Abstract: A system comprises an enterprise network system and engine. The engine has a discovery module coupled to a switch device, an AI and machine learning based monitoring and detection module coupled to the switch device, and a remediation module coupled to the switch device. The remediation module is configured to initiate a remediation process based upon the detection of at least one of the bot anomalies from the flow of data.

Abstract: A system comprises an enterprise network system and engine. The engine has a discovery module coupled to a switch device, an AI and machine learning based monitoring and detection module coupled to the switch device, and a remediation module coupled to the switch device. The remediation module is configured to initiate a remediation process based upon the detection of at least one of the anomalies from the flow of data.

Abstract: A system comprises an enterprise network system and engine. The engine has a discovery module coupled to a switch device, an AI and machine learning based monitoring and detection module coupled to the switch device, and a remediation module coupled to the switch device. The remediation module is configured to initiate a remediation process based upon the detection of at least one of the bot anomalies from the flow of data.

Abstract: A system comprises an enterprise network system and engine that could be inside an enterprise or hosted on a public and/or private cloud infrastructure. The engine has a discovery module coupled to a switch device, an AI and machine learning based monitoring and detection module coupled to the switch device and end point devices or assets including laptops, workstations and servers, and a remediation module coupled to the switch device. The system provides processes for building a network endpoint state transition model. The system can be unsupervised and is completely based on artificial intelligence processes. The network endpoint model is constructed by using a network identity and network behavior observed through data traffic flow to capture co-occurrence of data communications or connections in at least two consecutive observation windows or time frames. This network endpoint connection state transition model is used for detecting behavior anomalies.

Abstract: A system comprises an enterprise network system and engine. The engine has a discovery module coupled to a switch device, an AI and machine learning based monitoring and detection module coupled to the switch device, and a remediation module coupled to the switch device. The remediation module is configured to initiate a remediation process based upon the detection of at least one of the anomalies from the flow of data.

Abstract: A system comprises an enterprise network system and engine. The engine has a discovery module coupled to a switch device, an AI and machine learning based monitoring and detection module coupled to the switch device, and a remediation module coupled to the switch device. The remediation module is configured to initiate a remediation process based upon the detection of at least one of the anomalies from the flow of data.

Abstract: A system comprises an enterprise network system and engine. The engine has a discovery module coupled to a switch device, an AI and machine learning based monitoring and detection module coupled to the switch device, and a remediation module coupled to the switch device. The remediation module is configured to initiate a remediation process based upon the detection of at least one of the anomalies from the flow of data.