Artificial intelligence method and system for detecting anomalies in a computer network

An enterprise network system comprising:

• a data source coupled to a network;
• a router coupled to the data source;
• a switch device coupled to the router;
• an instant auto discovery engine (IAE) module coupled to switch device, the discovery module configured to monitor traffic to the switch device to detect all of a plurality of client devices, including a plurality of IoT devices, coupled to the switch device, detect all of a plurality of sensor devices coupled to the switch device, and detect all of a plurality input device coupled to the switch device, the IAE module comprising a catalog of each of the plurality of client devices, input devices, sensing devices, or other network devices;
• a behavior analytics engine (BAE) module coupled to the switch device, the BAE module configured to monitor traffic to the switch device and configured to detect one or more anomalies from a flow of traffic;
• an intelligent machine learning engine (IMLE) module configured with the BAE module, the IMLE module configured to process the flow of data through one of a plurality of processes, one of the plurality of processes numbered from one through N, where N is greater than 5, the plurality of processes being categorized into a clustering process, a classification process, a regression process, an association process, a probabilistic processes comprising a Bayesian Network, or a graph based model, alone or in combination with any of the other aforementioned processes;
• a smart security engine (SSE) module, the SSE being configured to implement a security measure from feedback from the BAE module;
• an autonomous decision engine (ADE) module coupled to the SSE module, the ADE module configured for a remediation process, the remediation process comprising an autonomous decision engine comprising a sense process, plan process, and an act process (collectively the “AI processes”), and configured to make a decision from the flow of data to remediate and take appropriate action based upon the what signal is received from the client device, and processed through a behavior analytics engine thereby feeding information into the autonomous decision engine taking into account information selected form an a status of an internal state, a response associated with the internal state and a received input, and a model associated with the device from a catalog stored in a database for remediation to reason over achieving a future state using remediation to predict a future state and use the AI processes to ensure migration to the future state;
• and
• whereupon the IAE module, BAE module, ADE module, and SSE module are configured to discover instantly the plurality of client devices connected to the network, monitoring the flow of data from each of the plurality of the client devices, detecting at least one anomaly, and taking a remediation action for the detected anomaly.