Abstract: Techniques and architectures for representing data with one or more n-dimensional representations and/or using one or more models to identify malware are described herein. For example, the techniques and architectures may determine one or more coordinates for one or more points based on one or more sets of bits in the data and generate an n-dimensional representation for the data based on the one or more points. The techniques and architectures may evaluate the n-dimensional representation with one or more machine-trained models to detect malware.

Abstract: Techniques and architectures for representing data with one or more n-dimensional representations and/or using one or more models to identify malware are described herein. For example, the techniques and architectures may determine one or more coordinates for one or more points based on one or more sets of bits in the data and generate an n-dimensional representation for the data based on the one or more points. The techniques and architectures may evaluate the n-dimensional representation with one or more machine-trained models to detect malware.

Abstract: Techniques and architectures include representing data with one or more n-dimensional representations and using one or more analysis models to identify target properties associated with the one or more n-dimensional representations. For example, data can be represented as a plurality of points in a coordinate system. A set of points in the plurality of points can be identified and an n-dimensional model can be generated for the set of points. The n-dimensional model can be compared to a plurality of n-dimensional models that are tagged as including a target property associated with malicious behavior, benign behavior, and/or a vulnerability. Based on the comparison, a likelihood can be determined that the data includes the target property.

Abstract: A manipulator has a manipulator arm with a manipulator flange at one free end. The flange holds an end effector having an application device for machining a workpiece. The manipulator flange is rotatable about hand axes. A first hand axis extends in the direction of the longitudinal axis of the manipulator arm, a second hand axis extends transversely to the first hand axis and a third hand axis extends transversely to the second hand axis. The hand axes intersect at a common intersection point. A machining force acting on the application device is diverted into the manipulator arm by way of the end effector. So that process forces during a mechanical operation do not lead to impairment of the machining pose of the manipulator arm, provision is made to fix the application device to the manipulator flange at an attachment angle to the first hand.

Abstract: Techniques and architectures for representing data with one or more n-dimensional representations and/or using one or more models to identify malware are described herein. For example, the techniques and architectures may determine one or more coordinates for one or more points based on one or more sets of bits in the data and generate an n-dimensional representation for the data based on the one or more points. The techniques and architectures may evaluate the n-dimensional representation with one or more machine-trained models to detect malware.

Abstract: Techniques and architectures for representing data with one or more n-dimensional representations and/or using one or more models to identify threats associated with the one or more n-dimensional representations are described herein. For example, the techniques and architectures may determine one or more coordinates for one or more points based on one or more sets of bits in the data and generate an n-dimensional representation for the data based on the one or more points. The techniques and architectures may evaluate the n-dimensional representation with one or more machine-trained models to detect a threat associated with the data, such as malware or another threat.

Abstract: Techniques and architectures for representing data with one or more n-dimensional representations and/or using one or more models to identify threats associated with the one or more n-dimensional representations are described herein. For example, the techniques and architectures may determine one or more coordinates for one or more points based on one or more sets of bits in the data and generate an n-dimensional representation for the data based on the one or more points. The techniques and architectures may evaluate the n-dimensional representation with one or more machine-trained models to detect a threat associated with the data, such as malware or another threat.

Abstract: The invention relates to a manipulator having a manipulator arm (5) at the one free end (6) of which a manipulator flange (8) is provided on which an end effector (46) having an application device (9) for machining a workpiece (37) is held. The manipulator flange (8) is rotatable about hand axes (20, 21, 22). A first hand axis (20) extends in the direction of the longitudinal axis (18) of the manipulator arm (5), a second hand axis (21) extends transversely to the first hand axis (20) and a third hand axis (22) extends transversely to the second hand axis (21), wherein the hand axes (20, 21, 22) intersect one another in a common intersection point (26). A machining force (33) acting on the application device (9) is diverted into the manipulator arm (5) by way of the end effector (46).