Abstract: Various aspects provide systems and methods for optimizing hardware monitoring on a computing device. A computing device may receive a monitoring request to monitor a portion of code or data within a process executing on the computing device. The computing device may generate from the monitoring request a first monitoring configuration parameter for a first hardware monitoring component in the computing device and may identify a non-optimal event pattern that occurs while the first hardware monitoring component monitors the portion of code or data according to the first monitoring configuration parameter. The computing device may apply a transformation to the portion of code or data and reconfigure the first hardware monitoring component by modifying the first monitoring configuration parameter in response to the transformation of the portion of code or data.

Abstract: Various embodiments include methods implemented on a computing device for analyzing a program executing within a virtual environment on the computing device. The methods may include determining whether the program is attempting to detect whether it is being executed within the virtual environment, and analyzing the program within a protected mode of the computing device in response to determining that the program is attempting to detect whether it is being executed within the virtual environment.

Abstract: Various embodiments include a honeypot system configured to trigger malicious activities by malicious applications using a behavioral analysis algorithm and dynamic resource provisioning. A method performed by a processor of a computing device, which may be a mobile computing device, may include determining whether or not a target application currently executing on the computing device is potentially malicious based, at least in part, on the analysis, predicting a triggering condition of the target application in response to determining the target application is potentially malicious, provisioning one or more resources based, at least in part, on the predicted triggering condition, monitoring activities of the target application corresponding to the provisioned one or more resources, and determining whether or not the target application is a malicious application based, at least in part, on the monitored activities. The resources may be device components (e.g., network interface(s), sensor(s), etc.

Abstract: Embodiments include computing devices, apparatus, and methods implemented by the apparatus for accelerating machine learning on a computing device. Raw data may be received in the computing device from a raw data source device. The apparatus may identify key features as two dimensional matrices of the raw data such that the key features are mutually exclusive from each other. The key features may be translated into key feature vectors. The computing device may generate a feature vector from at least one of the key feature vectors. The computing device may receive a first partial output resulting from an execution of a basic linear algebra subprogram (BLAS) operation using the feature vector and a weight factor. The first partial output may be combined with a plurality of partial outputs to produce an output matrix. Receiving the raw data on the computing device may include receiving streaming raw data.

Abstract: Various embodiments include methods for detecting software attacks on a process executing on a computing device. Various embodiment methods may include monitoring structural attributes of a plurality of virtual memory regions utilized by the process, and comparing the monitored structural attributes to the expected structural attributes of the plurality of VMRs. Various embodiment methods may further include determining whether the monitored structural attributes represent anomalous behavior of the process based on the comparison between the monitored structural attributes and the expected structural attributes.

Abstract: Various aspects provide systems and methods for optimizing hardware monitoring on a computing device. A computing device may receive a monitoring request to monitor a portion of code or data within a process executing on the computing device. The computing device may generate from the monitoring request a first monitoring configuration parameter for a first hardware monitoring component in the computing device and may identify a non-optimal event pattern that occurs while the first hardware monitoring component monitors the portion of code or data according to the first monitoring configuration parameter. The computing device may apply a transformation to the portion of code or data and reconfigure the first hardware monitoring component by modifying the first monitoring configuration parameter in response to the transformation of the portion of code or data.

Abstract: Methods, devices, systems, and non-transitory process-readable storage media for a computing device to use machine learning to dynamically configure an application and/or complex algorithms associated with the application. An aspect method performed by a processor of the computing device may include operations for performing an application that calls a library function associated with a complex algorithm, obtaining signals indicating user responses to performance of the application, determining whether a user tolerates the performance of the application based on the obtained signals indicating the user responses, adjusting a configuration of the application to improve a subsequent performance of the application in response to determining the user does not tolerate the performance of the application, and storing data indicating the user responses to the performance of the application and other external variables for use in subsequent evaluations of user inputs.

Abstract: Aspect methods, systems and devices may be configured to create/capture checkpoints without significantly impacting the performance, power consumption, or responsiveness of the mobile device. An observer module of the mobile device may instrument or coordinate various application programming interfaces (APIs) at various levels of the mobile device system and constantly monitor the mobile device (via a low power process, background processes, etc.) to identify the normal operation patterns of the mobile device and/or to identify behaviors that are not consistent with previously computed normal operation patterns. The mobile device may store mobile device state information in a memory as a stored checkpoint when it determines that the mobile device behaviors are consistent with normal operation patterns, and upload a previously stored checkpoint to a backup storage system when it determines that the mobile device behaviors are not consistent with normal operation patterns.

Abstract: The subject matter disclosed herein relates to a system and method for receiving incentives on a mobile device. A first message may be received based on a first location of the mobile device, such that the first message indicates to a user of the mobile device that an incentive will be provided if the user remains within a certain proximity a waypoint for a predetermined length of time, and a second message including may be received if a second location of the mobile device is within the certain proximity of the waypoint, such that an elapsed time between a determination of the first location and a determination of the second location is equal to or greater than the predetermined length of time.

Abstract: Methods, devices, and non-transitory storage media for dynamic patching of diversity-based software executing on a computing device. One of many variations of various module utilized by software may be selected from a list of available module variations to be used when software is executed. An embodiment method for updating software may include obtaining or receiving a notification indicating a particular module variation that should not be used as a module for the software, and removing the module variation from the list of available module variations for the module in response to the notification. In some embodiments, the notification may be received by the mobile device from a remote server, and further the notification does not include data capable of being used as a module by the software during runtime. In some embodiments, the module variation may be one of flawed, outdated, and identified as exploited by malware.

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 position estimation via one or more proximate fingerprints for use in or with a mobile communication device.

Abstract: Aspect methods, systems and devices may be configured to create/capture checkpoints without significantly impacting the performance, power consumption, or responsiveness of the mobile device. An observer module of the mobile device may instrument or coordinate various application programming interfaces (APIs) at various levels of the mobile device system and constantly monitor the mobile device (via a low power process, background processes, etc.) to identify the normal operation patterns of the mobile device and/or to identify behaviors that are not consistent with previously computed normal operation patterns. The mobile device may store mobile device state information in a memory as a stored checkpoint when it determines that the mobile device behaviors are consistent with normal operation patterns, and upload a previously stored checkpoint to a backup storage system when it determines that the mobile device behaviors are not consistent with normal operation patterns.

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 position estimation via one or more proximate fingerprints for use in or with a mobile communication device.

Abstract: Schema-driven XML parsing techniques allow an XML parser to optimize its parsing process by composing parse and to dynamically generate parsing code components based on XML schema definition for the targeted XML document. These techniques reduce the XML parsing time and reduce the memory requirement during parsing process. Further, a reconfigurable parser is provided which is guided during parsing of the XML document by XML element lexicographical information and state transition information extracted from a schema associated with the XML document. Pre-allocated element object pools may be provided based on the schema analysis to reduce the requirements for dynamic memory allocation and de-allocation operations.

Abstract: A mechanism and supporting apparatus to enable resource sharing among groups of users over mobile terminals. The system presented leverages the carrier infrastructure to simplify the requirements at the terminals, and describes a graphical user interface binding mechanism that allows developing generic graphical users interfaces that can be customized to heterogeneous devices at run-time.

Abstract: The subject matter disclosed herein relates to a system and method for influencing behavior of a user of a mobile device. A determination may be made regarding whether a mobile device is within an area associated with one or more predefined waypoints. An incentive may be provided to the mobile device based at least in part on a location of the mobile device to influence behavior of a user of the mobile device.

Abstract: A method and apparatus is disclosed herein for generating and solving constraints. In one embodiment, the method comprises modifying program code by inserting one or more dynamic annotations having unsolved variables, generating one or more constraints based on the one or more dynamic annotations using a verifier, solving the one or more generated constraints; and modifying the program code by inserting a dynamic annotation in place of an annotation containing an unsolved variable.

Abstract: A method and apparatus for performing checks on program code. In one embodiment, the method comprises receiving program code and statically verifying information about one or more dynamic checks in the program code, where each of the one or more dynamic checks in the program code checks an operation in the program code.

Abstract: A method and apparatus for composing software are described. In one embodiment, the method includes obtaining software structure data that identifies multiple application components associated with requested functionality, obtaining software logic data indicating interaction rules between the application components, storing the software structure data and the software logic data in memory, and coordinating the invocation of the application components at run time based on the software logic data.

Abstract: In one aspect of the invention, a method for load balancing an application among a plurality of computing devices coupled with at least one access network for communication between the devices is provided. The method comprises storing the application on a server device coupled with the access network. The method also comprises measuring a set of application attributes associated with the application, including at least one performance attribute for characterizing a user perceived performance of the application. The method further comprises issuing a request, from a client device coupled with the access network, for the application. Additionally, the method comprises provisioning execution of the application on the client or server device in response to the request based on the set of application attributes. The method further comprises executing the application on the client or server device in response to provisioning the execution of the application.