Network Path Probing Using Available Network Connections

    公开(公告)号:US20170366978A1

    公开(公告)日:2017-12-21

    申请号:US15187837

    申请日:2016-06-21

    Abstract: Various embodiments provide methods, devices, and non-transitory processor-readable storage media enabling network path probing with a communications device by sending probes via a network connection to a STUN server and receiving probe replies. The communications device may increment a counter and transmit a test probe configured to be dropped at the first access point (NAT) causing all subsequent NATs to release their IP/port mappings. The communications device may send another probe to the STUN server and receive a probe reply. The communications device may compare the first and second probe replies to determine whether the final IP addresses within the network path match. By continuously incrementing the counter and querying access points, the communications device may determine the number of access points lay along any given network path. The presence of addition or unexpected numbers of NAT Servers may indicate the presence of a rogue access point.

    Communicating behavior information in a mobile computing device

    公开(公告)号:US09690635B2

    公开(公告)日:2017-06-27

    申请号:US13796595

    申请日:2013-03-12

    CPC classification number: G06F9/541 G06F21/44 G06F21/554 G06F21/564

    Abstract: Methods, systems and devices for communicating behavior analysis information using an application programming interface (API) may include receiving data/behavior models from one or more third-party network servers in a client module of a mobile device and communicating the information to a behavior observation and analysis system via a behavior API. The third-party servers may be maintained by one or more partner companies that have domain expertise in a particular area or technology that is relevant for identifying, analyzing, classifying, and/or reacting to mobile device behaviors, but that do not have access to (or knowledge of) the various mobile device sub-systems, interfaces, configurations, modules, processes, drivers, and/or hardware systems required to generate effective data/behavior models suitable for use by the mobile device. The behavior API and/or client modules allow the third-party server to quickly and efficiently access the most relevant and important information on the mobile device.

    Dynamic Honeypot System
    116.
    发明申请

    公开(公告)号:US20170134405A1

    公开(公告)日:2017-05-11

    申请号:US14935522

    申请日:2015-11-09

    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.) and/or data (e.g., files, etc.).

    Method And Devices For Non-Intrusive Malware Detection For The Internet Of Things (IOT)

    公开(公告)号:US20170126704A1

    公开(公告)日:2017-05-04

    申请号:US14924763

    申请日:2015-10-28

    Abstract: Method and devices of detecting a malware infection of a computing device in a communication network are disclosed. A computing device may monitor outputs of temperature sensors associated with elements of the computing device. The monitored outputs of the temperature sensors may be compared to a profile of temperatures associated with normal operation of the computing device. A deviation of the monitored temperatures from the profile of temperatures associated with normal operation may be reported. The profile of temperatures associated with the normal operation of the computing device may be learned based on temperature sensor data obtained during normal operations. Learning the profile of temperatures may include monitoring outputs of temperature sensors associated with elements of the computing device during normal operation of the computing device and storing the monitored outputs as one or more profiles of temperatures associated with normal operation of the computing device.

    Methods and Systems of Building Classifier Models in Computing Devices
    119.
    发明申请
    Methods and Systems of Building Classifier Models in Computing Devices 审中-公开
    在计算设备中构建分类器模型的方法和系统

    公开(公告)号:US20170046510A1

    公开(公告)日:2017-02-16

    申请号:US14826464

    申请日:2015-08-14

    CPC classification number: G06F21/552 G06F2221/033 G06N20/00

    Abstract: Methods, and computing devices implementing the methods, use application-based classifier models to improve the efficiency and performance of a comprehensive behavioral monitoring and analysis system predicting whether a software application is causing undesirable or performance depredating behavior. The application-based classifier models may include a reduced and more focused subset of the decision nodes that are included in a full or more complete classifier model that may be received or generated in the computing device. The application groups may be represented by application groups formed of computing device applications sharing related features, and may be generated using one or more clustering algorithms. Lean classifier models may be generated for each of the application group and may incorporate historical user input regarding execution permissions for features of applications within an application group.

    Abstract translation: 方法和实现方法的计算设备使用基于应用的分类器模型来提高综合行为监测和分析系统的效率和性能,以预测软件应用程序是否导致不良或性能下降的行为。 基于应用的分类器模型可以包括被包括在可以在计算设备中接收或生成的完整或更完整的分类器模型中的决策节点的简化和更集中的子集。 应用组可以由由共享相关特征的计算设备应用形成的应用组来表示,并且可以使用一个或多个聚类算法生成。 可以为每个应用组生成精益分类器模型,并且可以包括关于应用组内的应用的特征的执行许可的历史用户输入。

    Optimization of Hardware Monitoring for Computing Devices
    120.
    发明申请
    Optimization of Hardware Monitoring for Computing Devices 有权
    计算设备硬件监控优化

    公开(公告)号:US20160274991A1

    公开(公告)日:2016-09-22

    申请号:US14660260

    申请日:2015-03-17

    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 translation: 各个方面提供用于优化计算设备上的硬件监视的系统和方法。 计算设备可以接收监视请求以监视在计算设备上执行的过程中的代码或数据的一部分。 所述计算设备可以从所述监视请求生成所述计算设备中的第一硬件监视组件的第一监视配置参数,并且可以识别当所述第一硬件监视组件根据所述第一硬件监视组件监视所述代码或数据的所述部分时发生的非最佳事件模式 第一个监控配置参数。 计算设备可以对代码或数据的一部分应用变换,并且通过响应于代码或数据的部分的变换来修改第一监视配置参数来重新配置第一硬件监视组件。

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