Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, data from public sites, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device, and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device, and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device, and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device, and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: A method and apparatus is provided that includes techniques for providing complete solutions for role-based, rules-driven access enforcement, the techniques including situational awareness and video surveillance. An embodiment addresses blended risk assessment and security across logical systems, IT applications, databases, and physical systems from a single analytic dashboard, with auto-remediation capabilities. Further, an embodiment provides capability and functionality for co-relating seemingly innocent events and activities to detect real threats and risks, while providing powerful alerting and automated remedial action strategies for decisive action.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device, and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device, and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device, and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device, and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: A method and apparatus is provided that includes techniques for providing complete solutions for role-based, rules-driven access enforcement, the techniques including situational awareness and video surveillance. An embodiment addresses blended risk assessment and security across logical systems, IT applications, databases, and physical systems from a single analytic dashboard, with auto-remediation capabilities. Further, an embodiment provides capability and functionality for co-relating seemingly innocent events and activities to detect real threats and risks, while providing powerful alerting and automated remedial action strategies for decisive action.