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81.发明申请Malware Detection and Prevention by Monitoring and Modifying a Hardware Pipeline 有权监控和修改硬件管道的恶意软件检测和预防公开(公告)号：US20150101048A1
公开(公告)日：2015-04-09
申请号：US14044956
申请日：2013-10-03
IPC分类号： G06F21/55
CPC分类号： G06F21/55 , G06F9/30145 , G06F9/3861 , G06F11/3612 , G06F21/125 , G06F21/52 , G06F21/54 , G06F21/566 , G06F21/577 , H04L63/1425 , H04L63/1433 , H04L63/145 , H04W12/12
摘要： 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.
摘要翻译： 各方面提供了一种用于在移动计算设备发生之前通过监视和修改在移动计算设备的硬件流水线中挂起的指令（即，排队的指令）来识别和防止恶意行为的方法。 在各个方面，移动计算设备可以预先确定在给定移动计算设备的当前配置的情况下，是否执行一组排队指令将导致恶意配置。 当移动计算设备确定执行排队的指令将导致恶意配置时，移动计算设备可以在排队的指令被执行之前停止执行排队的指令或采取其他动作来抢占恶意行为。
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82.发明申请METHOD AND APPARATUS FOR IMPROVING POSITIONING ACCURACY OF A MOBILE DEVICE WITH A LOWER POSITIONING CAPABILITY 审中-公开用于提高具有较低定位能力的移动设备的定位精度的方法和装置公开(公告)号：US20150087328A1
公开(公告)日：2015-03-26
申请号：US14034089
申请日：2013-09-23
IPC分类号： H04W64/00
CPC分类号： H04W64/00
摘要： 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 improving positioning accuracy of a mobile device with a lower positioning capability, such as, for example, via one or more proximate mobile devices with a higher positioning capability.
摘要翻译： 本文公开的可以全部或部分地利用的示例性方法，装置或制造方式来促进或支持用于改善具有较低定位能力的移动装置的定位精度的一个或多个操作或技术，例如， 例如，经由具有较高定位能力的一个或多个邻近移动设备。
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公开(公告)号：US20140281698A1
公开(公告)日：2014-09-18
申请号：US13797916
申请日：2013-03-12
IPC分类号： G06F11/14
CPC分类号： G06F11/1415 , G06F11/1402 , G09B29/005
摘要： Methods, systems, computer-readable media, and apparatuses for detection of anomalies within indoor map information are presented. In some embodiments, the method includes receiving a digital map. The method may further include identifying one or more anomalies within the digital map using a software-based anomaly detection tool. The method may also include displaying one or more suggested corrections to a user based on the one or more identified anomalies. The method may additionally include correcting the one or more identified anomalies within the digital map.
摘要翻译： 提出了用于检测室内地图信息中的异常的方法，系统，计算机可读介质和装置。 在一些实施例中，该方法包括接收数字地图。 该方法还可以包括使用基于软件的异常检测工具识别数字地图内的一个或多个异常。 该方法还可以包括基于一个或多个所识别的异常来向用户显示一个或多个建议的修正。 该方法可以另外包括校正数字地图内的一个或多个识别的异常。
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84.发明申请Methods and Systems of Using Boosted Decision Stumps and Joint Feature Selection and Culling Algorithms for the Efficient Classification of Mobile Device Behaviors 有权使用增强决策树的方法和系统以及移动设备行为的有效分类的联合特征选择和剔除算法公开(公告)号：US20140188781A1
公开(公告)日：2014-07-03
申请号：US14090261
申请日：2013-11-26
发明人： Kassem Fawaz , Vinay Sridhara , Rajarshi Gupta
IPC分类号： G06N5/02
摘要： Methods and systems for classifying mobile device behavior include configuring a server use a large corpus of mobile device behaviors to generate a full classifier model that includes a finite state machine suitable for conversion into boosted decision stumps and/or which describes all or many of the features relevant to determining whether a mobile device behavior is benign or contributing to the mobile device's degradation over time. A mobile device may receive the full classifier model and use the model to generate a full set of boosted decision stumps from which a more focused or lean classifier model is generated by culling the full set to a subset suitable for efficiently determining whether mobile device behavior are benign. Boosted decision stumps may be culled by selecting all boosted decision stumps that depend upon a limited set of test conditions.
摘要翻译： 用于分类移动设备行为的方法和系统包括配置服务器使用大的移动设备行为语料库来生成包括适合于转换为增强的决策树桩的有限状态机和/或描述所有或许多特征的完整分类器模型 与确定移动设备行为是否良好或对移动设备随着时间的退化有所贡献相关。 移动设备可以接收完整的分类器模型并且使用该模型来产生一整套增强的决策树桩，通过将整个集合剔除，从而可以通过将整个集合剔除，从而从中产生更集中或精确的分类器模型，适合于有效地确定移动设备行为是否 良性。 通过选择依赖于有限的测试条件的所有提升的决策树桩，可以剔除增强的决策树桩。
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85.发明申请公开(公告)号：US20140187177A1
公开(公告)日：2014-07-03
申请号：US14091707
申请日：2013-11-27
发明人： Vinay Sridhara , Rajarshi Gupta , Kassem Fawaz
CPC分类号： H04B17/391 , G06N5/003 , G06N99/005
摘要： The various aspects provide a mobile device and methods implemented on the mobile device for modifying behavior models to account for device-specific or device-state-specific features. In the various aspects, a behavior analyzer module may leverage a full feature set of behavior models (i.e. a large classifier model) received from a network server to create lean classifier models for use in monitoring for malicious behavior on the mobile device, and the behavior analyzer module may dynamically modify these lean classifier models to include features specific to the mobile device and/or the mobile device's current configuration. Thus, the various aspects may enhance overall security for a particular mobile device by taking the mobile device and its current configuration into account and may improve overall performance by monitoring only features that are relevant to the mobile device.
摘要翻译： 各个方面提供在移动设备上实现的移动设备和方法，用于修改行为模型以考虑设备特定或设备状态特定的特征。 在各个方面，行为分析器模块可以利用从网络服务器接收的行为模型（即大型分类器模型）的完整特征集来创建用于监视移动设备上的恶意行为的精简分类器模型，以及行为 分析器模块可以动态地修改这些精益分类器模型以包括特定于移动设备和/或移动设备的当前配置的特征。 因此，各个方面可以通过考虑移动设备及其当前配置来增强特定移动设备的总体安全性，并且可以通过仅监视与移动设备相关的特征来提高整体性能。
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86.发明申请Adaptive Observation of Driver and Hardware Level Behavioral Features on a Mobile Device 审中-公开移动设备上驱动程序和硬件级别行为特征的自适应观察公开(公告)号：US20140150100A1
公开(公告)日：2014-05-29
申请号：US14161853
申请日：2014-01-23
IPC分类号： H04L29/06
CPC分类号： H04L63/1425 , G06F21/316 , G06F21/552 , G06N5/043
摘要： 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.
摘要翻译： 用于智能地，动态地和/或自适应地检测待观察的计算设备行为，要观察的行为的数量以及细节或粒度的级别来检测可疑或降级性能的移动设备行为的方法，设备和系统 在那里要观察移动设备的行为。 各个方面有效地识别可疑或降低性能的移动设备行为，而不需要过多的处理，存储器或能量资源。
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公开(公告)号：US20130237246A1
公开(公告)日：2013-09-12
申请号：US13859658
申请日：2013-04-09
IPC分类号： G01S5/10
CPC分类号： G01S5/10 , G01S5/0205 , G01S5/14 , G01S13/765 , H04W24/00 , H04W64/00
摘要： An example method for updating a wireless signal model includes: measuring a distance from a mobile station to each wireless access point, of multiple wireless access points, based upon a wireless signal model; calculating a position of the mobile station based upon the measured distance; determining a computed distance to each wireless access point based upon the calculated position of the mobile station; updating the wireless signal model based upon the measured and computed distances to each wireless access point; and determining whether the wireless signal model has converged.
摘要翻译： 用于更新无线信号模型的示例性方法包括：基于无线信号模型测量多个无线接入点中的从移动台到每个无线接入点的距离; 基于所测量的距离计算移动台的位置; 基于所计算的所述移动台的位置确定到每个无线接入点的计算距离; 基于到每个无线接入点的测量和计算的距离来更新无线信号模型; 以及确定无线信号模型是否已收敛。
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公开(公告)号：US20130184012A1
公开(公告)日：2013-07-18
申请号：US13781414
申请日：2013-02-28
摘要： The subject matter disclosed herein relates to systems, methods, apparatuses, devices, articles, and means for updating radio models. For certain example implementations, a method for one or more server devices may comprise receiving at one or more communication interfaces at least one measurement that corresponds to a position of a first mobile device within an indoor environment. At least one radio model that is stored in one or more memories may be updated based, at least in part, on the at least one measurement to produce at least one updated radio model. The at least one radio model and the at least one updated radio model may correspond to the indoor environment. The at least one updated radio model may be transmitted to enable a second mobile device to use the at least one updated radio model for positioning within the indoor environment. Other example implementations are described herein.
摘要翻译： 本文公开的主题涉及用于更新无线电模型的系统，方法，装置，装置，物品和装置。 对于某些示例实现，用于一个或多个服务器设备的方法可以包括在一个或多个通信接口处接收与室内环境中的第一移动设备的位置相对应的至少一个测量。 至少一个存储在一个或多个存储器中的无线电模型可以至少部分地基于所述至少一个测量来更新，以产生至少一个更新的无线电模型。 所述至少一个无线电模型和所述至少一个更新的无线电模型可以对应于室内环境。 可以发送所述至少一个更新的无线电模型以使得第二移动设备能够使用至少一个更新的无线电模型来在室内环境内定位。 本文描述了其他示例实现。
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公开(公告)号：US10452840B2
公开(公告)日：2019-10-22
申请号：US15210815
申请日：2016-07-14
发明人： Yin Chen , Dong Li , Vinay Sridhara
摘要： Methods, systems and devices compute and use the execution session contexts of software applications to perform behavioral monitoring and analysis operations. A mobile device may be configured to monitor user activity and system activity of a software application, generate a shadow feature value that identifies actual execution session context of the software application during that activity, generate a behavior vector that incorporates context into the values describing behaviors, and determine whether the activity is malicious or benign based, at least in part, on the generated behavior vector. The mobile device processor may also be configured to intelligently determine whether the execution session context 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 session contexts of the software applications for which such determinations are relevant.
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90.发明授权公开(公告)号：US10063585B2
公开(公告)日：2018-08-28
申请号：US14661195
申请日：2015-03-18
发明人： Mastooreh Salajegheh , Mona Mahmoudi , Vinay Sridhara , Mihai Christodorescu , Gheorghe Calin Cascaval
IPC分类号： H04L29/06 , G06F9/46 , G06F11/34 , G06F21/55 , G06F21/62 , H04W12/12 , H04W24/10 , H04W12/02
摘要： 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.
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