Abstract: An estimation device includes processing circuitry configured to extract a fixed-length feature amount from a payload of communication data, calculate a similarity between feature amounts of abnormal communication data, and determine that events are of a same type when the calculated similarity is greater than a predetermined threshold.

Abstract: A learning device includes processing circuitry configured to calculate a degree of deviation between a first output obtained by inputting first training data to a learned first model and a second output obtained by inputting second training data created by giving noise to the first training data to a second model, and a degree of deviation between an intermediate representation of the first model generated in a process of obtaining the first output and an intermediate representation of the second model generated in a process of obtaining the second output, and update a parameter of the second model so that the degree of deviation between the first output and the second output and the degree of deviation between the intermediate representation of the first model and the intermediate representation of the second model are reduced.

Abstract: A detection device includes processing circuitry configured to acquire data to be detected and normal reference data, calculate a Learned Perceptual Image Patch Similarity (LPIPS) distance between the acquired data and the reference data, and classify the acquired data into either a Clean Sample or an Adversarial Example by using the calculated LPIPS distance.

Abstract: A detection device includes a feature value database configured to store a packet feature value, a label assigned to each packet feature value, and a threshold used for determination in advance. The detection device includes a memory and a processor coupled to the memory. The processor is configured to perform operations including: converting a target packet into a feature value using a first natural language processing model that has been trained using normal communication packets as learning data; assigning a label to the feature value converted using the first natural language processing model, based on the feature value converted using the first natural language processing model and the data stored in the feature value database; and determining whether the target packet has an anomaly based on the assigned label.

Abstract: An evaluation device receives input of latent variables of a variational autoencoder, clusters the input latent variables, and assigns, for each cluster, a label indicating the cluster to latent variables belonging to the cluster. After that, the evaluation device performs learning of a classifier so as to accurately classify the latent variables based on the assigned label, performs an adversarial attack resistance evaluation for the classifier after learning, and outputs a result of the resistance evaluation. Thus, the evaluation device can perform an adversarial attack resistance evaluation even for a variational autoencoder that uses unlabeled data as input data.

Abstract: A low-temperature storage system 100 is provided, which can, with a simple structure, minimize heat transfer into the low-temperature storage chamber, reduce the operation noise, allow easy positioning of a reciprocating part inside the low-temperature storage chamber, and preclude device bulkiness outside the low-temperature storage chamber. The low-temperature storage system 100 includes a low-temperature storage chamber 110, and a transfer mechanism 120. The transfer mechanism 120 includes an in-storage unit 121 and an external unit 140. The in-storage unit 121 includes a reciprocating part 122 that holds the storage objects C, a turn guide 126 that guides the reciprocating part 122, and a lift member 131 that causes the reciprocating part 122. The external unit 140 includes a torque transmission part 141, a lift transmission part 147, and a detachable moving part 150 that drives the torque transmission part 141 and lift transmission part 147.

Abstract: An estimation device includes processing circuitry configured to generate a feature quantity by performing invertible transformation on a payload of a packet character by character with respect to each packet determined to be abnormal or normal by an abnormality detector, and give a determination result as to whether a packet is abnormal or normal to the generated feature quantity, learn a model that classifies whether the packet is abnormal or normal by machine learning using the feature quantity of the payload of the packet and the determination result as to whether the packet is abnormal or normal as teacher data, extract a number of dimensions of the feature quantity in which a contribution degree to classification is equal to or greater than a predetermined value in the learned model, and estimate a cause part of abnormality in the payload of the packet determined to be abnormal.

Abstract: A detection device includes acquisition circuitry, conversion circuitry, and detection circuitry. The acquisition circuitry acquires data to be classified using a model. The conversion circuitry converts the data acquired using noise in a predetermined direction. The detection circuitry detects an adversarial example using a change in output between the data acquired and the data converted, at a time when the data acquired and the data converted are input to the model.

Abstract: The present invention aims at providing a workpiece transfer method and a workpiece transfer system that enable stable transfer of workpieces with a simple structure. The workpiece transfer system includes two workpiece holding members that hold workpieces such as to be inserted and pulled out in a vertical direction, a picking device having a claw member operable to open and close, and a temporary workpiece holding member. The workpiece transfer method includes: grasping and transferring a workpiece that is held by one workpiece holding member to a temporary workpiece holding member, and transferring the workpiece from the temporary workpiece holding member to another workpiece holding member after the workpiece has been grasped again at a point where the workpiece is held in a stable posture.

Abstract: An evaluation device receives input of latent variables of a variational autoencoder, clusters the input latent variables, and assigns, for each cluster, a label indicating the cluster to latent variables belonging to the cluster. After that, the evaluation device performs learning of a classifier so as to accurately classify the latent variables based on the assigned label, performs an adversarial attack resistance evaluation for the classifier after learning, and outputs a result of the resistance evaluation. Thus, the evaluation device can perform an adversarial attack resistance evaluation even for a variational autoencoder that uses unlabeled data as input data.

Abstract: A low-temperature storage system 100 is provided, which can, with a simple structure, minimize heat transfer into the low-temperature storage chamber, reduce the operation noise, allow easy positioning of a reciprocating part inside the low-temperature storage chamber, and preclude device bulkiness outside the low-temperature storage chamber. The low-temperature storage system 100 includes a low-temperature storage chamber 110, and a transfer mechanism 120. The transfer mechanism 120 includes an in-storage unit 121 and an external unit 140. The in-storage unit 121 includes a reciprocating part 122 that holds the storage objects C, a turn guide 126 that guides the reciprocating part 122, and a lift member 131 that causes the reciprocating part 122. The external unit 140 includes a torque transmission part 141, a lift transmission part 147, and a detachable moving part 150 that drives the torque transmission part 141 and lift transmission part 147.

Abstract: A low temperature storage system, a transport mechanism, and a low temperature storage vessel are provided, which enable downsizing and simplification of the transport mechanism, as well as stable transport of stored objects. A low temperature storage system (1) includes a low temperature storage vessel (10) and a transport mechanism (20). The transport mechanism (20) includes a reciprocating part (30) that has a holding part (35) and that is capable of reciprocating along a transfer direction, and guide unit (40). The guide unit (40) include an in-vessel guide (50) fixedly placed inside the low temperature storage vessel (10), and a telescopic guide (60) configured to be able to extend and contract along the transfer direction. The telescopic guide (60) is provided independently of the in-vessel guide (50) so as to be connectable to the in-vessel guide (50).

Abstract: A low temperature storage system, a transport mechanism, and a low temperature storage vessel are provided, which enable downsizing and simplification of the transport mechanism, as well as stable transport of stored objects. A low temperature storage system (1) includes a low temperature storage vessel (10) and a transport mechanism (20). The transport mechanism (20) includes a reciprocating part (30) that has a holding part (35) and that is capable of reciprocating along a transfer direction, and guide unit (40). The guide unit (40) include an in-vessel guide (50) fixedly placed inside the low temperature storage vessel (10), and a telescopic guide (60) configured to be able to extend and contract along the transfer direction. The telescopic guide (60) is provided independently of the in-vessel guide (50) so as to be connectable to the in-vessel guide (50).