Anomaly detection device, image forming apparatus, anomaly detection method, and program

Abstract

The objective is to provide an anomaly detection device that can accurately detect abnormalities in input devices connected to its own equipment. [Solution] An abnormality detection device according to one aspect of the present invention comprises: a receiving unit that receives input operations performed on an input device and generates input operation information; and a determination unit that determines an abnormality of the input device based on the input operation information, which includes the count value of the input operations received within a predetermined period, and abnormality determination conditions stored in a database in advance, wherein the abnormality determination conditions are conditions relating to the count value of the input operations within the predetermined period.

Description

Technical Field

[0001] The present invention relates to an abnormality detection device, an image forming apparatus, an abnormality detection method, and a program.

Background Art

[0002] Techniques for detecting abnormalities in input interface devices such as touch panels and touch pads are known. Patent Document 1 discloses a technique for determining an abnormal state of an input interface device based on a count determined that a position on a screen selected in an input operation is not a predetermined selection area in an input interface device such as a pen-type input device.

Summary of the Invention

Problems to be Solved by the Invention

[0003] In order to make it easier for a user to determine whether an abnormality is in the device itself or in an input device such as a touch panel or keyboard connected to the device itself, it is required to detect an abnormality in the input device with high accuracy in a short time.

[0004] An object of the present invention is to provide an abnormality detection device that can accurately detect an abnormality in an input device connected to the device itself in order to solve the above problems.

Means for Solving the Problems

[0005] An abnormality detection device according to an aspect of the present invention includes a reception unit that receives an input operation performed on an input device and generates input operation information, and a determination unit that determines an abnormality of the input device based on the input operation information including a count value of the input operation received within a predetermined period and abnormality determination conditions stored in a database in advance. The abnormality determination conditions are conditions related to the count value of the input operation within the predetermined period.

Effects of the Invention

[0006] According to the anomaly detection device of the present invention, anomalies in input devices connected to the device can be detected with high accuracy. [Brief explanation of the drawing]

[0007] [Figure 1] This figure shows a schematic configuration of an anomaly detection system according to the first embodiment of the present invention. [Figure 2] This is a hardware configuration diagram of an anomaly detection device according to the first embodiment of the present invention. [Figure 3] This is a block diagram showing the functional configuration of an anomaly detection device according to the first embodiment of the present invention. [Figure 4] This figure shows an example of abnormality detection conditions according to the first embodiment of the present invention. [Figure 5] This is a diagram illustrating a predetermined area on the screen of an input device according to the first embodiment of the present invention. [Figure 6] This is a flowchart illustrating the anomaly detection method according to the first embodiment of the present invention. [Figure 7] This is a block diagram showing the functional configuration of an anomaly detection device according to the second embodiment of the present invention. [Figure 8] This figure shows an example of corrected abnormality determination conditions according to a second embodiment of the present invention. [Figure 9] This is a flowchart illustrating an anomaly detection method according to a second embodiment of the present invention. [Figure 10] This figure shows a schematic configuration of an image forming apparatus equipped with an anomaly detection device according to a third embodiment of the present invention. [Modes for carrying out the invention]

[0008] The embodiments for carrying out the invention will be described below with reference to the drawings. In each drawing, the same reference numerals are used for identical components, and redundant explanations may be omitted.

[0009] [First Embodiment] <Example Configuration of Anomaly Detection System 1> Figure 1 is a diagram showing the schematic configuration of an anomaly detection system 1 according to the first embodiment of the present invention. As shown in the figure, the anomaly detection system 1 comprises an anomaly detection device 10, an input device 2, and a database 3.

[0010] Input device 2 is a device connected to the anomaly detection device 10, such as a keyboard and mouse. Alternatively, input device 2 may be a device included in the anomaly detection device 10, such as a touch panel. Furthermore, input device 2 may be a terminal device (not shown) equipped with a touch panel, keyboard, and mouse, and connected to the anomaly detection device 10.

[0011] Database 3 may be provided on a server or other device connected to the anomaly detection device 10 via a network, or it may be included in the anomaly detection device 10. Database 3 stores anomaly determination conditions used to determine anomalies in the input device 2.

[0012] The anomaly detection device 10 may be a device included in various devices such as an image forming apparatus, or it may be a device connected to various devices such as an image forming apparatus via a network. The anomaly detection device 10 receives input operations performed on the input device 2 and determines an anomaly in the input device 2 based on the received input operation information and anomaly determination conditions.

[0013] <Example configuration of the anomaly detection device 10> Figure 2 is a hardware configuration diagram of an anomaly detection device 10 according to the first embodiment of the present invention. The anomaly detection device 10 has the function of an information processing device (computer). The anomaly detection device 10 includes a CPU (Central Processing Unit) 101, RAM 102, ROM (Read Only Memory) 103, and I / O (Input / Output) 104 which are interconnected by a bus.

[0014] The CPU 101 controls the entire abnormality detection device 10 by executing the program 105 using the RAM 102 as a work memory. The ROM 103 is a non-volatile memory such as a flash memory and stores the program 105. By executing the program 105, the CPU 101 provides the functions described below. The I / O 104 is an input / output interface.

[0015] FIG. 3 is a block diagram showing the functional configuration of the abnormality detection device 10 according to the first embodiment of the present invention. As shown in the figure, the abnormality detection device 10 includes a reception unit 11, a determination unit 12, and a notification unit 13.

[0016] The reception unit 11 receives an input operation performed on the input device 2. The input operation includes a key operation on the keyboard, a click operation on the mouse, etc. Further, the input operation is various operations by a finger or the like, such as a touch operation, a tap operation, and a swipe operation on a touch panel, for example. The input operation is not limited to an operation that physically contacts the input device 2 such as a touch panel, and also includes a non-contact operation.

[0017] Based on the input operation performed on the input device 2, the reception unit 11 generates input operation information. The reception unit 11 transmits the generated input operation information to the determination unit 12. The input operation information includes a count value of the input operations received within a predetermined period. The predetermined period may be an arbitrary period such as 1 second, for example. The count value is a value corresponding to the number of times of, for example, a click operation on the mouse, a key operation on the keyboard, and a touch operation on the touch panel.

[0018] Further, the input operation information includes coordinate information indicating the position on the screen selected by the input operation, information regarding the key code of the key pressed on the input device 2, and information regarding the time when the input operation was performed.

[0019] The determination unit 12 determines the abnormality of the input device 2 based on the input operation information and the abnormality determination conditions in the database 3 in advance. When there is an item in the input operation information that matches the abnormality determination conditions, the determination unit 12 determines that there is an abnormality in the input device 2. The abnormality of the input device 2 includes, for example, malfunctions such as poor contact of a touch panel, keyboard, mouse, etc., and abnormalities in signals transmitted from the input device 2, but is not limited thereto.

[0020] The abnormality determination conditions are conditions for determining the abnormality of the input device 2 connected to the own device. Hereinafter, the own device may include the abnormality detection device 10 and devices such as an image forming device provided with the abnormality detection device 10.

[0021] The abnormality determination conditions include, for example, conditions related to the count value of input operations within a predetermined period, conditions related to coordinate information and a predetermined area on the screen, conditions related to the key code of the input device 2 permitted to be connected to the own device, and conditions related to a predetermined time zone, etc., but are not limited thereto. The coordinate information is information related to the coordinates of a position selected by a touch operation or the like on a screen such as a touch panel. The predetermined time zone is, for example, a time zone when the possibility that the user performs an input operation is low.

[0022] Based on the abnormality determination conditions, the determination unit 12 determines that there is an abnormality in the input device 2 when the count value included in the input operation information is abnormal a predetermined number of times, and when the position on the screen selected by the input operation is outside the predetermined area.

[0023] Further, based on the abnormality determination conditions, the determination unit 12 determines that there is an abnormality in the input device 2 when the position on the screen selected by the input operation is outside the predetermined area and the count value of the input operations within a predetermined period is equal to or greater than the threshold value.

[0024] Furthermore, the determination unit 12 determines that there is an abnormality in the input device 2 if the key code is not the key code of an input device 2 that is permitted to be connected to its own device, and if the time the input operation was performed falls within a predetermined time period, based on the abnormality determination conditions. If the determination unit 12 determines that there is an abnormality in the input device 2, it notifies the notification unit 13 of this fact.

[0025] The notification unit 13 notifies the user of any abnormality in the input device 2 when the determination unit 12 determines that there is an abnormality in the input device 2. As a result, the user can recognize that there is an abnormality in the input device 2. The notification unit 13 may use means such as sound, such as a buzzer, or means such as illumination of an LED, or means such as notifying an external device, such as a mobile terminal device.

[0026] Here, the abnormality detection conditions will be explained using Figure 4. Figure 4 is a diagram showing an example of abnormality detection conditions according to the first embodiment of the present invention. In the illustrated table, "item" indicates the type of abnormality of the input device 2, and "target input device" indicates the input device 2 that is subject to abnormality detection, such as a keyboard and a mouse. As shown in the illustration, "item," "target input device," and "abnormality detection conditions" may be associated with each other. Note that the abnormality detection conditions are not limited to the illustrated example.

[0027] In the illustrated example, the item "Excessive Input" indicates an abnormality in input device 2 when the number of mouse clicks or other counts exceeds 30 per second. The item "Outside Input Range (Screen A)" indicates an abnormality when, while Screen A is displayed on the device, multiple touch operations are continuously counted that select an area outside the designated area on the screen, such as the screen background where no operation buttons are located.

[0028] The item "Outside Input Range (Screen B)" indicates an abnormality that occurs when, while Screen B (different from Screen A) is displayed on the device, multiple touch operations are continuously counted that select an area outside a predetermined area on the screen, such as the screen background where no operation buttons are located. The item "Outside Input Range (Abnormal Coordinates)" indicates that an area outside the input range is selected by a touch operation on the touch panel, and the coordinate information corresponding to the selected position is abnormal.

[0029] The item "Out of Input Range (Abnormal Key Code)" indicates a case where the key code of a key pressed on input device 2 is not a key code of input device 2 that is permitted to be connected to this device. In the example in the diagram, for example, "KEYCODE_BUTTON_A" is not the "A" key on the keyboard of the operating device, but the "A" button on the gamepad.

[0030] The "Input Time Slot" item indicates when the user's input operation occurred outside of the designated time slot. In the illustrated example, the designated time slot is set to 0:00 to 6:00, a late-night period when users are less likely to perform input operations, but it is not limited to this time slot.

[0031] Here, a predetermined area on the screen of the input device 2 will be explained using Figure 5. Figure 5 is a diagram illustrating a predetermined area on the screen of the input device 2 according to the first embodiment of the present invention. The illustrated example is a screen for selecting a document to be printed in an image forming apparatus.

[0032] In the illustrated example, the document selection screen 200 is a screen for selecting document data to be printed, and includes a list box 201 and a document list display area 202. The list box 201 displays a list of registered names as candidates for retrieval. The document list display area 202 displays a list of documents stored on the device selected in the list box 201.

[0033] The user selects a desired position on the document selection screen 200 by inputting to the input device 2. The selected position is converted into coordinate information. Area R1 is the area on the displayed document selection screen 200 where the user executes a desired function, and corresponds to, for example, the "Cancel" button, the "OK" button, the list box 201, and the document list display area 202. Area R2 is the area of ​​the document selection screen 200 that is not the screen background.

[0034] As already mentioned, the determination unit 12 determines that there is a problem with the input device 2 if the position on the screen selected by the input operation is outside a predetermined area. The predetermined area is the area shown as R1 and R2 in the figure. Therefore, if an area other than areas R1 and R2 is selected multiple times, the determination unit 12 performs a fault determination regarding the input device 2.

[0035] <Anomaly detection method> Figure 6 is a flowchart illustrating the anomaly detection method according to the first embodiment of the present invention.

[0036] First, the reception unit 11 receives input operations performed on the input device 2 and generates input operation information (S101). Then, the determination unit 12 obtains abnormality determination conditions from the database 3 to be used to determine abnormalities in the input device 2 (S102).

[0037] If there are no items in the input operation information that meet the abnormality judgment conditions (NO in S103), the process is completed. If there are items in the input operation information that meet the abnormality judgment conditions (YES in S103), the notification unit 13 notifies that there is an abnormality based on a notification from the judgment unit 12 (S104).

[0038] These steps carry out an anomaly detection method according to one aspect of the present invention. However, the anomaly detection method according to one aspect of the present invention may include other steps as appropriate, depending on the measurement conditions, measurement environment, etc.

[0039] <Effects and Effects of the Anomaly Detection Device 10 According to the First Embodiment> In the abnormality detection device 10 according to this embodiment, the determination unit 12 determines an abnormality in the input device 2 based on the input operation information generated by the reception unit 11 and abnormality determination conditions set in the database 3 in advance. The determination unit 12 determines an abnormality in the input device 2 based on abnormality determination conditions relating to the count value of input operations within a predetermined period.

[0040] Therefore, according to the abnormality detection device 10 of this embodiment, abnormalities in the input device 2 connected to the device can be detected in a short time with high accuracy.

[0041] [Second Embodiment] In the anomaly detection device 10 according to this embodiment, a configuration related to machine learning is added in addition to the configuration according to the first embodiment. The anomaly detection device 10 according to this embodiment will be described below. Note that the same reference numerals are used for components that have already been described, and redundant explanations are omitted.

[0042] Figure 7 is a block diagram showing the functional configuration of an anomaly detection device 10 according to a second embodiment of the present invention. The anomaly detection device 10 includes a reception unit 11, a determination unit 12, a notification unit 13, an estimation unit 14, and a correction unit 15. The details of the reception unit 11, the determination unit 12, and the notification unit 13 are the same as those of the anomaly detection device 10 according to the first embodiment.

[0043] The estimation unit 14 estimates the user's input operation trends using a machine learning model that has acquired user-specific input operation information from the input device 2. User identification may be based on user-specific identification information included in the input operation information generated by the reception unit 11. User-specific identification information may be, but is not limited to, information generated based on login information on the input device 2, including, for example, a keyboard and mouse connected to a terminal device, and a touch panel.

[0044] User-specific identification information is stored in a storage means in association with input operation information. The storage means may be included in the anomaly detection device 10, or it may be included in an image forming apparatus or other device on which the anomaly detection device 10 is installed. Alternatively, the storage means may be included in a server or other device connected to the anomaly detection device 10 via a network. The storage means is composed of RAM and ROM, etc.

[0045] The correction unit 15 corrects the abnormality determination conditions based on the user input operation trends estimated by the estimation unit 14. User input operation trends include, but are not limited to, a high number of inputs per predetermined time, the selected position on the screen being outside a predetermined area, and a high frequency of inputs during late-night hours.

[0046] Figure 8 shows an example of corrected abnormality detection conditions according to a second embodiment of the present invention. In the illustrated table, "Item" indicates the type of abnormality of the input device 2, and "Correction content for abnormality detection conditions" indicates the content of the correction to the abnormality detection conditions shown in Figure 4, based on the user's input operation tendencies. Note that the correction content for abnormality detection conditions is not limited to the illustrated example.

[0047] For example, for users who input a large number of times per predetermined time, the abnormality detection condition for the "excessive input" item is adjusted so that the threshold for the count value per predetermined time is increased. Also, for users whose selected screen position is often outside the predetermined area, the abnormality detection condition for the "outside input range" item is adjusted so that even if the screen position selected by the input operation is outside the predetermined area, it is not judged as an abnormality of the input device 2.

[0048] Furthermore, for users who frequently input data during late-night hours, the abnormality detection criteria for the "input time period" item are modified so that even if the time the input operation was performed falls within a specified time period, the system will not be judged as having an abnormality in the input device 2.

[0049] Figure 9 is a flowchart illustrating an anomaly detection method according to a second embodiment of the present invention. First, the reception unit 11 receives input operations performed on the input device 2 and generates input operation information (S201). User identification information is stored in the storage means in association with the input operation information (S202).

[0050] Then, the estimation unit 14 obtains abnormality determination conditions from the database 3 for machine learning purposes to determine abnormalities in the input device 2 (S203). The estimation unit 14 estimates the user's input operation tendencies using a learning model that has been trained on user-specific input operation information of the input device 2 (S204). The correction unit 15 corrects the abnormality determination conditions based on the user's input operation tendencies estimated by the estimation unit 14 (S205).

[0051] If there are no items in the input operation information that match the corrected abnormality judgment conditions (NO in S206), the process is completed. If there are items in the input operation information that match the corrected abnormality judgment conditions (YES in S206), the notification unit 13 notifies that there is an abnormality based on a notification from the judgment unit 12 (S207).

[0052] These steps carry out an anomaly detection method according to one aspect of the present invention. However, the anomaly detection method according to one aspect of the present invention may include other steps as appropriate, depending on the measurement conditions, measurement environment, etc.

[0053] <Effects of the abnormality detection device 10 according to the second embodiment> In the anomaly detection device 10 according to this embodiment, the anomaly determination conditions are corrected based on the user-specific input operation trends estimated using a learning model. The determination unit 12 determines an anomaly in the input device 2 based on the input operation information and the corrected anomaly determination conditions.

[0054] Therefore, the abnormality detection device 10 according to this embodiment can further improve the accuracy of abnormality detection of the input device 2 by determining abnormalities in the input device 2 based on the characteristics of each user's input operation.

[0055] [Third Embodiment] <Overall configuration of the image forming apparatus 100> Figure 10 is a diagram showing a schematic configuration of an image forming apparatus 100 equipped with an anomaly detection device 10 according to a third embodiment of the present invention. As shown in the figure, the anomaly detection device 10 according to this embodiment is included in the image forming apparatus 100. The anomaly detection device 10 detects anomalies in the input device 2 connected for the operation of the image forming apparatus 100. The configuration of the anomaly detection device 10 may be the configuration of the first and second embodiments already described.

[0056] The image forming apparatus 100 is an MFP (Multifunction Peripheral / Printer / Product) that incorporates functions such as scanning, copying, printing, and facsimile into a single housing. The image forming apparatus 100 has an output function that records full-color or monochrome images onto transfer paper, which is a recording sheet, based on the input image data.

[0057] The image forming apparatus 100 may be an electrophotographic copier. The main body 1M of the image forming apparatus 100 includes a paper feeding unit 20, an image forming unit 30, and an image reading unit 40. An automatic document transport unit 50 (hereinafter referred to as ADF 50) is also arranged on the main body 1M.

[0058] The paper feeding unit 20 transports the fed transfer paper P to the image forming unit 30. The image forming unit 30 can form electrostatic latent images of each color based on the scanned image. Then, toner is transferred onto the electrostatic latent images, and the toner images developed on the multiple photoreceptor drums 31 are primary transferred to the primary transfer unit 32, and the toner images are secondary transferred to the transfer paper P in the secondary transfer unit 33 adjacent to the primary transfer unit 32.

[0059] The transfer paper P, transported to the fuser unit 34, has the full-color image fixed by pressurization and heating within the fuser unit 34. After this, it is sent from the fuser unit 34 to the paper discharge roller pair and discharged onto the paper discharge tray 35 outside the machine.

[0060] In the image reading unit 40, the first carriage 41 illuminates the document sheet S passing over the slit glass 45 with illumination light from a light source. The reflected light that passes through the slit glass 45 and is reflected off the surface (first surface) of the document sheet S is then imaged by the imaging unit 44 via the imaging lens 43 after passing through the mirror members mounted on the first carriage 41 and the second carriage 42, and read as a surface reading image. At the first reading position R, the surface image of the document sheet S may be conjugate with respect to the imaging unit 44 with respect to the imaging lens 43.

[0061] The stopper member 47 is provided between the slit glass 45 and the platen glass 46, and is positioned by stopping against the platen glass 46 when the document placed on it is stopped against the stopper member 47. When reading a document placed on the platen glass 46 while it is stopped against the stopper member 47, the first carriage 41 and the second carriage 42 move in the sub-scanning direction (left-right direction in the figure).

[0062] The first carriage 41 and the second carriage 42 move in the sub-scanning direction at a speed ratio of, for example, 2:1. Even with the movement of the first carriage 41 and the second carriage 42 at such a speed ratio, the optical path length from the surface of the document to the imaging lens 43 does not change.

[0063] Then, as each carriage 41, 42 moves, light is shone from the light source onto the original document, and the reflected light from the original document is reflected back by the mirror members mounted on each carriage 41, 42. The reflected light is then formed into an image by the imaging lens 43 and read by the imaging unit 44.

[0064] The ADF 50 is connected to the upper part of the main body 1M of the image forming apparatus 100 so as to be able to be opened and closed. The connecting means may be formed by a hinge or the like. The ADF 50 is rotated between an open position that exposes the upper surfaces of the slit glass 45 and the platen glass 46 and a closed position that covers the upper surfaces of the slit glass 45 and the platen glass 46.

[0065] The ADF50 is configured as a sheet-through automatic document transport device. The ADF50 comprises a document table 51 which is a document placement platform, a document transport unit 52 consisting of various rollers and guide members, and a document output tray 53 for collecting the document sheets S after image scanning.

[0066] In the ADF 50, the topmost document sheet S of the document placed on the document table 51 is separated one by one and transported by the document transport unit 52 along a predetermined transport path that passes over the slit glass 45. Then, as the document sheet S passes over the slit glass 45, it is read by the image reading unit 40 and then ejected into the document output tray 53.

[0067] <Effects of the abnormality detection device 10 according to the third embodiment> The anomaly detection device 10 according to this embodiment is included in the image forming apparatus 100. Therefore, it can accurately detect anomalies in the input device 2 with respect to input operations to the image forming apparatus 100.

[0068] Although embodiments have been described above, the present invention is not limited to the embodiments described above, and various modifications and improvements are possible within the scope of the present invention.

[0069] Each of the functions of the embodiments described above can be realized by one or more processing circuits. Hereinafter, "processing circuit" as used herein includes processors programmed to execute each function by software, such as processors implemented by electronic circuits, as well as devices such as ASICs (Application Specific Integrated Circuits), DSPs (Digital Signal Processors), FPGAs (Field Programmable Gate Arrays), and conventional circuit modules designed to execute each of the functions described above.

[0070] Examples of the present invention are as follows: <1> An abnormality detection device comprising: a receiving unit that receives input operations performed on an input device and generates input operation information; and a determination unit that determines an abnormality of the input device based on the input operation information, including the count value of the input operations received within a predetermined period, and abnormality determination conditions stored in a database in advance, wherein the abnormality determination conditions are conditions relating to the count value of the input operations within the predetermined period. <2> The input operation information includes coordinate information indicating the position on the screen selected by the input operation, the abnormality determination condition is a condition relating to the coordinate information and a predetermined area on the screen, and the determination unit determines that there is an abnormality in the input device if the position on the screen selected by the input operation is outside the predetermined area. <1> An anomaly detection device as described above. <3> The determination unit determines that there is an abnormality in the input device if the position on the screen selected by the input operation is outside the predetermined area and the count value of the input operation within the predetermined period is equal to or greater than a threshold. <2> An anomaly detection device as described above. <4> The input operation information includes information regarding the key code of a key pressed on the input device, the abnormality determination condition is a condition relating to the key code of the input device permitted to be connected to the device, and the determination unit determines that there is an abnormality in the input device if the key code is not the key code of the input device permitted to be connected to the device. <1> from the above <3> An anomaly detection device as described in any one of the items. <5> The input operation information includes information regarding the time the input operation was performed, the abnormality determination condition is a condition relating to a predetermined time period, and the determination unit determines that there is an abnormality in the input device if the time the input operation was performed falls within the predetermined time period. <1> from the above <4> An anomaly detection device as described in any one of the items. <6> The determination unit further comprises a notification unit that notifies the input device of the abnormality when the determination unit determines that there is an abnormality in the input device, <1> from the above <5> An anomaly detection device as described in any one of the items. <7> The following are further comprising: an estimation unit that estimates the user's input operation tendencies using a learning model that has acquired the user's input operation information for each user of the input device; and a correction unit that corrects the abnormality determination conditions based on the user's input operation tendencies estimated by the estimation unit, <1> from the above <6> An anomaly detection device as described in any one of the items. <8> The aforementioned <1> from the above <7> An image forming apparatus equipped with an anomaly detection device as described in any one of the items. <9> An anomaly detection method performed by an anomaly detection device, comprising the steps of: receiving input operations performed on an input device and generating input operation information; and determining an anomaly in the input device based on the input operation information, which includes the count values ​​of the input operations received within a predetermined period, and an anomaly determination condition stored in a database in advance, wherein the anomaly determination condition is a condition relating to the count values ​​of the input operations within the predetermined period. <10> A program that causes an abnormality detection device to execute a process that receives input operations performed on an input device and generates input operation information, and a process that determines an abnormality in the input device based on the input operation information, which includes the count values ​​of the input operations received within a predetermined period, and abnormality determination conditions, which are conditions related to the count values ​​of the input operations within the predetermined period and are stored in a database in advance. [Explanation of Symbols]

[0071] 1. Anomaly detection system 2 Input devices 3 Databases 10 Anomaly detection device 11 Reception Department 12 Judgment section 13 Hochi Department 14 Estimation part 15 Correction section 100 Image forming apparatus [Prior art documents] [Patent Documents]

[0072] [Patent Document 1] Japanese Patent Publication No. 2017-220165

Claims

1. A receiving unit that receives input operations performed on an input device and generates input operation information, A determination unit that determines an abnormality in the input device based on the input operation information, which includes the count value of the input operation received within a predetermined period, and abnormality determination conditions stored in a database in advance, Equipped with, The aforementioned abnormality determination conditions are conditions relating to the count value of the input operation within the predetermined period. Anomaly detection device.

2. The input operation information includes coordinate information indicating the position on the screen selected by the input operation. The aforementioned abnormality determination conditions are conditions relating to the coordinate information and a predetermined area on the screen, The determination unit determines that there is an abnormality in the input device if the position on the screen selected by the input operation is outside the predetermined area. An anomaly detection device according to claim 1.

3. The determination unit determines that there is an abnormality in the input device if the position on the screen selected by the input operation is outside the predetermined area and the count value of the input operation within the predetermined period is equal to or greater than a threshold. An anomaly detection device according to claim 2.

4. The input operation information includes information regarding the key code of the key pressed in the input device. The aforementioned abnormality determination conditions are conditions relating to the key code of the input device that is permitted to be connected to the device itself, The determination unit determines that there is a problem with the input device if the key code is not the key code of the input device that is authorized to be connected to its own device. An anomaly detection device according to claim 1.

5. The input operation information includes information regarding the time when the input operation was performed. The aforementioned abnormality determination conditions are conditions relating to a predetermined time period, The determination unit determines that there is an abnormality in the input device if the time at which the input operation was performed falls within the predetermined time period. An anomaly detection device according to claim 1.

6. The system further includes a notification unit that notifies the system of an abnormality when the determination unit determines that there is an abnormality in the input device. An anomaly detection device according to claim 1.

7. An estimation unit that estimates the user's input operation trends using a machine learning model that has acquired the input operation information for each user of the input device, A correction unit corrects the abnormality determination conditions based on the user's input operation trends estimated by the estimation unit, An anomaly detection device according to claim 1, further comprising the above.

8. The abnormality detection device is provided according to any one of claims 1 to 7. Image forming apparatus.

9. An anomaly detection method performed by an anomaly detection device, The steps include receiving input operations performed on an input device and generating input operation information, A step of determining an abnormality in the input device based on the input operation information, which includes the count value of the input operation received within a predetermined period, and abnormality determination conditions stored in a database in advance. Includes, The aforementioned abnormality determination conditions are conditions relating to the count value of the input operation within the predetermined period. Anomaly detection method.

10. Anomaly detection device, A process that receives input operations performed on an input device and generates input operation information, A process for determining an abnormality in the input device based on input operation information including the count value of the input operations received within a predetermined period and abnormality determination conditions, which are conditions related to the count value of the input operations within the predetermined period and are stored in a database in advance. A program that executes the command.

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