INTEGRATING SENSATION FUNCTIONALITIES INTO A MOBILE DEVICE USING A HAPTIC SLEEVE

    公开(公告)号:US20170357343A1

    公开(公告)日:2017-12-14

    申请号:US15688831

    申请日:2017-08-28

    CPC classification number: G06F3/041 G06F3/016 G06F3/0414 G06F2203/04809

    Abstract: Methods, apparatuses, systems, and computer-readable media for integrating sensation functionalities into a mobile device using a haptic sleeve are presented. According to one or more aspects of the disclosure, a computing device may receive, via a haptic sleeve, sensation input captured by one or more haptic components of the haptic sleeve. Subsequently, the computing device may store haptic data corresponding to the received sensation input. For example, in storing such haptic data, the computing device may store information describing one or more electrical signals received via the one or more haptic components of the haptic sleeve during a period of time corresponding to a particular event, and this stored information may reflect various characteristics of the sensation input received by the computing device in connection with the particular event, such as the magnitude(s), position(s), duration, and/or type(s) of sensation(s) captured during the period of time.

    Method and System for Inferring Application States by Performing Behavioral Analysis Operations in a Mobile Device
    14.
    发明申请
    Method and System for Inferring Application States by Performing Behavioral Analysis Operations in a Mobile Device 有权
    通过在移动设备中执行行为分析操作来推断应用程序状态的方法和系统

    公开(公告)号:US20150286820A1

    公开(公告)日:2015-10-08

    申请号:US14247400

    申请日:2014-04-08

    CPC classification number: G06F21/566 G06F1/3206 G06F9/4893

    Abstract: Methods, systems and devices compute and use the actual execution states of software applications to implement power saving schemes and to perform behavioral monitoring and analysis operations. A mobile device may be configured to monitor an activity of a software application, generate a shadow feature value that identifies actual execution state of the software application during that activity, generate a behavior vector that associates the monitored activity with the shadow feature value, and determine whether the activity is malicious or benign based on the generated behavior vector, shadow feature value and/or operating system execution states. The mobile device processor may also be configured to intelligently determine whether the execution state of a software application is relevant to determining whether any of the monitored mobile device behaviors are malicious or suspicious, and monitor only the execution states of the software applications for which such determinations are relevant.

    Abstract translation: 方法,系统和设备计算和使用软件应用程序的实际执行状态来实现节电方案并执行行为监测和分析操作。 移动设备可以被配置为监视软件应用的活动,生成在该活动期间识别软件应用的实际执行状态的阴影特征值,生成将所监视的活动与阴影特征值相关联的行为向量,并且确定 基于生成的行为矢量,阴影特征值和/或操作系统执行状态,活动是否是恶意的或良性的。 移动设备处理器还可以被配置为智能地确定软件应用的执行状态是否与确定所监视的移动设备行为中的任何一个是恶意的还是可疑的,并且仅监视这些确定的软件应用的执行状态 是相关的

    Methods and Systems of Using Application-Specific and Application-Type-Specific Models for the Efficient Classification of Mobile Device Behaviors
    15.
    发明申请
    Methods and Systems of Using Application-Specific and Application-Type-Specific Models for the Efficient Classification of Mobile Device Behaviors 有权
    使用特定应用程序和应用程序类型的模型进行移动设备行为的有效分类的方法和系统

    公开(公告)号:US20150161386A1

    公开(公告)日:2015-06-11

    申请号:US14259501

    申请日:2014-04-23

    Abstract: Methods, and mobile devices implementing the methods, use application-specific and/or application-type specific classifier 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-specific and application-type specific 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 mobile device. The locally generated application-specific and/or application-type specific classifier models may be used to perform real-time behavior monitoring and analysis operations by applying the application-based classifier models to a behavior/feature vector generated by monitoring mobile device behavior. The various aspects focus monitoring and analysis operations on a small number of features that are most important for determining whether operations of a software application are contributing to undesirable or performance depredating behavior.

    Abstract translation: 实现这些方法的方法和移动设备使用特定应用程序和/或应用程序类型的分类器来提高综合行为监视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。 特定于应用程序和应用程序类型的分类器模型可以包括被包括在可以在移动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。 本地生成的特定应用程序和/或应用程序类型的分类器模型可用于通过将基于应用程序的分类器模型应用于通过监视移动设备行为生成的行为/特征向量来执行实时行为监视和分析操作。 各个方面将监视和分析操作集中在对确定软件应用程序的操作是否导致不良或性能下降行为最为重要的少量功能上。

    MULTI-LEVEL LOCATION DISAMBIGUATION
    17.
    发明申请
    MULTI-LEVEL LOCATION DISAMBIGUATION 审中-公开
    多层次的位置分配

    公开(公告)号:US20140032161A1

    公开(公告)日:2014-01-30

    申请号:US13658717

    申请日:2012-10-23

    CPC classification number: G01C21/00 G01C5/06 G01S5/0009

    Abstract: A method of disambiguating a location of a mobile station within a structure includes: obtaining, at the mobile station, regional pressure indications and corresponding region indications indicating regions within a structure that are vertically displaced with respect to each other, each of the regional pressure indications indicating atmospheric pressure information associated with the corresponding region; determining mobile station pressure information associated with a present location of the mobile station; comparing the mobile station pressure information with the regional pressure indications; and based on the comparing, determining in which of the regions the mobile station presently resides.

    Abstract translation: 消除移动台在结构内的位置的方法包括:在移动站处获取区域压力指示和指示结构内相对于彼此垂直移位的区域的对应区域指示,区域压力指示 指示与相应区域相关联的大气压力信息; 确定与所述移动台的当前位置相关联的移动站压力信息; 将移动台压力信息与区域压力指示进行比较; 并且基于比较,确定移动站当前驻留的区域中的哪一个。

    METHODS AND SYSTEMS FOR IDENTIFYING MALWARE THROUGH DIFFERENCES IN CLOUD VS. CLIENT BEHAVIOR
    18.
    发明申请
    METHODS AND SYSTEMS FOR IDENTIFYING MALWARE THROUGH DIFFERENCES IN CLOUD VS. CLIENT BEHAVIOR 有权
    通过云中差异识别恶意软件的方法和系统 客户行为

    公开(公告)号:US20160285897A1

    公开(公告)日:2016-09-29

    申请号:US14667461

    申请日:2015-03-24

    Abstract: A computing device may be configured to work in conjunction with another component (e.g., a server) to better determine whether a software application is benign or non-benign. This may be accomplished via the server performing static and/or dynamic analysis operations, generating a behavior information structure that describes or characterizes the range of correct or expected behaviors of the software application, and sending the behavior information structure to a computing device. The computing device may compare the received behavior information structure to a locally generated behavior information structure to determining whether the observed behavior of the software application differs or deviates from the expected behavior of the software application or whether the observed behavior is within the range of expected behaviors. The computing device may increase its level of security/scrutiny when the behavior information structure does not match the local behavior information structure.

    Abstract translation: 计算设备可以被配置为与另一组件(例如,服务器)结合工作,以更好地确定软件应用是良性还是非良性。 这可以通过执行静态和/或动态分析操作的服务器来实现,生成描述或表征软件应用的正确或预期行为的范围的行为信息结构,以及将行为信息结构发送到计算设备。 计算设备可以将接收到的行为信息结构与本地生成的行为信息结构进行比较,以确定所观察到的软件应用的行为是否不同或偏离了软件应用的预期行为,或观察到的行为是否在预期行为的范围内 。 当行为信息结构与本地行为信息结构不匹配时,计算设备可能会提高其安全性/审查级别。

    Hardware Assisted Asset Tracking for Information Leak Prevention
    19.
    发明申请
    Hardware Assisted Asset Tracking for Information Leak Prevention 有权
    硬件辅助资产跟踪信息泄漏预防

    公开(公告)号:US20150230108A1

    公开(公告)日:2015-08-13

    申请号:US14174956

    申请日:2014-02-07

    CPC classification number: H04W24/08 G06F21/552 H04W4/60

    Abstract: Mobile computing devices may be equipped with hardware components configured to monitor key assets of the mobile device at a low level (e.g., firmware level, hardware level, etc.). The hardware component may also be configured to dynamically determine the key assets that are to be monitored in the mobile device, monitor the access or use of these key assets by monitoring data flows, transactions, or operations in a system data bus of the mobile device, and report suspicious activities to a comprehensive behavioral monitoring and analysis system of the mobile device. The comprehensive behavioral monitoring and analysis system may then use this information to quickly identify and respond to malicious or performance degrading activities of the mobile device.

    Abstract translation: 移动计算设备可以配备有被配置为以低水平(例如,固件级别,硬件级别等)监视移动设备的关键资产的硬件组件。 硬件组件还可以被配置为动态地确定在移动设备中要被监视的关键资产,通过监视移动设备的系统数据总线中的数据流,事务或操作来监视这些关键资产的访问或使用 将可疑活动报告给移动设备的综合行为监测和分析系统。 然后,综合行为监测和分析系统可以使用该信息来快速识别和响应移动设备的恶意或性能降级活动。

    METHOD AND APPARATUS FOR NETWORK BASED POSITIONING (NBP)
    20.
    发明申请
    METHOD AND APPARATUS FOR NETWORK BASED POSITIONING (NBP) 有权
    基于网络定位的方法与装置(NBP)

    公开(公告)号:US20150215955A1

    公开(公告)日:2015-07-30

    申请号:US14165213

    申请日:2014-01-27

    CPC classification number: H04W72/10 G01S5/0263 H04W48/04 H04W64/00

    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 translation: 基于网络的定位的系统和方法包括被配置为将优先级分配给可定位在网络内的移动设备的服务器,以及基于分配给移动设备的相应优先级,为可定位的移动设备的网络定位分配网络资源。 服务器还可以被配置为仅允许可定位的移动设备的所选择的子集进入网络,以用于基于网络的定位和拒绝允许其余可定位的移动设备,其中可以基于移动设备的属性来确定所选择的子集 设备和/或移动设备的用户的特征。

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