Abstract: In some embodiments, a method determines a first functional domain that includes a group of security policies that have been copied from a second functional domain. Network flow data is queried to determine network traffic that is associated with a security policy in the group of security policies in the first functional domain. The method analyzes utilization of the security policy based on the network traffic. Based on the analyzing, a recommendation is generated to change the security policy in the first functional domain.

Abstract: A computer-implemented method for monitoring and remediating security drift in a public cloud network is disclosed. The security drift event includes an unintended change to existing security controls effected through an unauthorized deployment channel, performed by an unauthorized user. The method includes providing a cloud server application including a number of cloud client accounts, and deploying the cloud client accounts in client account clusters. The client account clusters include a master account that includes a drift detection component and a number of service accounts including serverless application components. The method further includes instantiating cloud infrastructure resources in the service accounts, and detecting a security drift event in the client account cluster, by the drift detection components.

Abstract: A computer implemented method and system for determining reliability of a machine includes receiving one of a machine data from one or more locations through an internet of things (IOT) based machine wearable sensor network. The method further includes storing the data in a distributed computer database communicatively coupled to an enterprise resource planning (ERP) system and extracting, through a computer server, one or more entity information from the data to compare against a pre-defined baseline. Further, mapping, though a big data machine learning engine, the extracted one or more entity information into a multi-classification model. The method includes indicating, through a machine learning engine coupled to a predictive analytics engine, on a user interface a set of analytical predictions for machine maintenance, repair and operation.

Abstract: A computer implemented method and system for determining reliability of a machine includes receiving one of a machine data from one or more locations through an internet of things (IOT) based machine wearable sensor network. The method further includes storing the data in a distributed computer database communicatively coupled to an enterprise resource planning (ERP) system and extracting, through a computer server, one or more entity information from the data to compare against a pre-defined baseline. Further, mapping, though a big data machine learning engine, the extracted one or more entity information into a multi-classification model. The method includes indicating, through a machine learning engine coupled to a predictive analytics engine, on a user interface a set of analytical predictions for machine maintenance, repair and operation.