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: 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 process of pretreatment for selective application of electroless metallization to a surface of a non-conductive material and a solution useful for the pretreatment are provided. The process achieves good coverage in areas to be plated on the surface of non-conductive materials without skip plating or over plating.

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 process of pretreatment for selective application of electroless metallization to a surface of a non-conductive material and a solution useful for the pretreatment are provided. The process achieves good coverage in areas to be plated on the surface of non-conductive materials without skip plating or over plating.

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 entities such as user identities and other objects. For example, an identity is assigned a risk score which is based on baseline factors such as HR attributes, such as training and screening status; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, as well as anomalies from normal behavior patterns. Techniques herein encompass the management of a risk profile (“behavior profile”) for each entity, e.g. identity, and maintains a risk score that is correlated with behavior, e.g. an individual's behavior, to track anomalies or irregularities in every day routines of the entity, e.g. individual.

Abstract: A process of pretreatment for selective application of electroless metallization to a surface of a non-conductive material and a solution useful for the pretreatment are provided. The process achieves good coverage in areas to be plated on the surface of non-conductive materials without skip plating or over plating.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across entities such as user identities and other objects. For example, an identity is assigned a risk score which is based on baseline factors such as HR attributes, such as training and screening status; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, as well as anomalies from normal behavior patterns. Techniques herein encompass the management of a risk profile (“behavior profile”) for each entity, e.g. identity, and maintains a risk score that is correlated with behavior, e.g. an individual's behavior, to track anomalies or irregularities in every day routines of the entity, e.g. individual.

Abstract: A process of pretreatment for selective application of electroless metallization to a surface of a non-conductive material and a solution useful for the pretreatment are provided. The process achieves good coverage in areas to be plated on the surface of non-conductive materials without skip plating or over plating.