifying the extent to which data is mission-critical data, wherein the learning data includes the mission-critical data specified by the user, the non-mission-critical data, and undefined data that is not defined in the non-mission-critical data, as well as a weight label relative to the undefined data.

10. An information processing device, in, The information processing device is an information processing device in an information processing system including a control device as a central brain mounted on a vehicle and an information processing device, and the information processing device includes: an acquisition unit that acquires data processed by the control device; a determination unit, the determination unit determining whether the type of the acquired data is mission-critical data or non-mission-critical data pre-specified by a user; an identification unit that, in the determination, when the data is determined to be the non-mission-critical data and the acquired data is undefined data that is not defined in the designation, identifies the extent to which the acquired data is the mission-critical data using a learned identification model for identifying the extent to which the data is the mission-critical data; and A setting unit configured to set the control device to connect the mission-critical data to a secure private cloud and to connect the non-mission-critical data to a public cloud.

11. A procedure, in, The program is for causing a computer to function as the information processing device according to claim 10.

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