公开(公告)号：US20160103996A1

公开(公告)日：2016-04-14

申请号：US14510772

申请日：2014-10-09

Applicant: QUALCOMM Incorporated

Inventor： Mastooreh Salajegheh ,  Vinay Sridhara ,  Yin Chen ,  Rajarshi Gupta

IPC: G06F21/57 ,  G06F11/30 ,  G06F11/34

CPC classification number: G06F21/577 ,  G06F11/3024 ,  G06F11/3438 ,  G06F21/316 ,  G06F21/552 ,  H04L63/1425 ,  H04L63/145

Abstract: A computing device processor may be configured with processor-executable instructions to implement methods of using behavioral analysis and machine learning techniques to identify, prevent, correct, or otherwise respond to malicious or performance-degrading behaviors of the computing device. As part of these operations, the processor may generate user-persona information that characterizes the user based on that user's activities, preferences, age, occupation, habits, moods, emotional states, personality, device usage patterns, etc. The processor may use the user-persona information to dynamically determine the number of device features that are monitored or evaluated in the computing device, to identify the device features that are most relevant to determining whether the device behavior is not consistent with a pattern of ordinary usage of the computing device by the user, and to better identify or respond to non-benign behaviors of the computing device.

Abstract translation: 计算设备处理器可以配置有处理器可执行指令，以实现使用行为分析和机器学习技术来识别，防止，纠正或以其他方式响应计算设备的恶意或性能降级的行为的方法。 作为这些操作的一部分，处理器可以基于该用户的活动，偏好，年龄，职业，习惯，情绪，情绪状态，个性，设备使用模式等来生成表征用户的用户角色信息。处理器可以使用 用户角色信息以动态地确定在计算设备中被监视或评估的设备特征的数量，以识别与确定设备行为是否与计算设备的普通使用模式最相关的设备特征 并且更好地识别或响应计算设备的非良性行为。

公开(公告)号：US20190297465A1

公开(公告)日：2019-09-26

申请号：US16441857

申请日：2019-06-14

Applicant: QUALCOMM Incorporated

Inventor： Hui CHAO ,  Saumitra Mohan Das ,  Yin Chen

IPC: H04W4/029 ,  G01S5/02 ,  G06Q30/02 ,  H04W4/021 ,  G06Q10/06

Abstract: Methods and systems for providing information associated with a location history of a mobile device to one or more applications are disclosed. A mobile device generates one or more location history records based on one or more locations of the mobile device, each location history record comprising one or more points of interest and a duration at the one or more points of interest, receives an information request from at least one application, determines a subset of the one or more location history records that meet criteria from the information request, determines a level of permission for the at least one application based on the information request and the subset of the one or more location history records, and provides information associated with the subset of the one or more location history records to the at least one application based on the level of permission.

公开(公告)号：US10028084B2

公开(公告)日：2018-07-17

申请号：US14618977

申请日：2015-02-10

Applicant: QUALCOMM Incorporated

Inventor： Yin Chen ,  Saumitra Mohan Das ,  Payam Pakzad

IPC: H04W24/00 ,  H04W4/02 ,  G01S1/06 ,  H04W4/04

Abstract: Methods, systems, computer-readable media, and apparatuses for determining a position indicator are presented. In some embodiments, position data indicating a position of a mobile device is obtained. A position indicator is determined based on at least one region of a map. The position of the mobile device is located within the at least one region. The position indicator indicates a map-feature-dependent region of the map. The position indicator is provided.

公开(公告)号：US10021123B2

公开(公告)日：2018-07-10

申请号：US14753666

申请日：2015-06-29

Applicant: QUALCOMM Incorporated

Inventor： Saumitra Mohan Das ,  Mona Mahmoudi ,  Vinay Sridhara ,  Rajarshi Gupta ,  Yin Chen

IPC: H04L29/06 ,  H04L12/26 ,  G06F21/55 ,  H04L12/24

CPC classification number: H04L63/1425 ,  G06F21/552 ,  H04L41/0631 ,  H04L43/0817 ,  H04L63/1416

Abstract: Systems, methods, and devices of the various aspects enable identification of anomalous application behavior. A computing device processor may detect network communication activity of an application on the computing device. The processor may identify one or more device states of the computing device, and one or more categories of the application. The processor may determine whether the application is behaving anomalously based on a correlation of the detected network communication activity of the application, the identified one or more device states of the computing device, and the identified one or more categories of the application.

公开(公告)号：US20180077569A1

公开(公告)日：2018-03-15

申请号：US15262358

申请日：2016-09-12

Applicant: QUALCOMM Incorporated

Inventor： Hui Chao ,  Yin Chen ,  Ramin Samadani

IPC: H04W12/06 ,  H04L29/08 ,  H04L12/26 ,  H04W4/02

CPC classification number: H04W12/06 ,  H04L43/16 ,  H04L67/104 ,  H04W4/023

Abstract: Implementations include systems and methods for managing security for a mobile communication device. In implementations, a processor of the mobile communication device may determine environment context information. The processor may receive safety information from one or more peer devices. The processor may determine an authentication requirement for the mobile communication device based on the received safety information and the determined environment context information. The processor may deny access to a function of the mobile communication device in response to determining that the determined authentication requirement is not satisfied.

公开(公告)号：US09910984B2

公开(公告)日：2018-03-06

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 ,  G06F21/57 ,  G06N99/00 ,  G06F21/56

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.

公开(公告)号：US09875357B2

公开(公告)日：2018-01-23

申请号：US14616046

申请日：2015-02-06

Applicant: QUALCOMM Incorporated

Inventor： Yin Chen ,  Man Ki Yoon ,  Vinay Sridhara

IPC: G06F21/00 ,  G06F12/14 ,  G06F21/56 ,  H04L29/06 ,  G06F21/31

CPC classification number: G06F21/566 ,  G06F21/316 ,  G06F2221/2133

Abstract: A computing device processor may be configured with processor-executable instructions to implement methods of detecting and responding to fake user interaction (UI) events. The processor may determine whether a user interaction event is a fake user interaction event by analyzing raw data generated by one or more hardware drivers in conjunction with user interaction event information generated or received by the high-level operating system. In addition, the processor may be configured with processor-executable instructions to implement methods of using behavioral analysis and machine learning techniques to identify, prevent, correct, or otherwise respond to malicious or performance-degrading behaviors of the computing device based on whether a detected user interaction event is an authentic or fake user interaction event.

公开(公告)号：US20170367051A1

公开(公告)日：2017-12-21

申请号：US15675530

申请日：2017-08-11

Applicant: QUALCOMM Incorporated

Inventor： Payam Pakzad ,  Yin Chen

IPC: H04W52/02 ,  H04W64/00 ,  G01C21/20 ,  G01S5/02

CPC classification number: H04W52/0261 ,  G01C21/206 ,  G01S5/0236 ,  G01S5/0263 ,  H04W64/00 ,  Y02D70/1262 ,  Y02D70/1264 ,  Y02D70/142 ,  Y02D70/144 ,  Y02D70/146 ,  Y02D70/164 ,  Y02D70/26

Abstract: Various techniques are provided which may be implemented as methods, apparatuses and articles of manufacture for use by a mobile device or one or more computing devices to provide for or otherwise support motion state based mobile device positioning. In an example, a method may be implemented at a computing device to obtain a set of grid points corresponding to an electronic map representative of a particular environment, subdivide the set of grid points to identify two or more subsets of grid points for use in position estimation by a mobile device based, at least in part, on two or more motion states corresponding to the mobile device, and communicate at least one of the two or more subsets of grid points between the computing device and the mobile device.

公开(公告)号：US20160379136A1

公开(公告)日：2016-12-29

申请号：US14751572

申请日：2015-06-26

Applicant: QUALCOMM Incorporated

Inventor： Yin Chen ,  Vinay Sridhara ,  Mihai Christodorescu

IPC: G06N99/00

CPC classification number: G06N20/00 ,  G06F21/552 ,  G06F21/566

Abstract: An aspect computing device may be configured to perform program analysis operation in response to classifying a behavior as non-benign. The program analysis operation may identify new sequences of API calls or activity patterns that are associated with the identified non-benign behaviors. The computing device may learn new behavior features based on the program analysis operation or update existing behavior features based on the program analysis operation. For example, API sequences observed to occur when a non-benign behavior is recognized may be added to behavior features observed during program analysis operation.

Abstract translation: 方面计算设备可以被配置为响应于将行为分类为非良性来执行程序分析操作。 程序分析操作可以识别与所识别的非良性行为相关联的API调用或活动模式的新序列。 计算设备可以基于程序分析操作学习新的行为特征，或者基于程序分析操作来更新现有行为特征。 例如，当识别到非良性行为时观察到发生的API序列可以被添加到在程序分析操作期间观察到的行为特征。

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。