Multi-factor verification system, multi-factor verification method, and program

Abstract

Provided is a multifactor collation system in a cyber-physical system constructed by connecting a physical space and a cyber space via a network, the multifactor collation system comprising: a collation unit that determines whether or not to project an object in the physical space into the cyber space on the basis of first position information that is information on the position of the object and obtained by a positioning means in the object and second position information that is information on the position of the object and obtained by a means other than the positioning means; and a projection unit that projects the object into the cyber space when the collation unit has determined to project the object into the cyber space.

Description

[Technical field]

[0001] The present invention relates to a technology for projecting a physical space onto a logical space in a Cyber-Physical System in which the physical space and the logical space are connected via a network. [Background technology]

[0002] A technology called Cyber-Physical System (CPS) is currently being considered. CPS is a technology that captures objects and phenomena in physical space using object detection technologies that use sensors such as cameras and LiDAR (Light Detection and Ranging) and positioning technologies based on GNSS (Global Navigation Satellite System) signals, and projects the captured situation onto logical (cyber) space connected by a network (NW), thereby executing or enhancing control and simulation of the physical space.

[0003] In order to appropriately transform (control) physical space based on a CPS, it is assumed that a process will be involved in which the ideal physical space after the transformation will be simulated (tried) in advance in cyberspace.

[0004] To effectively simulate the above process, it is necessary to precisely reproduce (project) the physical space before the transformation into cyberspace. Furthermore, the projection into cyberspace needs to be reliable as a digital twin of the physical space.

[0005] Possible methods for estimating the position of an object in physical space include self-location estimation / positioning, in which the object itself estimates its position using absolute positioning based on GNSS signals or relative positioning based on information from a six-axis sensor, and third-party position estimation, in which an external sensor other than the object itself captures the object and estimates its position using a camera or other external sensor. [Prior art documents] [Non-patent literature]

[0006] [Non-Patent Document 1] Yoshida et al., High-value-added location information services through collaboration between GNSS and networks, NTT Technical Journal, April 2019 [Non-Patent Document 2] Sakai, Security of GPS, Journal of Reliability Engineering, Japan, pp.158-164, Vol. 39, No. 4, 2017 Summary of the Invention [Problem to be solved by the invention]

[0007] When projecting physical space into cyberspace, there is a possibility that an erroneous projection may occur due to accidental / naturally occurring events, interference events from outside the object, intentional position spoofing events of the object itself, etc. Non-Patent Documents 1 and 2 propose techniques to avoid erroneous projection, but existing techniques cannot deal with spoofing events of the object itself.

[0008] The present invention has been made in consideration of the above-mentioned points, and aims to provide a technology that improves the reliability of projection from physical space to cyberspace and makes it possible to avoid erroneous projection. [Means for solving the problem]

[0009] According to the disclosed technology, there is provided a multi-factor authentication system in a cyber-physical system in which a physical space and a cyber space are connected by a network, comprising: a collation unit that determines whether or not to project the object into the cyberspace based on first position information, which is position information of the object in the physical space obtained by a positioning means, and second position information, which is position information of the object obtained by a means other than the positioning means; a projection unit that projects the object into the cyberspace when the collation unit determines that the object should be projected into the cyberspace, The collation unit compares the first location information with the second location information to determine a reliability of the first location information, and determines whether or not to project the object into the cyberspace based on the reliability. A multi-factor verification system is provided. Effect of the Invention

[0010] According to the disclosed technology, it is possible to improve the reliability of projection from physical space to cyberspace and avoid erroneous projection. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram for explaining an assumed environment. [Diagram 2] FIG. 1 is a diagram for explaining an assumed environment. [Diagram 3] FIG. 1 is a diagram for explaining a problem. [Figure 4] FIG. 1 is a diagram for explaining a problem. [Diagram 5] FIG. 1 is a diagram for explaining an overview of an embodiment. [Figure 6] 1 is a system configuration diagram according to an embodiment of the present invention. [Figure 7] FIG. 2 is a sequence diagram for explaining the operation of the system. [Figure 8] 1 is a flowchart for explaining the first embodiment. [Figure 9] 11 is a flowchart for explaining a second embodiment. [Figure 10] FIG. 13 is a sequence diagram for explaining an eighth embodiment. [Figure 11] FIG. 2 illustrates an example of a hardware configuration of the apparatus. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention (the present embodiment) will be described with reference to the drawings. The embodiment described below is merely an example, and the embodiment to which the present invention is applied is not limited to the following embodiment.

[0013] Below, we will explain a technology that compares multiple information elements when projecting physical space onto cyberspace in a Cyber-Physical System where physical space and cyberspace are connected by a network, and performs the projection after taking the comparison results into consideration. Matching multiple information elements is called "multi-factor comparison."

[0014] (Assumed environment) First, the environment assumed in the CPS will be explained. Figure 1 shows the CPS. As mentioned above, in the CPS, sensors capture objects and phenomena in the physical space, and the captured situation is projected onto the cyberspace connected by the network, thereby controlling the physical space and carrying out simulations, etc. In addition, the "cyberspace" is specifically, for example, a database that stores information including the identifier of an object in the cyberspace and the location information of the object. In addition, "projecting" corresponds to storing information in the database that constitutes the cyberspace.

[0015] Objects in physical space can be classified into three types: A, B, and C.

[0016] A: An object that broadcasts its own location (or similar) information B: Objects other than A connected to the network C: Objects that have no means of communication and are not connected to the network Figure 2 shows a CSP targeting A, B, and C in the physical space. The objects A', B', and C' that are projected into the cyberspace are shown as A', B', and C', respectively. Figure 2 shows that the control function attempts to transform A', B', and C' in the physical space.

[0017] Here, A can estimate / locate its own position and broadcast it. In other words, the subject of projection into cyberspace is A itself. In contrast, for B and C, the subject of projection into cyberspace is external, and someone other than the object itself estimates their positions.

[0018] Factors that impede accurate projection include disturbances in location estimation / location measurement for all of A through C. In addition, factors A also include intentional location spoofing and unstable communication. Factors B and C include duplicated replays due to double capture / non-replays due to capture failures.

[0019] In this embodiment, a technique for solving the problem regarding the projection of an object A that actively broadcasts its own position will be described.

[0020] (About the assignment) The above problem will be explained in detail. In a CPS, the GNSS positioning calculation result (position) distributed by the object itself and the identifier (called a network management ID) of the object (e.g., terminal) on the network used for distribution are basically projected / managed in cyberspace as true values ​​in physical space.

[0021] By matching the position broadcast by the object with its actual position in physical space, proper CPS control is achieved, as shown in Figure 3.

[0022] However, if the position broadcast by an object differs from its actual position in the physical space, a difference will arise between the physical space and its projection, cyberspace, as shown in Figure 4. In such a case, effective simulation is not possible, and therefore the physical space cannot be appropriately transformed (controlled).

[0023] For example, the above difference occurs due to intentional position spoofing by the object itself (a spoofing event inside the object), but conventional techniques have not been able to deal with such position spoofing.

[0024] In addition to the above-mentioned internal camouflage events, factors that can cause erroneous projections include accidental / naturally occurring events and interference events from outside the object. Below, we explain the existing technologies / approaches to avoid each of these, the challenges of their introduction, and the common challenges that remain even after their introduction.

[0025] <(1) Accidental / naturally occurring events> Accidental / naturally occurring events include GNSS signal multipath, GNSS signal out-of-service areas, etc. As an existing technology for avoiding erroneous projection for GNSS signal multipath, there is a satellite signal selection algorithm disclosed in Non-Patent Document 1, but there are issues with its introduction in terms of cost, maturity of the technology, and widespread use.

[0026] In addition, existing technologies for avoiding erroneous projection into out-of-service areas of GNSS signals include IMS disclosed in Non-Patent Document 1, dead reckoning using images, and hybrid positioning, but these have issues with dependency on terminal equipment / functions, cost, etc.

[0027] <(2) Disturbance events from outside the object> Jamming / spoofing of GNSS signals is an example of interference from outside an object. Existing technology to avoid erroneous projections against this is the addition of an array antenna / authentication signal to the GNSS signal, as disclosed in Non-Patent Document 2. However, there are issues with its implementation, such as the fact that array antennas are for military use (not distributed to the public) and that a complete replacement of the GNSS infrastructure is required (unrealistic).

[0028] Even after the common introduction of "(1) accidental / naturally occurring events" and "(2) disturbance events from outside the object," the following common problem remains: In other words, all existing technologies are approaches to solving the disturbance of object (A)'s location estimation / positioning, and cannot deal with the intentional location spoofing of object (A) itself or the spoofing of information required for location estimation / positioning.

[0029] <(3) Camouflage phenomenon inside objects> An example of a falsification event inside an object is a change in the positioning calculation result (location information) used inside the object. Existing technologies to avoid erroneous projection in response to this include monitoring and strengthening security of software / APIs operating inside the object, as disclosed in Non-Patent Document 2. However, this existing technology has implementation issues such as software sophistication, constant updates, and resource consumption including power.

[0030] Furthermore, even after the above-mentioned existing technologies are introduced, they cannot deal with hacking of the object itself, including the forced shutdown of monitoring / blocking software.

[0031] The problem assumed in this embodiment is mainly the above-mentioned "fake events inside an object", but the technology according to the present invention is also effective for "accidental / naturally occurring events" and "interfering events from outside an object". In other words, the technology according to the present invention functions as a method for solving problems related to "accidental / naturally occurring events" and "interfering events from outside an object", and contributes to precise reproduction of physical space in cyberspace and improvement of the reliability of the reproduction. In other words, the technology according to the present invention makes it possible to improve the reliability of projection from physical space to cyberspace and avoid erroneous projection.

[0032] (Outline of the embodiment) Next, an outline of the present embodiment will be described. In the present embodiment, a CPS projection multi-factor matching method utilizing network side positioning will be described.

[0033] In this method, a projection request based on the active location distribution of an object (A) in the physical space is projected into cyberspace after multi-factor verification. This improves the reliability of cyberspace as a projection of the physical space by avoiding both of the following impediments.

[0034] -Disturbances in device (information) location estimation / positioning Intentional spoofing of the device's location or spoofing of information required for location estimation / location measurement An overview will be given with reference to Fig. 5. Fig. 5 shows an example in which the object (A) is a person who owns a smartphone with a GNSS function. As shown in Fig. 5, the position of the person (smartphone) is acquired by GNSS positioning. Furthermore, the position of the person is measured by methods such as network side positioning, image positioning, and laser positioning.

[0035] In S1, an object (A) transmits a projection request including position information obtained by positioning to the system. In S2, a matching function checks the presence and matches the position of the object (A). In S3, the matching function generates a projection of the object (A) based on the most reliable (highly accurate) positioning result or the calculation result as a composite positioning.

[0036] The above-mentioned matching function includes the functions of the matching unit 130 and the projection unit 110 described later. For example, the matching function determines whether or not to project the object (A) into cyberspace based on first position information, which is position information of the object (A) obtained by a positioning means in the object (A) and second position information, which is position information of the object (A) obtained by a means other than the positioning means of the object (A). The means other than the positioning means of the object (A) may be any of a network side positioning means, an image positioning means, and a laser positioning means, or may be other means. In addition, the means other than the positioning means of the object (A) may include multiple positioning means.

[0037] For example, the matching function determines the reliability of the first location information by comparing the first location information with the second location information. For example, the matching function compares the first location information with the image positioning result, and also compares the first location information with the NW-side positioning result. If the difference in any of these comparison results is equal to or less than a threshold, the matching function can determine that the first location information is reliable to a certain extent. Also, if the difference between one positioning result considered to be highly reliable (e.g., the NW-side positioning result) and the first location information is equal to or less than a threshold, the matching function may determine that the first location information is reliable to a certain extent.

[0038] If it is determined that the first location information is information that is reliable to a certain extent, the matching function may project into cyberspace using "the most probable location information among the first location information and one or more location information included in the second location information" or "location information estimated based on at least one of the first location information and one or more location information included in the second location information."

[0039] Regarding "the most probable location information among one or more pieces of location information included in the first location information and the second location information", for example, among the location means that obtained the second location information, a location means with the highest reliability may be determined in advance, and the location information obtained by that location means may be set as "the most probable location information among one or more pieces of location information included in the first location information and the second location information". In addition, for example, a current predicted location of the object (A) may be calculated using a method described later, and the location information that is closest to the predicted location among "the one or more pieces of location information included in the first location information and the second location information" may be set as "the most probable location information among one or more pieces of location information included in the first location information and the second location information".

[0040] Regarding "location information estimated based on at least one of the location information included in the first location information and the one or more location information included in the second location information," for example, the center of gravity position of all or any of the location information included in the "first location information and the one or more location information included in the second location information" may be used.

[0041] (System Configuration) A configuration example of the multi-factor matching system in this embodiment is shown in Fig. 6. As shown in Fig. 6, the multi-factor matching system in this embodiment includes a projection unit 110, a projection information management unit 120, a matching unit 130, a NW information management unit 140, a positioning unit 150 that performs NW side positioning, a stranger's position estimation management unit 160, and a stranger's position estimation unit 170 that performs image positioning, laser positioning, etc.

[0042] FIG. 6 also shows an object 300 (object A) having a positioning unit 310 and a cyberspace (digital twin) 200.

[0043] The operation of each unit will be described in the following sequences and examples. The functions of the units enclosed by the dotted lines in Fig. 6 may be implemented in one device (computer) or may be distributed among multiple devices.

[0044] (Sequence) An example of the operation of the multi-factor matching system will be described with reference to Fig. 7. In S11, position information (corresponding to a projection request) is delivered from the object 300 to the projection unit 110. In S12, the projection unit 110 transmits a matching request to the matching unit 130.

[0045] Upon receiving the matching request, matching unit 130 transmits a position information (positioning result) request to positioning unit (NW side) 150 (S13), and transmits a position information (positioning result) request to other party position estimation management unit 160 (S14).

[0046] The other person's position estimation management unit 160, which has received the position information (positioning result) request, requests the other person's position estimation unit 170 to perform other person's position estimation in S15. The positioning unit (NW side) 150 performs positioning / position estimation of the object 300 in S16, and the other person's position estimation unit 170 performs positioning / position estimation of the object 300 in S17.

[0047] In S18, the collation unit 130 transmits a NW information request to the NW information management unit 140, and in S20 receives a NW information response.

[0048] Furthermore, the matching unit 130 transmits a projection / matching history request to the projection information management unit 120 in S19, and receives a projection / matching history response in S21.

[0049] In S22 to S24, the collation unit 130 receives responses of the position information obtained by each of the other person's position estimation unit 170 and the positioning unit (NW side) 150. The collation unit 130 determines whether or not to project the object 300 into the cyberspace 200 by using the position information obtained by the response, history information, and the like.

[0050] The collation unit 130 returns the collation result to the projection unit 110 in S25, and stores the collation result in the projection information management unit 120 in S26.

[0051] If the collation result indicates that projection should be performed, the projection unit 110 performs projection in S27, and stores the projection result in the projection information management unit 120 in S .

[0052] As more specific processing examples, Examples 1 to 8 will be described below. Examples 1 to 8 are examples in the following cases.

[0053] Example 1: When GNSS signal-based positioning is compared only with network-side positioning Example 2: When positioning based on camera images and LiDAR can be used as the other person's position estimation unit 170 Example 3: When matching is performed based on the difference in real-time location (positioning results) Example 4: When matching is performed by referring to the history of location transitions Example 5: When verification is performed by referring to the projection history in cyberspace Example 6: When matching is performed based on the difference with the result of location prediction based on history (future location) Example 7: When referencing matching history Example 8: When the technology according to the present invention is applied to the A-GNSS positioning method defined by 3GPP The purpose, projection target, position estimation / location method, and matching logic in the embodiment are summarized as follows: Note that the following is an example, and projection targets, position estimation / location methods, and matching logic other than those described below may be used.

[0054] <Purpose> The aim is to ensure reliability as a digital twin by precisely projecting objects in physical space into cyberspace.

[0055] <Projection target> Examples of projection objects are as follows:

[0056] · Communication devices (smartphones, etc.) Devices equipped with communication terminals (automobiles, etc.) Owner of communication device <Location estimation / positioning method> Examples of location estimation / positioning methods are as follows:

[0057] GNSS positioning ·Autonomous navigation (IMS, geomagnetic) positioning Base station positioning Camera image positioning LiDAR positioning ·IMES (Indoor Messaging System) ·Wi-Fi (registered trademark) positioning ·Sonic positioning Barometric positioning ·Beacon positioning Visible light positioning <Matching logic> An example of matching logic is as follows:

[0058] - Real-time location (positioning results) difference (single / multiple positioning methods) - Location transition history (single / multiple positioning methods) - Projection history onto cyberspace - Difference from location prediction results based on history · Matching history The following describes Examples 1 to 8. Examples 1 to 8 can be implemented in any combination.

[0059] Example 1 First, a description will be given of Example 1. Example 1 is an example in which the comparison target for positioning based on GNSS signals is only NW side positioning.

[0060] In the first embodiment, when location information is distributed (projection request) from the object 300, the collation unit 130 acquires the result of NW-side positioning and compares it with the location information distributed from the object. For the NW-side positioning, for example, positioning based on radio wave propagation between a base station and a terminal as specified in 3GPP (specifically, 3GPP TS 38.305, etc.) can be used.

[0061] If the matching unit 130 is able to confirm based on the comparison result that the object 300 is present at the corresponding position in the physical space, it performs projection into cyberspace based on the location information transmitted from the object 300, or the result of positioning on the network side, or the result of positioning calculated by combining these positioning results in a composite manner.

[0062] The operation of the first embodiment will be described in more detail with reference to the flowchart in Fig. 8. In S101, an object 300 (object A) in the physical space moves to its own position (P A ) to the projection unit 110. This positional information transmission corresponds to a projection request.

[0063] In S102, the collation unit 130 A Based on P A A positioning result based on the information of the positioning or nearby facilities is requested from the nearby NW facilities (positioning unit (NW side) 150), cameras, LiDAR, and other sensors (other person's position estimation unit 170). In S103, the collation unit 130 acquires the positioning result of the NW side.

[0064] In S104, the collation unit 130 checks the positioning result (P' A In the first embodiment, it is determined whether or not there is a positioning result (P') other than the NW side positioning (positioning based on NW information). A ) does not exist, proceed to S105.

[0065] In S105, the collation unit 130 A The difference between the result of the positioning on the network side and the specified value (predetermined threshold) D th3If the result of the determination in S105 is Yes (D th3 If it is the case below, proceed to S106, and if it is No, end the process.

[0066] In S106, the projection unit 110 projects the object 300 into cyberspace based on the most reliable (highly accurate) positioning result or the calculation result as the combined positioning.

[0067] Example 2 Next, a description will be given of Example 2. Example 2 is an example in which positioning based on a camera image and LiDAR can be used as the function of the other person's position estimation unit 170.

[0068] In the second embodiment, in response to a location information distribution (projection request) from the object 300, the collation unit 130 acquires a location result based on a camera image and a location result based on LiDAR in addition to the NW side location measurement, and compares the location result with the location information distributed from the object. Note that the location measurement based on a camera image and the location measurement based on LiDAR are examples, and other third party location estimation functions may be used alone or in combination.

[0069] If the matching unit 130 is able to confirm based on the comparison result that the object 300 is present at the corresponding position in the physical space, it performs projection into cyberspace based on the position information distributed from the object 300, or the result of the network side positioning, or the result of another party's position estimation, or the positioning result calculated by combining these positioning results in a composite manner.

[0070] The operation of the second embodiment will be described in more detail with reference to the flowchart of Fig. 9. In S201, an object 300 (object A) in the physical space moves to its own position (P A ) to the projection unit 110. This positional information transmission corresponds to a projection request.

[0071] In S202, the collation unit 130 A Based on P AThe collation unit 130 requests the nearby network equipment, cameras, LiDAR, and other sensors to perform positioning or provide a positioning result based on information about nearby equipment. In S203, the collation unit 130 acquires various positioning results.

[0072] In S204, the collation unit 130 checks the positioning result (P' A In the second embodiment, it is determined whether or not there is a positioning result (P' A ) exists, proceed to S205.

[0073] In S205, the collation unit 130 A and P' A The difference is the specified value D th1 Determine whether the following is true: No (D th1 If not, proceed to S206; if Yes, proceed to S207.

[0074] In S206, if the result of S205 is No, the collation unit 130 A The difference between the result of the positioning on the network side and the specified value D th3 If the result of the determination in S206 is Yes, the process proceeds to S208, and if the result is No, the process ends.

[0075] In S207, if the result of S205 is Yes, the collation unit 130 A The difference between the result of the positioning on the network side and the specified value D th2 It is determined whether or not the following occurs: If the result of the determination in S207 is Yes, the process proceeds to S208, and if the result is No, the process ends.

[0076] In S208, the projection unit 110 projects the object 300 (object A) into cyberspace based on the most reliable (highly accurate) positioning result or the calculation result as the combined positioning.

[0077] The thresholds used in S206 and S207 above include D th3 >D th2 In other words, S207 is stricter than S206. The reason is as follows.

[0078] The threshold is set on the assumption that the network side positioning may be at the base station coverage level (rough), and that the location estimation function of other parties that are locally installed / functioning can estimate the location more accurately. Therefore, D th3 >D th2 It states that:

[0079] However, since 5G uses higher frequencies for communication, it is expected that the accuracy of positioning will be improved, and the threshold value must be set according to the accuracy of the position obtained by the network side positioning. The accuracy of other parties' position estimation is also improving year by year, but in some cases, th3 and D th2 The magnitude relationship is also reversed.

[0080] Example 3 Next, a third embodiment will be described. The third embodiment is an embodiment in which matching is performed based on a difference in real-time positions (positioning results). The third embodiment is applicable to both the first and second embodiments.

[0081] In the third embodiment, the matching unit 130 performs multi-factor matching by comparing whether the difference between the position information delivered from the object 300 and one or more object positions obtained by different position estimation / positioning methods is equal to or less than a specified value. If the difference is equal to or less than the specified value, it is determined that the object exists at the corresponding position in the physical space, and the projection is permitted. If the difference exceeds the specified value, the projection request from the object is not accepted.

[0082] However, this does not apply to projection based on other person's position estimation, which occurs as an event independent of the projection request from the object.

[0083] Example 4 Next, a fourth embodiment will be described. The fourth embodiment is an embodiment in which matching is performed by referring to a history of position transitions. The fourth embodiment can be applied in combination with any of the first to third embodiments.

[0084] In the fourth embodiment, the matching unit 130 refers to past object positions and base station connection history in addition to the real-time object position obtained as a snapshot during multi-factor matching.

[0085] Past object positions and base station connection history are stored in, for example, the NW information management unit 140, and this information can be acquired by S18 and S20 shown in the sequence of FIG.

[0086] The matching unit 130 takes into account, as a matching factor, whether the object position and the connected base station are not extremely discrete, and whether a prescribed level of continuity can be ensured, taking into account the power (communication function) OFF time.

[0087] Specifically, the continuity of an object's position is determined by calculating the object's movement speed (v) from the position transition history and determining whether position information has been delivered within the range of the transition at that movement speed (d = v × (the time from the time the position information in the most recent history was received to the time the newly delivered position information is received)).

[0088] The location transition history may be a history of results based on a single location estimation / positioning method, or may be a history of results based on a plurality of different location estimation / positioning methods.

[0089] The continuity of base station connections is determined by whether there is any discrepancy between the object position and the geographical location of deployed base stations, and whether handovers have occurred between base stations that are not geographically adjacent.

[0090] In any case, since there is a possibility that the location may become discrete before and after the power (communication function) is turned on / off regardless of whether or not there is intentional location spoofing, rather than comparing based on the history alone, the location transition history is treated as one of multiple elements used for matching.

[0091] Example 5 Next, a fifth embodiment will be described. The fifth embodiment is an embodiment in which matching is performed by referring to a projection history into a cyberspace. The fifth embodiment can be applied in combination with any of the first to fourth embodiments.

[0092] In the fifth embodiment, the matching unit 130 refers to the projection history of the object 300 (its NW management ID) onto the cyberspace in addition to the real-time object position obtained as a snapshot during multi-factor matching.

[0093] The projection history is stored in, for example, the projection information management unit 120, and the information can be acquired by steps S19 and S21 shown in the sequence of FIG.

[0094] The matching unit 130 takes into account in the matching factors whether the current projection request from the object is far removed from the projection history so far, and whether continuity beyond the prescribed level can be guaranteed, taking into account the time when the power (communication function) is turned off.

[0095] The continuity of the projection is determined based on the position of the projected object or the properties of the object (physical / external features, etc.). The same determination method as in the fourth embodiment can be applied to the determination based on the position of the object.

[0096] In any case, since there is a possibility that continuity may be lost before and after the power (communication function) is turned on / off or before and after the transfer or loss of a communication device, regardless of whether or not there is intentional location spoofing, rather than comparing based on the history alone, the projection history is treated as one of multiple elements used for matching.

[0097] Example 6 Next, a sixth embodiment will be described. The sixth embodiment is an embodiment in which matching is performed based on the difference with the result of location prediction based on history (future location). The sixth embodiment can be applied in combination with any of the first to fifth embodiments.

[0098] In the sixth embodiment, the matching unit 130 refers to the difference between the real-time object position obtained as a snapshot and the future position of the object predicted from the history of position transition or projection during multi-factor matching. For example, the matching unit 130 refers to the difference between the current position delivered by the object and the current position of the object obtained by position prediction.

[0099] The information for calculating the position transition can be obtained in steps S18 and S20 in the sequence of FIG. 7, and the projection history can be obtained in steps S19 and S21 in the sequence of FIG.

[0100] The matching unit 130 compares whether the object position is far from the predicted future position (whether the difference exceeds a threshold) and whether the difference in position is below a specified value, taking into account the time the power (communication function) has been off.

[0101] Position prediction may be performed based on the object's movement speed as described in Example 4, or based on the object's movement plan, the object's properties, external objects / phenomena related to the object, and the object's behavior derived from the surrounding environment / situation.

[0102] In any case, there is a possibility that the difference will be large before and after the power (communication function) is turned on / off or for objects that exhibit sudden behavior, regardless of whether or not there is intentional location spoofing. Therefore, rather than comparing only the difference with the location prediction result, the difference with the location prediction result is treated as one of multiple elements used for matching.

[0103] Example 7 Next, a seventh embodiment will be described. The seventh embodiment is an embodiment in which the collation history is referred to. The seventh embodiment can be applied in combination with any of the first to sixth embodiments.

[0104] In the seventh embodiment, the matching unit 130 refers to the real-time object position obtained as a snapshot during multi-factor matching, as well as to how many times a request to project an object has been approved or rejected in the past. For example, if a projection has been rejected a predetermined number of times in the past, the matching unit 130 rejects the projection even if there is no problem in matching based on a comparison of position information.

[0105] The collation history is stored in, for example, the projection information management unit 120, and the information can be acquired by steps S19 and S21 shown in the sequence of FIG.

[0106] In addition, the matching unit 130 varies the settings of various thresholds and the conditions used for matching for each projection request based on the reliability of the object (information distributed from the object), such as setting stricter thresholds and conditions used for matching for objects where intentional position spoofing is frequently observed (low reliability).

[0107] However, reliability also changes depending on the object's environment or changes in owner, so matching is not performed based solely on the matching history, but rather the matching history is treated as one of multiple elements used for matching.

[0108] Example 8 Next, an eighth embodiment will be described. The eighth embodiment is an embodiment in which the technology according to the present invention is applied to the A-GNSS positioning method defined by 3GPP. The eighth embodiment can be applied in combination with any of the first to seventh embodiments. The A-GNSS positioning method is disclosed, for example, in "NTT DOCOMO Technical Journal Vol. 2 No. 4 Advancement of Positioning Method for Smartphones-A - GNSS (GPS+GLONASS) Positioning Support and UE-A Positioning Support."

[0109] First, an example of a procedure for UE-A positioning in the A-GNSS positioning method described in the above document will be described with reference to Fig. 10. In Fig. 10, a server 20 is an SLP (SUPL Location Platform) and is a server that distributes assist data for positioning, etc.

[0110] In S801, the terminal 10 transmits a positioning start request to the server 20, and in S802, the server 20 returns a positioning start response. In S803, the terminal 10 transmits an assist data request to the server, and the server 20 performs approximate positioning (S804) and distributes satellite information around the mobile device (terminal) (S805). In S806, assist data including the satellite information is returned to the terminal 10.

[0111] In S807, the terminal 10 acquires satellite radio waves, and in S808, notifies the terminal 10 of satellite radio wave acquisition information. In S809, the server 20 performs positioning calculation. If positioning fails, the approximate positioning result is adopted (S810). In S811, the server 20 notifies the terminal 10 of the positioning result.

[0112] In the UE-A positioning of the A-GNSS positioning method described above (see Figure 3 in the document *), when the positioning calculation is performed in the SLP (server 20), NW side positioning based on the technology of the present invention and position estimation by the other party position estimation unit 170 are performed, and the result is transmitted to the outside including the terminal 10 (cyberspace in the technology of the present invention).

[0113] By regarding the positioning start request from terminal 10 as a projection request into cyberspace and regarding the reception result of the satellite radio wave acquisition information notification sent from terminal 10 as potentially spoofed information, the technology of the present invention can be applied to a mobile communication network conforming to the 3GPP regulations in accordance with a data flow similar to the flow shown in Figure 7, etc.

[0114] (Hardware configuration example) The multi-factor verification system can be realized, for example, by causing a computer to execute a program. This computer may be a physical computer or a virtual machine on the cloud.

[0115] That is, the multi-factor matching system can be realized by executing a program corresponding to the processing performed by the multi-factor matching system using hardware resources such as a CPU and memory built into a computer. The above program can be recorded on a computer-readable recording medium (such as a portable memory) and stored or distributed. The above program can also be provided via a network such as the Internet or email.

[0116] Fig. 11 is a diagram showing an example of the hardware configuration of the computer. The computer in Fig. 11 includes a drive device 1000, an auxiliary storage device 1002, a memory device 1003, a CPU 1004, an interface device 1005, a display device 1006, an input device 1007, an output device 1008, and the like, all of which are interconnected via a bus BS.

[0117] The program for realizing the processing on the computer is provided by a recording medium 1001 such as a CD-ROM or a memory card. When the recording medium 1001 storing the program is set in the drive device 1000, the program is installed from the recording medium 1001 to the auxiliary storage device 1002 via the drive device 1000. However, the program does not necessarily have to be installed from the recording medium 1001, but may be downloaded from another computer via a network. The auxiliary storage device 1002 stores the installed program as well as necessary files, data, etc.

[0118] The memory device 1003 reads out and stores the program from the auxiliary storage device 1002 when an instruction to start the program is received. The CPU 1004 realizes functions related to the light touch maintenance device 100 in accordance with the program stored in the memory device 1003. The interface device 1005 is used as an interface for connecting to a network, etc. The display device 1006 displays a GUI (Graphical User Interface) or the like according to a program. The input device 1007 is composed of a keyboard and mouse, buttons, a touch panel, etc., and is used to input various operation instructions. The output device 1008 outputs the results of calculations.

[0119] (Points and Effects of the Embodiment) As described above, in this embodiment, multi-factor matching is adopted for precise (reliable) projection.

[0120] More specifically, network information is used for multi-factor verification. That is, network information is essential as a social infrastructure for realizing CPS, and is useful as a reliable and wide-ranging information source, so network information is used in this embodiment. In addition, network information is used from the viewpoint of assuming application to areas where mission-criticality must be guaranteed, even if some cost is incurred.

[0121] Furthermore, in this embodiment, in addition to real-time positioning results that utilize NW information, it is also possible to refer to past positioning results and base station connection history.

[0122] In other words, it is possible to take into account the results of network positioning, whether the connected base stations are extremely distant, and whether there is evidence of a certain degree of continuous stay, taking into account the time the power (communication function) is turned off, as comparison factors.

[0123] In addition, in this embodiment, it is possible to refer to the projection history onto cyberspace based on the "network management ID of an object," which is expected to be used as an identifier in the physical space of an object with communication means.

[0124] This makes it possible to take into account the time the power (communication function) has been turned off, and also to take into account factors such as whether there is continuity with past projections and the reliability of the object (information delivered from the object) estimated from the multi-factor matching history.

[0125] As described above, in this embodiment, problems that may occur on the object side in the physical space that is projected into cyberspace are addressed based on information that can be obtained on the network side and that is difficult for the object side to falsify, thereby making it possible to improve the reliability of cyberspace.

[0126] (Additional Note) This specification discloses at least the following multi-factor verification system, multi-factor verification method, and program: (Section 1) A multi-factor authentication system in a cyber-physical system in which physical space and cyber space are connected by a network, a collation unit that determines whether or not to project the object into the cyberspace based on first position information, which is position information of the object in the physical space obtained by a positioning means, and second position information, which is position information of the object obtained by a means other than the positioning means; a projection unit that projects the object into the cyberspace when the collation unit determines that the object should be projected into the cyberspace; A multi-factor verification system comprising: (Section 2) The collation unit compares the first location information with the second location information to determine a reliability of the first location information, and determines whether or not to project the object into the cyberspace based on the reliability. 2. The multi-factor verification system of claim 1. (Section 3) The second location information includes one or more pieces of location information obtained by one or more means, and the projection unit performs projection into the cyberspace using the first location information and most probable location information among the one or more pieces of location information, or location information estimated based on the first location information and at least one piece of location information among the one or more pieces of location information. 3. A multi-factor verification system according to claim 1 or 2. (Section 4) The collation unit determines whether to project the object into the cyberspace based on a comparison result between the first location information and the second location information, as well as a continuity of a location transition of the object, a continuity of a base station connection of the object, or a continuity of a projection of the object. A multi-factor verification system according to any one of claims 1 to 3. (Section 5) The collation unit determines whether or not to project the object into the cyberspace based on a difference between real-time position information of the object and position information obtained by predicting the position of the object, in addition to a comparison result between the first position information and the second position information. A multi-factor verification system according to any one of claims 1 to 4. (Section 6) The collation unit determines whether or not to project the object into the cyberspace based on a comparison result between the first location information and the second location information as well as a collation history indicating whether or not projection onto the object has been permitted. 6. A multi-factor verification system according to any one of claims 1 to 5. (Section 7) A multi-factor authentication method executed by a multi-factor authentication system in a cyber-physical system in which a physical space and a cyber space are connected by a network, comprising: a comparison step of determining whether or not to project the object into the cyberspace based on first position information, which is position information of the object in the physical space obtained by a positioning means, and second position information, which is position information of the object obtained by a means other than the positioning means; a projection step of projecting the object into the cyberspace when it is determined by the collation step that the object should be projected into the cyberspace; A multi-factor verification method comprising: (Section 8) A program for causing a computer to function as each unit in the multi-factor verification system according to any one of claims 1 to 6.

[0127] Although the present embodiment has been described above, the present invention is not limited to such a specific embodiment, and various modifications and variations are possible within the scope of the gist of the present invention described in the claims. [Explanation of symbols]

[0128] 10 Terminal 20 Servers 110 Projection section 120 Projection Information Management Department 130 Collation Unit 140 NW Information Management Department 150 Positioning unit that performs network positioning 160 Others position estimation management department 170 Other position estimation unit 200 Cyberspace (Digital Twin) 300 objects 310 Positioning Unit 1000 Drive Device 1001 Recording media 1002 Auxiliary storage device 1003 Memory device 1004 CPU 1005 Interface device 1006 Display device 1007 Input Device

Claims

1. A multi-factor authentication system in a cyber-physical system in which physical space and cyberspace are connected by a network, a collation unit that determines whether or not to project the object into the cyberspace based on first position information, which is position information of the object in the physical space obtained by a positioning means, and second position information, which is position information of the object obtained by a means other than the positioning means; a projection unit that projects the object into the cyberspace when the collation unit determines that the object should be projected into the cyberspace, The collation unit compares the first location information with the second location information to determine a reliability of the first location information, and determines whether or not to project the object into the cyberspace based on the reliability. Multi-factor matching system.

2. The second location information includes one or more pieces of location information obtained by one or more means, and the projection unit performs projection into the cyberspace using the first location information and most probable location information among the one or more pieces of location information, or location information estimated based on the first location information and at least one piece of location information among the one or more pieces of location information. The multi-factor verification system of claim 1 .

3. The collation unit determines whether to project the object into the cyberspace based on a comparison result between the first location information and the second location information, as well as a continuity of a location transition of the object, a continuity of a base station connection of the object, or a continuity of a projection of the object. A multi-factor verification system according to claim 1 or 2.

4. The collation unit determines whether or not to project the object into the cyberspace based on a difference between real-time position information of the object and position information obtained by position prediction of the object, in addition to a comparison result between the first position information and the second position information. A multi-factor verification system according to any one of claims 1 to 3.

5. The collation unit determines whether or not to project the object into the cyberspace based on a comparison result between the first location information and the second location information as well as a collation history indicating whether or not projection onto the object has been permitted. A multi-factor verification system according to any one of claims 1 to 4.

6. A multi-factor verification method executed by a multi-factor verification system in a cyber-physical system in which a physical space and a cyberspace are connected by a network, comprising: a comparison step of determining whether or not to project the object into the cyberspace based on first position information, which is position information of the object in the physical space obtained by a positioning means, and second position information, which is position information of the object obtained by a means other than the positioning means; a projection step of projecting the object into the cyberspace when it is determined by the collation step that the object should be projected into the cyberspace, In the matching step, the multi-factor matching system compares the first location information with the second location information to determine the reliability of the first location information, and determines whether or not to project the object into the cyberspace based on the reliability. Multi-factor matching methods.

7. A program for causing a computer to function as each unit in the multi-factor verification system according to any one of claims 1 to 5.

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