Abstract:
Various implementations include unmanned autonomous vehicles (UAVs) and methods for providing security for a UAV. In various implementations, a processor of the UAV may receive sensor data from a plurality of UAV sensors about an object in contact with the UAV. The processor may determine an authorization threshold based on the received sensor data. The processor may determine whether the object is authorized based on the received sensor data and the determined authorization threshold.
Abstract:
Embodiments include computing devices and methods implemented by computing devices for using programmable hardware security counters for detecting malicious behavior. Various embodiments may include tracking the value of hardware instruction pointers, such as pointers tracking the memory address of each executing instruction. The computing device may identify a start and end of contiguous instruction segments using the tracked instruction pointer. For example, the computing device may analyze changes in value of the instruction pointer to detect “jumps” or large changes in the memory address of executing instructions. Based, at least in part, on the identified instruction segments, the computing device may determine whether the instruction segments represent malicious behavior. If the instruction segments represent malicious behavior, the computing device may terminate the requesting software application.
Abstract:
Implementations include systems and methods for managing security for a mobile communication device. In implementations, a processor of the mobile communication device may determine environment context information. The processor may receive safety information from one or more peer devices. The processor may determine an authentication requirement for the mobile communication device based on the received safety information and the determined environment context information. The processor may deny access to a function of the mobile communication device in response to determining that the determined authentication requirement is not satisfied.
Abstract:
A method performed by an electronic device is described. The method includes receiving a set of image frames. The set of image frames includes a face. The method also includes determining at least one facial motion of the face based on the set of image frames. The method further includes determining, based on the at least one facial motion, a facial rigidity confidence value indicating a degree of confidence that the face is rigid. The method additionally includes determining at least one facial micro-motion of the face based on the set of image frames. The method also includes determining a micro-motion matching confidence value indicating a degree of matching between the at least one facial micro-motion and a micro-motion profile. The method further includes authenticating a user based on the facial rigidity confidence value and the micro-motion matching confidence value.
Abstract:
Implementations include systems and methods for managing security for a mobile communication device. In implementations, a processor of the mobile communication device may determine environment context information. The processor may receive safety information from one or more peer devices. The processor may determine an authentication requirement for the mobile communication device based on the received safety information and the determined environment context information. The processor may deny access to a function of the mobile communication device in response to determining that the determined authentication requirement is not satisfied.
Abstract:
Embodiments provide methods of managing network traffic flows. A processor of a network device may receive a first network traffic flow of a monitoring computing device and information identifying a source application of the first network traffic flow. The processor may determine a characteristic of the first network traffic flow associated with the application based at least in part on information in the first network traffic flow and the identified source application. The processor may receive a second network traffic flow from a non-monitoring computing device, and may associate the source application and the second network traffic flow if one or more characteristics of the second network traffic flow match or correlating to one or more characteristics of network traffic resulting from the source application.
Abstract:
Methods, systems, computer-readable media, and apparatuses for estimating a user's heart rate using a PG signal are presented. In some implementations, the heart rate is estimated by computing a frequency-domain PG, identifying one or more features in the frequency-domain PG, selecting qualified features from the one or more features, and constructing one or more traces. In some implementations, an accelerometer signal can be used for motion cancellation to eliminate traces that are motion artifacts.
Abstract:
Various implementations include unmanned autonomous vehicles (UAVs) and methods for providing security for a UAV. In various implementations, a processor of the UAV may receive sensor data from a plurality of UAV sensors about an object in contact with the UAV. The processor may determine an authorization threshold based on the received sensor data. The processor may determine whether the object is authorized based on the received sensor data and the determined authorization threshold.
Abstract:
Disclosed embodiments pertain to the measurement of heart rate in the presence of motion and noise. Spectral peaks in measurements by an optical sensor are compared with spectral peaks obtained from a motion sensor signal measurements, to obtain a fundamental frequency in the optical sensor signal, where the fundamental frequency is associated with a user's heart rate. A first heart rate may be estimated based on the fundamental frequency. A variety of quality metrics may be determined for the first heart rate estimate. A second estimated heart rate may be determined based by processing a frequency domain representation of the optical sensor signal based on a frequency domain representation of the motion sensor signal. One or more of the previously determined quality metrics may be dynamically adjusted based on a comparison of first and second estimated heart rates.
Abstract:
Techniques for determining one or more physiological properties of a user of a device is disclosed. The techniques include, in part, obtaining one or more vascular-related signals and a first set of data corresponding to one or more inertial sensors. The one or more vascular-related signals and the first set of data correspond to a common time interval. The techniques further include determining one or more motion state categories in accordance with the first set of data, selecting portions of the one or more vascular-related signals based on their corresponding motion state category, and processing the selected portions of the one or more vascular-related signals to determine the physiological properties of the user.