Abstract:
Methods, and devices implementing the methods, use device-specific classifiers in a privacy-preserving behavioral monitoring and analysis system for crowd-sourcing of device behaviors. Diverse devices having varying degrees of “smart” capabilities may monitor operational behaviors. Gathered operational behavior information may be transmitted to a nearby device having greater processing capabilities than a respective collecting device, or may be transmitted directly to an “always on” device. The behavior information may be used to generate behavior vectors, which may be analyzed for anomalies. Vectors containing anomaly flags may be anonymized to remove any user-identifying information and subsequently transmitted to a remote recipient such as a service provider or device manufacture. In this manner, operational behavior information may be gathered about different devices from a large number of users, to obtain statistical analysis of operational behavior for specific makes and models of devices, without divulging personal information about device users.
Abstract:
Systems, methods, and devices of the various aspects enable detecting a malfunction caused by radio frequency (RF) interference. A computing device processor may identify a location of the computing device based on a plurality of real-time data inputs received by the computing device. The processor may characterize an RF environment of the computing device based on the identified location and the plurality of real-time data inputs. The processor may determine at least one RF emissions threshold based on the characterization of the RF environment. The processor may compare the characterization of the RF environment to the at least one RF emissions threshold, and may perform an action in response to determining that the characterization of the RF environment exceeds the at least one RF emissions threshold.
Abstract:
Methods, systems and devices for identifying, classifying, modeling, and responding to mobile device behaviors may include using lightweight processes to monitor and analyze various conditions and device behaviors to detect an instance of a non-benign behavior, increasing a level of security or scrutiny to identify other instances of non-benign behavior, and notifying select computing devices of the increased security risk so that they may also increase their security/scrutiny levels. For example, a computing device may be configured to perform a first type of analysis operations (e.g., lightweight analysis operations) to determine whether there is an increased security risk, and perform a second type of analysis operations (e.g., robust analysis operations) in response to determining that there is an increased security risk to determine whether there are additional security risks that are different from the security risk detected via the performance of the first type of analysis operations.
Abstract:
Systems, apparatus and methods for estimating a location of a mobile device are presented. Before computing a location estimate, the mobile device groups a plurality of access points into two or more categories (for example, a first list of access points having a first characteristic and a second list of access points having a second characteristic). Round-trip time (RTT) measurements are computed for access points in the first list. A Short Interframe Space (SIFS) value may be determined for each access point in the first list or generally SIFT representing the first list as a whole. The RTT measurements are compensated with the appropriate SIFS value. The mobile device then computes its location or position fix estimate using the compensated RTT values while excluding less accurate RTT values from other access points. As a result, the location estimate eliminates adverse influent from some access points.
Abstract:
The various aspects provide for a computing device and methods implemented by the device to ensure that an application executing on the device and seeking root access will not cause malicious behavior while after receiving root access. Before giving the application root access, the computing device may identify operations the application intends to execute while having root access, determine whether executing the operations will cause malicious behavior by simulating execution of the operations, and pre-approve those operations after determining that executing those operations will not result in malicious behavior. Further, after giving the application root access, the computing device may only allow the application to perform pre-approved operations by quickly checking the application's pending operations against the pre-approved operations before allowing the application to perform those operations. Thus, the various aspects may ensure that an application receives root access without compromising the performance or security integrity of the computing device.
Abstract:
Example methods, apparatuses, or articles of manufacture are disclosed herein that may be utilized, in whole or in part, to facilitate or support one or more operations or techniques for detecting location changes and monitoring assistance data via scanning for use in or with a mobile device. Briefly, in accordance with at least one implementation, a method may include obtaining, at a mobile device, a rough estimate of a location of the mobile device; identifying a plurality of transmitters within a signal acquisition range of the roughly estimated location; transmitting probe requests addressed to at least some of the transmitters; and selectively initiating a passive scan at a receiver of the mobile device if a number of responses to the probe requests received from the transmitters is less than a threshold number.
Abstract:
Systems, apparatus and methods for estimating a location of a mobile device are presented. Before computing a location estimate, the mobile device groups a plurality of access points into two or more categories (for example, a first list of access points having a first characteristic and a second list of access points having a second characteristic). Round-trip time (RTT) measurements are computed for access points in the first list. A Short Interframe Space (SIFS) value may be determined for each access point in the first list or generally SIFT representing the first list as a whole. The RTT measurements are compensated with the appropriate SIFS value. The mobile device then computes its location or position fix estimate using the compensated RTT values while excluding less accurate RTT values from other access points. As a result, the location estimate eliminates adverse influent from some access points.
Abstract:
Example methods, apparatuses, or articles of manufacture are disclosed herein that may be utilized, in whole or in part, to facilitate or support one or more operations or techniques for detecting location changes and monitoring assistance data via scanning for use in or with a mobile device. Briefly, in accordance with at least one implementation, a method may include obtaining, at a mobile device, a rough estimate of a location of the mobile device; identifying a plurality of transmitters within a signal acquisition range of the roughly estimated location; transmitting probe requests addressed to at least some of the transmitters; and selectively initiating a passive scan at a receiver of the mobile device if a number of responses to the probe requests received from the transmitters is less than a threshold number.
Abstract:
Various methods, apparatuses and/or articles of manufacture are provided which may be implemented to support mobile device positioning through the use of adaptive passive scanning and/or adaptive active probing techniques. For example, a mobile device may acquire signals from wireless transceivers, identify wireless transceivers based, at least in part, on the acquired signal(s), determine a received signal strength measurement for each of the wireless transceivers based, at least in part, on the acquired signal(s), and determine a transmission power of a probe signal to be transmitted to at least one of the wireless transceivers based, at least in part, on at least one of the received signal strength measurements.
Abstract:
Techniques are provided for adaptively sampling orientation sensors in positioning systems based on location (e.g., map) data. Embodiments can enable a device to use location, direction, and/or location information to anticipate an expected change in motion. The embodiments can then identify and prioritize a number of sampling strategies to alter sampling rates of orientation sensors, and implement at least one strategy, based on priority.