Abstract: Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements, automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.

Abstract: Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements, automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.

Abstract: One embodiment provides a computing device for remote experiential teambuilding activities. The computing device includes a communication circuitry and a user interface (UI). The communication circuitry is configured to couple to a remote computing device via a network. The remote computing device is associated with a remote participant. The UI is configured to receive a local user input from a local participant, and to provide at least one of a local device output or a remote device output to the local participant. The local user input, local device output and remote device output are related to a selected experiential activity.

Abstract: Methods and systems for cross-platform user profiling based on disparate datasets using machine learning models. Specifically, the system may monitor native asset data of an asset corresponding to a cross-platform profile, wherein the cross-platform profile comprises a profile linked to an account, for a user, that is used across multiple assets. The system may detect, using a machine learning model, an incident of the user based on telemetry data extracted from the native asset data. The system may update a status of the cross-platform profile based on the incident. The system may generate for presentation, in a user interface for the account, the status of cross-platform profile and reconstructed asset data based on the incident.

Abstract: Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements, automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.

Abstract: Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements; automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.

Abstract: Methods and systems for detecting disparate incidents in processed data using a plurality of machine learning models. For example, the system may receive native asset data. The system may extract telemetry data from the native asset data. The system may input the first feature input into a first machine learning model, wherein the first machine learning model is trained to detect known incidents of a first type in a first set of labeled telemetry data. The system may then detect a first incident based on a first output from the first machine learning model, wherein the first incident is a first event in an asset related to the user's behavior.

Abstract: Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements; automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.

Abstract: Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Some embodiments involve using continual or periodic data collecting to improve inferential analysis, as well as obtaining circumstantial or inferential information from social networks. Machine learning may be used to improve predicitive capabilities. Some embodiments allow for identification of an entity from circumstantial or inferential information based on the machine learning and comparative analyses.

Abstract: Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Some embodiments involve using continual or periodic data collecting to improve inferential analysis, as well as obtaining circumstantial or inferential information from social networks. Machine learning may be used to improve predicitive capabilities. Some embodiments allow for identification of an entity from circumstantial or inferential information based on the machine learning and comparative analyses.

Abstract: Various embodiments disclosed include, for each entity in a portfolio, receiving entity data indicative of attributes of an entity, determining the received entity data for at least some entities is missing a portion of the entity data required to perform a cyber risk analysis; and synthesizing the missing portion. The method may further include comparing the received entity data and synthesized missing portion for each of the entities to each other; locating clusters of similar entity data shared between two or more of the entities; and calculating a cyber risk score representing how different the entities are to one another based on the entity data that are not shared between entities. Some embodiments include comparing entities that are missing some entity data to entities which have complete entity data, and generating a synthesized portfolio by selecting entities having complete entity data to replace the entities that are missing entity data.

Abstract: Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Some embodiments involve using continual or periodic data collecting to improve inferential analysis, as well as obtaining circumstantial or inferential information from social networks. Machine learning may be used to improve predicitive capabilities. Some embodiments allow for identification of an entity from circumstantial or inferential information based on the machine learning and comparative analyses.

Abstract: Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Some embodiments involve using continual or periodic data collecting to improve inferential analysis, as well as obtaining circumstantial or inferential information from social networks. Machine learning may be used to improve predicitive capabilities. Some embodiments allow for identification of an entity from circumstantial or inferential information based on the machine learning and comparative analyses.

Abstract: An adhesive tape cutting device includes a sleeve body having a top wall that has a tape slot defined by a slot-defining wall having a rear edge, front and rear end portions, and a protruded portion disposed between the rear edge and the front end portion. The tape slot separates the rear end portion and the protruded portion. The protruded portion extends outwardly and radially, through a tangent line passing through the rear edge, from one side of the tangent line to the other side of the tangent line. The protruded portion has a planar abutting surface, inclined away from the adhesive tape roll in a forward direction, and having opposite front and rear ends. The rear end is disposed on one side of a first reference line connecting the rear edge and the front end. The front end is disposed on one side of a second reference line connecting the rear edge and a tip of said cutting member.

Abstract: An adhesive tape cutting device includes: a sleeve body sleeved on an adhesive tape roll and having a top wall defining a tape slot, the tape slot being defined by a slot-defining wall having opposite front and rear edges, the top wall having front and rear end portions and a protruded portion disposed between and protruding outwardly from the front end portion and the slot-defining wall, the rear end portion and the protruded portion being separated by the tape slot, the protruded portion extending outwardly and radially through a tangent line from one side of the tangent line to the other side of the tangent line; and a cutting member mounted on the front end portion of the top wall of the sleeve body.