公开(公告)号：US09519775B2

公开(公告)日：2016-12-13

申请号：US14044937

申请日：2013-10-03

Applicant: QUALCOMM Incorporated

Inventor： Vinay Sridhara ,  Salyajit Prabhakar Patne ,  Rajarshi Gupta

IPC: G06F12/14 ,  G06F7/04 ,  G08B29/00 ,  G06F15/177 ,  G06F11/30 ,  G06F21/55 ,  H04W12/12 ,  G06F21/57 ,  H04L29/06 ,  G06F9/445

CPC classification number: G06F21/55 ,  G06F9/44505 ,  G06F21/57 ,  G06F21/577 ,  H04L63/1408 ,  H04L63/1433 ,  H04L63/1441 ,  H04L63/145 ,  H04W12/12

Abstract: The various aspects include systems and methods for enabling mobile computing devices to recognize when they are at risk of experiencing malicious behavior in the near future given a current configuration. Thus, the various aspects enable mobile computing devices to anticipate malicious behaviors before a malicious behavior begins rather than after the malicious behavior has begun. In the various aspects, a network server may receive behavior vector information from multiple mobile computing devices and apply pattern recognition techniques to the received behavior vector information to identify malicious configurations and pathway configurations that may lead to identified malicious configurations. The network server may inform mobile computing devices of identified malicious configurations and the corresponding pathway configurations, thereby enabling mobile computing devices to anticipate and prevent malicious behavior from beginning by recognizing when they have entered a pathway configuration leading to malicious behavior.

Abstract translation: 各个方面包括系统和方法，用于使移动计算设备能够在给定当前配置的情况下识别何时在不久的将来遇到恶意行为的风险。 因此，各方面使得移动计算设备能够在恶意行为开始之前而不是在恶意行为开始之后预测恶意行为。 在各个方面，网络服务器可以从多个移动计算设备接收行为向量信息，并将模式识别技术应用于接收的行为向量信息，以识别可能导致识别的恶意配置的恶意配置和路由配置。 网络服务器可以向移动计算设备通知所识别的恶意配置和相应的路由配置，从而使得移动计算设备能够通过识别何时进入导致恶意行为的路径配置来开始预测和防止恶意行为。

公开(公告)号：US09497641B2

公开(公告)日：2016-11-15

申请号：US13759844

申请日：2013-02-05

Applicant: QUALCOMM Incorporated

Inventor： Lionel Jacques Garin ,  Vinay Sridhara ,  Xiaoxin Zhang ,  Sundar Raman ,  Gengsheng Zhang ,  Bernal A. Arroyo ,  Carlos Horacio Aldana

IPC: H04W24/00 ,  H04B7/06 ,  H04B7/08

CPC classification number: H04W24/00 ,  H04B7/0671 ,  H04B7/0828 ,  H04B7/0874

Abstract: Systems, apparatus and methods for determining a cyclic shift delay (CSD) mode from a plurality of CSD modes is disclosed. A received OFDM signal is converted to a channel impulse response (CIR) signal in the time domain and/or a channel frequency response (CFR) signal in the frequency domain. Matched filters and a comparator are used to determine a most likely current CSD mode. Alternatively, a classifier is used with a number of inputs including outputs from two or more matched filters and one or more outputs from a feature extractor. The feature extractor extracts features in the time domain from the CIR signal and/or in the frequency domain from the CFR signal useful in distinguishing various CSD modes.

Abstract translation: 公开了用于从多个CSD模式确定循环移位延迟（CSD）模式的系统，装置和方法。 接收到的OFDM信号在时域中被转换为信道脉冲响应（CIR）信号和/或频域中的信道频率响应（CFR）信号。 匹配滤波器和比较器用于确定最可能的当前CSD模式。 或者，分类器使用多个输入，包括来自两个或多个匹配滤波器的输出和来自特征提取器的一个或多个输出。 特征提取器从CIR信号和/或频域中提取时域中的特征，来自用于区分各种CSD模式的CFR信号。

公开(公告)号：US09495537B2

公开(公告)日：2016-11-15

申请号：US13923547

申请日：2013-06-21

Applicant: QUALCOMM Incorporated

Inventor： Rajarshi Gupta ,  Vinay Sridhara ,  Anil Gathala ,  Xuetao Wei

IPC: G06F21/00 ,  G06F21/50 ,  G06F21/31 ,  G06F21/55

CPC classification number: G06F21/50 ,  G06F21/316 ,  G06F21/552

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 translation: 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。

公开(公告)号：US20160327596A1

公开(公告)日：2016-11-10

申请号：US14705546

申请日：2015-05-06

Applicant: QUALCOMM Incorporated

Inventor： Mastooreh Salajegheh ,  Govindarajan Krishnamurthi ,  Mihai Christodorescu ,  Rajarshi Gupta ,  Vinay Sridhara ,  Patrick Hughes

IPC: G01R29/08 ,  G01R31/00

CPC classification number: G01R29/0814 ,  G01R29/0892 ,  G01R31/001 ,  G01R31/002

Abstract: Systems, methods, and devices of the various aspects enable detecting anomalous electromagnetic (EM) emissions from among a plurality of electronic devices. A device processor may receive EM emissions of a plurality of electronic devices, wherein the receiving device has no previous information about any of the plurality of electronic devices. The device processor may cross-correlate the EM emissions of the plurality of electronic devices over time. The device processor may identify a difference of the cross-correlated EM emissions from earlier cross-correlated EM emissions. The device processor may determine that the difference of the cross-correlated EM emissions from the earlier cross-correlated EM emissions indicates an anomaly in one or more of the plurality of electronic devices.

Abstract translation: 各方面的系统，方法和装置能够检测多个电子设备中的异常电磁（EM）发射。 设备处理器可以接收多个电子设备的EM发射，其中接收设备没有关于多个电子设备中的任何一个的先前的信息。 设备处理器可以随着时间使得多个电子设备的EM发射互相关联。 器件处理器可以识别来自先前的相互关联的EM发射的相互关联的EM发射的差异。 设备处理器可以确定来自较早的交叉相关EM发射的交叉相关EM发射的差异指示多个电子设备中的一个或多个中的异常。

公开(公告)号：US20160253498A1

公开(公告)日：2016-09-01

申请号：US14837936

申请日：2015-08-27

Applicant: QUALCOMM Incorporated

Inventor： Andres Valencia ,  Vinay Sridhara ,  Yin Chen ,  Rajarshi Gupta

IPC: G06F21/55 ,  G06N99/00 ,  G06F21/57

CPC classification number: G06F21/554 ,  G06F21/55 ,  G06F21/566 ,  G06F21/577 ,  G06F2221/034 ,  G06N99/005

Abstract: Various aspects include methods and computing devices implementing the methods for evaluating device behaviors in the computing devices. Aspect methods may include using a behavior-based machine learning technique to classify a device behavior as one of benign, suspicious, and non-benign. Aspect methods may include using one of a multi-label classification and a meta-classification technique to sub-classify the device behavior into one or more sub-categories. Aspect methods may include determining a relative importance of the device behavior based on the sub-classification, and determining whether to perform robust behavior-based operations based on the determined relative importance of the device behavior.

Abstract translation: 各方面包括实现用于评估计算设备中的设备行为的方法的方法和计算设备。 Aspect方法可能包括使用基于行为的机器学习技术将设备行为分类为良性，可疑和非良性之一。 方面方法可以包括使用多标签分类和元分类技术之一来将设备行为分类为一个或多个子类别。 方面方法可以包括基于子分类来确定设备行为的相对重要性，以及基于所确定的设备行为的相对重要性来确定是否执行鲁棒的基于行为的操作。

公开(公告)号：US20160143065A1

公开(公告)日：2016-05-19

申请号：US15004658

申请日：2016-01-22

Applicant: QUALCOMM Incorporated

Inventor： Rajarshi Gupta ,  Saumitra Mohan Das ,  Douglas Neal Rowitch ,  Vinay Sridhara

IPC: H04W76/00 ,  H04W4/22 ,  H04W4/04

CPC classification number: H04W76/50 ,  G01S5/02 ,  H04W4/023 ,  H04W4/04 ,  H04W4/90 ,  H04W64/003 ,  H04W84/005 ,  H04W84/045

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 translation: 描述了用于定位用于辅助紧急“911”服务的便携式服务接入收发器（PSAT）的设备，方法，技术和系统。 在一个实现中，指示PSAT的移动的一个或多个条件可以启动用于获得PSAT的新估计位置的过程。 在另一实现中，可以使用室内导航技术来确定或更新PSAT的位置。

公开(公告)号：US09324034B2

公开(公告)日：2016-04-26

申请号：US13773247

申请日：2013-02-21

Applicant: QUALCOMM Incorporated

Inventor： Rajarshi Gupta ,  Xuetao Wei ,  Anil Gathala ,  Vinay Sridhara

IPC: G06N99/00 ,  G06N5/04

CPC classification number: G06N99/005 ,  G06N5/043

Abstract: Methods, systems and devices for generating data models in a communication system may include applying machine learning techniques to generate a first family of classifier models using a boosted decision tree to describe a corpus of behavior vectors. Such behavior vectors may be used to compute a weight value for one or more nodes of the boosted decision tree. Classifier models factors having a high probably of determining whether a mobile device behavior is benign or not benign based on the computed weight values may be identified. Computing weight values for boosted decision tree nodes may include computing an exclusive answer ratio for generated boosted decision tree nodes. The identified factors may be applied to the corpus of behavior vectors to generate a second family of classifier models identifying fewer factors and data points relevant for enabling the mobile device to determine whether a behavior is benign or not benign.

Abstract translation: 用于在通信系统中生成数据模型的方法，系统和设备可以包括应用机器学习技术来生成使用加强的决策树来描述行为矢量语料库的分类器模型的第一族。 可以使用这样的行为矢量来计算升压决策树的一个或多个节点的权重值。 可以识别分类器模型的因素，其可能基于所计算的权重值来确定移动设备行为是良性还是不良性。 用于升压的决策树节点的计算权重值可以包括计算生成的升压决策树节点的独占应答比率。 识别的因素可以应用于行为矢量语料库以产生第二类分类器模型，其识别与使移动设备能够确定行为是良性还是不良性相关的较少因素和数据点。

公开(公告)号：US09198119B2

公开(公告)日：2015-11-24

申请号：US13785876

申请日：2013-03-05

Applicant: QUALCOMM Incorporated

Inventor： Sai Pradeep Venkatraman ,  Weihua Gao ,  Vinay Sridhara ,  Sina Firouzabadi

IPC: H04W84/12 ,  H04W84/18 ,  H04W80/04 ,  H04W8/26 ,  H04W88/06 ,  H04W48/16 ,  H04W8/00 ,  H04W4/00

CPC classification number: H04W48/16 ,  H04W8/005

Abstract: According to some aspects, a method includes communicating a request from a first device to a second device using near field communication (NFC). The request includes a preferred mode of wireless local area network (Wi-Fi) operation and state information of the first device. The method further includes receiving a reply at the first device, sent from the second device, including acceptance of the preferred mode of Wi-Fi operation. The method further includes communicating wireless information to establish the Wi-Fi communication link from the first device to the second device.

Abstract translation: 根据一些方面，一种方法包括使用近场通信（NFC）将来自第一设备的请求传送到第二设备。 该请求包括无线局域网（Wi-Fi）操作的优选模式和第一设备的状态信息。 该方法还包括从第二设备接收第一设备的回复，包括接受Wi-Fi操作的优选模式。 该方法还包括传送无线信息以建立从第一设备到第二设备的Wi-Fi通信链路。

公开(公告)号：US09147072B2

公开(公告)日：2015-09-29

申请号：US14064437

申请日：2013-10-28

Applicant: QUALCOMM Incorporated

Inventor： Kassem Fawaz ,  Vinay Sridhara ,  Rajarshi Gupta ,  Mihai Christodorescu

IPC: G06F7/04 ,  G06F17/30 ,  H04N7/16 ,  G06F21/56 ,  G06F21/55

CPC classification number: G06F21/566 ,  G06F21/552

Abstract: Methods, systems and devices use operating system execution states while monitoring applications executing on a mobile device to perform comprehensive behavioral monitoring and analysis include configuring a mobile device to monitor an activity of a software application, generate a shadow feature value that identifies an operating system 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 may also be configured to intelligently determine whether the operating system 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 operating system execution states of the software applications for which such determinations are relevant.

Abstract translation: 方法，系统和设备使用操作系统执行状态，同时监视在移动设备上执行的执行综合行为监控和分析的应用程序，包括配置移动设备来监视软件应用程序的活动，生成标识操作系统执行的阴影特征值 在该活动期间生成软件应用程序的状态，生成将所监视的活动与影子特征值相关联的行为向量，并基于生成的行为向量，阴影特征值和/或操作系统执行状态来确定活动是恶意还是良性 。 移动设备还可以被配置为智能地确定软件应用的操作系统执行状态是否与确定所监视的移动设备行为是否是恶意的或可疑的相关，并且仅监视软件应用的操作系统执行状态 这些确定是相关的。

公开(公告)号：US09031573B2

公开(公告)日：2015-05-12

申请号：US13831343

申请日：2013-03-14

Applicant: QUALCOMM Incorporated

Inventor： Behrooz Khorashadi ,  Sameera Poduri ,  Vinay Sridhara ,  Payam Pakzad

IPC: H04W24/00 ,  H04W64/00 ,  G01C21/20 ,  H04W4/02

CPC classification number: H04W4/023 ,  G01C21/005 ,  G01C21/206 ,  H04W4/025 ,  H04W4/027 ,  H04W4/04 ,  H04W64/00

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.

Abstract translation: 在一个实现中，方法可以包括：存储指示移动台的用户的至少一个属性的用户简档; 至少部分地基于来自移动台上的至少一个传感器的信号来确定测量值; 以及至少部分地基于所述至少一个属性和所述测量值与上下文参数映射数据库的关联来估计所述移动站的位置。