Abstract: A module for a vehicle includes: a first communication module that transmits and receives first data to and from a first in-vehicle module; a second communication module that transmits and receives second data to and from a second in-vehicle module; and a control module that controls relay of third data among the first communication module and the second communication module. In a case where reception data received by the control module from the first or second communication module is unauthorized, the control module stops relaying the third data in accordance with a traveling state of the vehicle satisfying a predetermined condition, The traveling state includes: the vehicle being stopped; a vehicle speed being at or below a predetermined speed; brakes being applied; a hazard indicator being on; a driver being in a state capable of driving; and/or self-driving functions being in an off state.

Abstract: An attack detection method includes determining a sampling rule including a sampling interval and a sampling time on the basis of at least one of a statistic indicating a variation in sensor values included in the sensor data or event information on the mobility entity, which indicates the timing of a change in sensor values; generating sampling data including two or more sensor values selected from the sensor data on the basis of the sampling interval and the sampling time, first order information, and second order information; and calculating a first anomaly score indicating the degree of anomalies in the evaluation target data and a second anomaly score indicating the degree of anomalies in the evaluation target data, determining on the basis of the calculated first and second anomaly scores whether the evaluation target data has resulted from the attack, and outputting a determination result.

Abstract: An anomaly detection device includes: an obtainer that obtains vehicle information related to the status of a vehicle and including location data indicating the location of the vehicle; a model storage that stores, for each of a plurality of cells of a grid imposed on a map, an evaluation model for evaluating the vehicle information of the vehicle located at the cell; and a determiner that calculates, based on the vehicle information and evaluation models each being the evaluation model and corresponding to evaluation cells including a first cell including the location of the vehicle indicated in the location data and one or more second cells each having a predetermined positional relationship with the first cell, an anomaly level indicating a degree of anomaly of the vehicle information, determines, based on the anomaly level, whether the vehicle information is anomalous, and outputs a determination result.

Abstract: An information processing method is executed by an information processing system that analyzes an attack scenario by obtaining anomaly logs detected by mobile bodies. The method includes: obtaining, from a mobile body, an anomaly log indicating an anomaly of the mobile body; and when a detection detail of the anomaly included in the anomaly log and indicated by a first attack scenario does not match a detection detail of an anomaly indicated by any one of at least one second attack scenario that has been analyzed and matches a detection detail of an anomaly indicated by a third attack scenario among at least one third attack scenario that has not yet been analyzed, performing a process for the anomaly log as a first anomalous event occurring to the mobile body, after waiting until the third attack scenario has been analyzed.

Abstract: An anomaly detection device includes: an obtainer that obtains vehicle information related to the status of a vehicle and including location data indicating the location of the vehicle; a model storage that stores, for each of a plurality of cells of a grid imposed on a map, an evaluation model for evaluating the vehicle information of the vehicle located at the cell; and a determiner that calculates, based on the vehicle information and evaluation models each being the evaluation model and corresponding to evaluation cells including a first cell including the location of the vehicle indicated in the location data and one or more second cells each having a predetermined positional relationship with the first cell, an anomaly level indicating a degree of anomaly of the vehicle information, determines, based on the anomaly level, whether the vehicle information is anomalous, and outputs a determination result.

Abstract: A server includes memory and a processor that obtains a log created by a first node monitored on a V2X network, selects predetermined information therefrom, and performs supervised machine learning using the selected predetermined information as training data to create a model for a monitoring node that monitors the first node. The log associatively includes a time, and at the time: first node status information as indicated by at least one of sensor or control data on the first node; first anomaly information indicating whether an anomaly occurred on the first node; and second anomaly information indicating whether an anomaly occurred on a second, surrounding node of the first node that communicates with the first node. When the first anomaly information indicates an anomaly, or when the first and second anomaly information indicate no anomaly and an anomaly, respectively, the associated status information is selected as the predetermined information.

Abstract: A vehicle anomaly detection server includes: a communicator that communicates with a vehicle to receive a log of an in-vehicle network in the vehicle; a processor; and a memory including at least one set of instructions that, when executed by the processor causes the processor to perform operations including: selecting, when information indicating that an anomaly is occurring to a first vehicle among vehicles is obtained by the processor, an anomaly-related vehicle from among the vehicles based on the anomaly, the first vehicle being the vehicle that communicates with the communicator; transmitting, to the anomaly-related vehicle via the communicator, a first request to transmit a log of an in-vehicle network in the anomaly-related vehicle; and determining whether an anomaly is occurring to the anomaly-related vehicle, based on information indicated by the log transmitted from the anomaly-related vehicle and received by the communicator.

Abstract: A gateway that notifies a fraud detection server located outside a vehicle of information about an in-vehicle network system including an in-vehicle network includes: a priority determiner that determines a priority using at least one of: a state of the vehicle including the in-vehicle network system; an identifier of a message communicated on the in-vehicle network; and a result of fraud detection performed on the message; a frame transmitter-receiver that transmits and receives the message communicated on the in-vehicle network; a frame interpreter that extracts information about the in-vehicle network based on the message received by the frame transmitter-receiver; and a frame uploader that notifies the fraud detection server of notification information including the priority and the information about the in-vehicle network.

Abstract: A monitoring server of an in-vehicle control network system includes a threat information generator that obtains first threat information pertaining to a threat that has occurred in a vehicle of a first vehicle type, a threat information abstractor that generates abstracted threat information by deleting information specific to the first vehicle type from the first threat information, and a display that outputs second threat information generated based on the abstracted threat information and including a risk value indicating a risk level of the threat to a second vehicle type different from the first vehicle type.

Abstract: A threat information analysis server includes: an update manager that manages update information indicating that function addition to an IoT device is performed; a threat information manager that stores threat information of a cyberattack; a risk level manager that manages risk level information defining a risk level of the IoT device; a related threat information manager that manages the threat information and related threat information associating the IoT device with the risk level; a risk level updater that associates the threat information and the risk level of the IoT device with each other and updates the related threat information, based on the update information; and an outputter that outputs the related threat information managed by the related threat information manager.

Abstract: A threat information analysis server includes: an update manager that manages update information indicating that function addition to an IoT device is performed; a threat information manager that stores threat information of a cyberattack; a risk level manager that manages risk level information defining a risk level of the IoT device; a related threat information manager that manages the threat information and related threat information associating the IoT device with the risk level; a risk level updater that associates the threat information and the risk level of the IoT device with each other and updates the related threat information, based on the update information; and an outputter that outputs the related threat information managed by the related threat information manager.

Abstract: In an anomaly detection method that determines whether each frame in observation data constituted by a collection of frames sent and received over a communication network system is anomalous, a difference between a data distribution of a feature amount extracted from the frame in the observation data and a data distribution for a collection of frames sent and received over the communication network system, obtained at a different timing from the observation data, is calculated. A frame having a feature amount for which the difference is predetermined value or higher is determined to be an anomalous frame. An anomaly contribution level of feature amounts extracted from the frame determined to be an anomalous frame is calculated, and an anomalous payload part, which is at least one part of the payload corresponding to the feature amount for which the anomaly contribution level is at least the predetermined value, is output.

Abstract: An information processing apparatus connected to one or more vehicles and a threat information server storing pieces of threat information. The information processing apparatus includes: a processor; and a memory including at least one set of instructions that, when executed by the processor, causes the processor to perform: obtaining a detection result of an attack on one of the vehicles; (a) determining whether the attack is included in any one of the pieces of threat information; (b) when the attack is included therein, determining whether the resolution state to the attack included in the one of the pieces of threat information indicates that the attack has not been resolved or has been resolved; (c) deciding a processing priority level of the attack, based on a determination result in (a) and a determination result in (b); and (d) outputting the processing priority level decided.

Abstract: A gateway that notifies a fraud detection server located outside a vehicle of information about an in-vehicle network system including an in-vehicle network includes: a priority determiner that determines a priority using at least one of: a state of the vehicle including the in-vehicle network system; an identifier of a message communicated on the in-vehicle network; and a result of fraud detection performed on the message; a frame transmitter-receiver that transmits and receives the message communicated on the in-vehicle network; a frame interpreter that extracts information about the in-vehicle network based on the message received by the frame transmitter-receiver; and a frame uploader that notifies the fraud detection server of notification information including the priority and the information about the in-vehicle network.

Abstract: A module for a vehicle includes: a first communication module that transmits and receives first data to and from a first in-vehicle module; a second communication module that transmits and receives second data to and from a second in-vehicle module; and a control module that controls relay of third data among the first communication module and the second communication module. In a case where reception data received by the control module from the first or second communication module is unauthorized, the control module stops relaying the third data in accordance with a traveling state of the vehicle satisfying a predetermined condition, The traveling state includes: the vehicle being stopped; a vehicle speed being at or below a predetermined speed; brakes being applied; a hazard indicator being on; a driver being in a state capable of driving; and/or self-driving functions being in an off state.

Abstract: A vehicle monitoring apparatus includes: a first communicator that receives specifying information for specifying a target vehicle from a server; and an acquirer that acquires driving information from the target vehicle, the driving information being information regarding driving of the target vehicle specified by the specifying information received by the first communicator. The first communicator transmits the driving information acquired by the acquirer to the server. For example, the acquirer may acquire the driving information obtained from the target vehicle through communication.

Abstract: An anomaly detection device is located between a network and a first ECU in the plurality of ECUs, and includes: a communication circuit; a processor; and a memory including a set of instructions that, when executed, causes the processor to perform operations including: receiving a message from the first ECU and transmitting the message to the network, and receiving a message from the network and transmitting the message to the first ECU, using the communication circuit; holding, in the memory, a received ID list; when an ID of the message received by the communication circuit from the network is not included in the received ID list, adding the ID to the received ID list; and when an ID of the message received by the communication circuit from the first ECU is included in the received ID list, causing the communication circuit not to transmit the message to the network.

Abstract: A gateway that notifies a fraud detection server located outside a vehicle of information about an in-vehicle network system including an in-vehicle network includes: a priority determiner that determines a priority using at least one of: a state of the vehicle including the in-vehicle network system; an identifier of a message communicated on the in-vehicle network; and a result of fraud detection performed on the message; a frame transmitter-receiver that transmits and receives the message communicated on the in-vehicle network; a frame interpreter that extracts information about the in-vehicle network based on the message received by the frame transmitter-receiver; and a frame uploader that notifies the fraud detection server of notification information including the priority and the information about the in-vehicle network.

Abstract: An in-vehicle relay device for a vehicle is provided. The in-vehicle relay device includes a first communication circuit that transmits and receives first data to and from a first in-vehicle equipment in the vehicle. A second communication circuit transmits and receives second data to and from a second in-vehicle equipment in the vehicle. A control circuit controls relay of third data among the first communication circuit and the second communication circuit. In a case where reception data received by the control circuit from the first communication circuit or the second communication circuit is unauthorized, the control circuit stops relaying the third data in accordance with a traveling state of the vehicle.

Abstract: An information processing device comprising: a processor; and a memory including at least one set of instructions that, when executed by the processor, causes the processor to perform operations. The operations include: obtaining incident information about an incident of a cyberattack that occurred in a vehicle; obtaining second vehicle information about a state of a second vehicle via communication with the second vehicle; determining a risk level of a vehicle function of the second vehicle based on a degree of matching between the incident information and the second vehicle information; generating a function restriction command for restricting a vehicle function of a first vehicle corresponding to the vehicle function of the second vehicle, when the risk level is higher than a first criterion, the vehicle function of the first vehicle being one among one or more vehicle functions of the first vehicle; and outputting the function restriction command.