Abstract: A method for managing requests includes: intercepting a request, wherein the request was initiated by a user using a user interface; extracting content from the request; classifying the content; determining that the request violates an organization's policy; in response to the determining, modifying the request to generate a modified request; issuing the modified request to an artificial intelligence (AI) service, in which the AI service corresponds to the user interface; receiving, in response to the modified request, a response from the AI service; and displaying the response to the user.

Abstract: A method for implementing data loss prevention (DLP) includes: generating an asset lineage map from file system metadata; identifying, based on the asset lineage map, an input feature linked to the asset, a type of the asset, and a plurality of activities linked to the asset; obtaining a sensitivity score for the asset based on the input feature and the type of the asset; obtaining, based on the plurality of activities, a malicious score and a data loss score for the asset; determining a user level of a user; and initiating implementation of a first DLP policy for the user based on the user level, the malicious score, the data loss score, and the sensitivity score.

Abstract: A method for implementing data loss prevention (DLP) includes: generating an asset lineage map from file system metadata; identifying, based on the asset lineage map, an input feature linked to the asset, a type of the asset, and a plurality of activities linked to the asset; obtaining a sensitivity score for the asset based on the input feature and the type of the asset; obtaining, based on the plurality of activities, a malicious score and a data loss score for the asset; determining a user level of a user; and initiating implementation of a first DLP policy for the user based on the user level, the malicious score, the data loss score, and the sensitivity score.

Abstract: The present invention discloses a method of monitoring images, particularly images from cameras on offshore platforms, where only low-frequency events trigger alarms and high-frequency events are ignored. Preferably, it implements the Multi-scale Structural Quality Score where the compared image frames are spaced in time, for example, by a space of 1 minute, 10 minutes, 15 minutes, 30 minutes, or 60 minutes. If a quality score lower than a threshold quality score is obtained, or if the quality score obtained remains within a predetermined range for a time greater than a predetermined time limit, an alarm may be triggered. Accordingly, only events that represent a significant risk to operational and personnel safety and that persist for a certain period will trigger alarms. Consequently, spurious alarms that would be caused by low relevance events are avoided.

Abstract: A method for implementing data loss prevention (DLP) includes: generating an asset lineage map from file system metadata; identifying, based on the asset lineage map, an input feature linked to the asset, a type of the asset, and a plurality of activities linked to the asset; obtaining a sensitivity score for the asset based on the input feature and the type of the asset; obtaining, based on the plurality of activities, a malicious score and a data loss score for the asset; determining a user level of a user; and initiating implementation of a first DLP policy for the user based on the user level, the malicious score, the data loss score, and the sensitivity score.