Abstract:
Systems and methods of network based positioning include a server configured to assign priority levels to mobile devices locatable within the network, and allocate network resources for network based positioning of the locatable mobile devices, based on the corresponding priority levels assigned to the mobile devices. The server may further be configured to admit only a selected subset of the locatable mobile devices into the network for purposes of network based positioning and deny admission to the remaining locatable mobile devices, wherein the selected subset can be determined based on an attribute of the mobile device and/or a characteristic of the user of the mobile device.
Abstract:
A computing device processor may be configured with processor-executable instructions to implement methods of detecting and responding to fake user interaction (UI) events. The processor may determine whether a user interaction event is a fake user interaction event by analyzing raw data generated by one or more hardware drivers in conjunction with user interaction event information generated or received by the high-level operating system. In addition, the processor may be configured with processor-executable instructions to implement methods of using behavioral analysis and machine learning techniques to identify, prevent, correct, or otherwise respond to malicious or performance-degrading behaviors of the computing device based on whether a detected user interaction event is an authentic or fake user interaction event.
Abstract:
Methods and devices for tracking data flows in a computing device include monitoring memory in a hardware component of the computing device to identify a read operation that reads information from a tainted memory address, using heuristics to identify a first, second, and third number of operations performed after the identified read operation, marking memory addresses of write operations performed after first number of operations and before the second number of operations as tainted, and marking memory addresses of write operations performed after the third number of operations and before the second number of operations as untainted.
Abstract:
Methods, devices and systems for detecting suspicious or performance-degrading mobile device behaviors intelligently, dynamically, and/or adaptively determine computing device behaviors that are to be observed, the number of behaviors that are to be observed, and the level of detail or granularity at which the mobile device behaviors are to be observed. The various aspects efficiently identify suspicious or performance-degrading mobile device behaviors without requiring an excessive amount of processing, memory, or energy resources.
Abstract:
A computing device processor may be configured with processor-executable instructions to implement methods of using behavioral analysis and machine learning techniques to identify, prevent, correct, or otherwise respond to malicious or performance-degrading behaviors of the computing device. As part of these operations, the processor may generate user-persona information that characterizes the user based on that user's activities, preferences, age, occupation, habits, moods, emotional states, personality, device usage patterns, etc. The processor may use the user-persona information to dynamically determine the number of device features that are monitored or evaluated in the computing device, to identify the device features that are most relevant to determining whether the device behavior is not consistent with a pattern of ordinary usage of the computing device by the user, and to better identify or respond to non-benign behaviors of the computing device.
Abstract:
Described are devices, methods, techniques and systems for locating a portable services access transceiver (PSAT) for use in aiding emergency “911” services. In one implementation, one or more conditions indicative of movement of a PSAT may initiate a process for obtaining a new estimated location of the PSAT. In another implementation, a location of a PSAT may be determined or updated using indoor navigation techniques.
Abstract:
The various aspects provide a method for recognizing and preventing malicious behavior on a mobile computing device before it occurs by monitoring and modifying instructions pending in the mobile computing device's hardware pipeline (i.e., queued instructions). In the various aspects, a mobile computing device may preemptively determine whether executing a set of queued instructions will result in a malicious configuration given the mobile computing device's current configuration. When the mobile computing device determines that executing the queued instructions will result in a malicious configuration, the mobile computing device may stop execution of the queued instructions or take other actions to preempt the malicious behavior before the queued instructions are executed.
Abstract:
Various aspects provide methods implemented by at least one processor executing on a mobile communication device to efficiently identify, classify, model, prevent, and/or correct the non-benign (e.g., performance degrading) conditions and/or behaviors that are related to an application operating on the device. Specifically, in various aspects, the mobile computing device may derive or extract application-specific features by performing a binary analysis of an application and may determine the application's category (e.g., a “games,” “entertainment,” or “news” category) based on the application-specific features. The mobile computing device may also obtain a classifier model associated with the application's category that includes various conditions, features, behaviors and corrective actions that may be used to quickly identify and correct non-benign behaviors (e.g., undesirable, malicious, and/or performance-degrading behaviors) occurring on the mobile computing device that are related to the application.
Abstract:
A position fix for a mobile platform is determined using RSSI values for wireless signals received from access points (APs), at least one of which has dynamic transmission power control. The transmission power data for the APs is received from an entity separate from the APs, e.g., a central entity or a positioning assistance server. The RSSI values for wireless signals received from the APs are acquired, as is an RSSI heatmap. Using the transmission power data, the RSSI values and the RSSI heatmap, the position fix for the mobile platform is determined. The position fix may be determined by the mobile platform or a positioning assistance server. Additionally, a server may receive transmission power data for APs and may provide to a mobile platform RSSI heatmap information based on the transmission power data. The RSSI heatmap information may be, e.g., the transmission power data or a RSSI heatmap.
Abstract:
In one implementation, a method may comprise: storing a user profile indicative of at least one attribute of a user of a mobile station; determining a measurement value based, at least in part, on a signal from at least one sensor on the mobile station; and estimating a location of the mobile station based, at least in part, on an association of the at least one attribute and the measurement value with a context parameter map database.