Abstract: An outboard motor in which an exhaust pipe arrangement is easily performed and the center of gravity can be lowered. Cylinders where pistons operate are arranged in a V-shape and a crankshaft driven by driving of the pistons is disposed vertically, and upper exhaust pipes (exhaust pipes) communicating with exhaust openings in the respective banks of a cylinder head and a catalyst holder that is provided in a position, which corresponds to a lower side of the cylinder, of the upper exhaust pipe and that holds a catalyst are included. In this manner, arrangement of the upper exhaust pipe and a lower exhaust pipe is easily performed while the catalytic effect is maintained and the center of gravity can be lowered, and also, the size and weight of the V-type engine can be reduced.

Abstract: A V-type engine, an outboard motor, and a ship capable of restricting exposure of a catalyst to water. The engine includes cylinders where pistons operate are arranged in a V-shape, a crankshaft driven by driving of the pistons is disposed vertically, and exhaust pipes communicating with exhaust openings in the respective banks of a cylinder head and a catalyst holder that holds a catalyst in a merge portion where the exhaust pipes are merged in a site located on an upper side of the banks are included.

Abstract: An operation assistance system for a small watercraft includes: a position specification unit that specifies an abnormality occurrence position, which is a position where an abnormality has occurred, when the abnormality has occurred in a small watercraft; a transmission unit that transmits information on the abnormality occurrence position specified by the position specification unit; and a processing circuit, in which the processing circuit includes a storage unit that stores information on the abnormality occurrence position transmitted from the transmission unit, and an information provision unit that creates predetermined operation assistance information based on information on the abnormality occurrence position stored in the storage unit and transmits the created operation assistance information.

Abstract: A signature generation unit (132) generates a signature in which header information of packet data included in traffic data is correlated with a label representing a category for an application corresponding to the packet data. A flow data generation unit (131) generates flow data from the packet data. An assigning unit (134) assigns the label to the flow data on the basis of the signature and the header information of the flow data. A calculation unit (135) calculates a feature amount of the flow data. A learning unit (136) learns a model for predicting a label from the feature amount using the label and the feature amount of the flow data to which the label is assigned.

Abstract: A detection device includes processing circuitry configured to collect communication information in a network including clients and servers, generate a matrix representing states of access from the clients to the servers using the communication information collected, aggregate a plurality of the clients accessing a target server and generate statistical information of similiarities between the aggregated clients in the matrix as a feature amount of the target server, learn, with regard to the target server which is a server for which it is known whether the server is a malicious server, a model for determining whether a server is a malicious server using the feature amount generated, and determine, with regard to the target server which is a server for which it is unknown whether the server is a malicious server, whether the target server is a malicious server using the feature amount generated and the model.

Abstract: A detection device includes processing circuitry configured to identify candidate bots using flow data, use the flow data to count a number of the candidate bots communicating with servers, for each of the servers, and determine servers communicating with a predetermined number or more of the candidate bots among the servers to be malicious servers, and detect candidate bots communicating with the malicious servers that are determined among the candidate bots to be malicious bots.

Abstract: A signature generation unit (132) generates a signature in which header information of packet data included in traffic data is correlated with a label representing a category for an application corresponding to the packet data. A flow data generation unit (131) generates flow data from the packet data. An assigning unit (134) assigns the label to the flow data on the basis of the signature and the header information of the flow data. A calculation unit (135) calculates a feature amount of the flow data. A learning unit (136) learns a model for predicting a label from the feature amount using the label and the feature amount of the flow data to which the label is assigned.

Abstract: A classification apparatus 10 acquires a communication log including a plurality of pieces of traffic data, and extracts different types of feature values from the plurality of pieces of traffic data. Subsequently, the classification apparatus 10 classifies the traffic data on a per IP address basis based on the extracted different types of feature values, and uses a plurality of classification results to count the number of times of appearance of a pattern having the same combination of the classification results.