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    Malware And Anomaly Detection Via Activity Recognition Based On Sensor Data
    5.
    发明申请
    Malware And Anomaly Detection Via Activity Recognition Based On Sensor Data 有权
    基于传感器数据的活动识别的恶意软件和异常检测

    公开(公告)号：US20150128265A1

    公开(公告)日：2015-05-07

    申请号：US14070875

    申请日：2013-11-04

    Applicant: AT&T INTELLECTUAL PROPERTY I, L.P.

    Inventor： Roger P. Jover ,  Ilona Murynets

    IPC: H04L29/06

    CPC classification number: H04L63/1425 ,  H04L63/14 ,  H04L63/1416 ,  H04L63/1441 ,  H04L63/145 ,  H04L2463/144 ,  H04W12/12

    Abstract: A system for malware and anomaly detection via activity recognition based on sensor is disclosed. The system may analyze sensor data collected during a selected time period from one or more sensors that are associated with a device. Once the sensor data is analyzed, the system may determine a context of the device when the device is in a connected state. The system may determine the context of the device based on the sensor data collected during the selected time period. The system may also determine if traffic received or transmitted by the device during the connected state is in a white list. Furthermore, the system may transmit an alert if the traffic is determined to not be in the white list or if the context determined for the device indicates that the context does not correlate with the traffic.

    Abstract translation: 公开了一种通过基于传感器的活动识别的恶意软件和异常检测系统。 系统可以分析在与设备相关联的一个或多个传感器的选定时间段期间收集的传感器数据。 一旦分析了传感器数据，当设备处于连接状态时，系统可以确定设备的上下文。 系统可以基于在所选择的时间段期间收集的传感器数据来确定设备的上下文。 系统还可以确定在连接状态期间由设备接收或发送的业务是白名单。 此外，如果业务被确定为不在白名单中，或者如果为设备确定的上下文指示上下文与业务不相关，则系统可以发送警报。

    Resolving customer communication security vulnerabilities
    6.
    发明授权
    Resolving customer communication security vulnerabilities 有权

    公开(公告)号：US10819735B2

    公开(公告)日：2020-10-27

    申请号：US16415584

    申请日：2019-05-17

    Applicant: AT&T INTELLECTUAL PROPERTY I, L.P.

    Inventor： Ilona Murynets

    IPC: H04L29/06 ,  G06F11/36 ,  G06F11/30 ,  G06F11/34 ,  G06F21/56 ,  H04L12/26 ,  H04L12/24

    Abstract: Various embodiments for resolving customer communication security vulnerabilities are provided. Customer traffic data is stored in a database and analyzed to identify problem traffic. A report of a first user device and a usage history for the first user device is obtained. Similarities between the usage history of the first user device and the problem traffic are searched for to identify an issue. A first vulnerability is remedied on the first user device by a first remote action in response to the issue being identified. A second user device that is in a same account as the first user device and that has engaged in similar problematic communications as the first user device is identified. A second vulnerability is proactively remedied on the second user device by a second remote action.

    Malware and anomaly detection via activity recognition based on sensor data
    8.
    发明授权
    Malware and anomaly detection via activity recognition based on sensor data 有权
    基于传感器数据的活动识别的恶意软件和异常检测

    公开(公告)号：US09319423B2

    公开(公告)日：2016-04-19

    申请号：US14070875

    申请日：2013-11-04

    Applicant: AT&T INTELLECTUAL PROPERTY I, L.P.

    Inventor： Roger P. Jover ,  Ilona Murynets

    IPC: G06F11/00 ,  H04L29/06

    CPC classification number: H04L63/1425 ,  H04L63/14 ,  H04L63/1416 ,  H04L63/1441 ,  H04L63/145 ,  H04L2463/144 ,  H04W12/12

    Abstract: A system for malware and anomaly detection via activity recognition based on sensor is disclosed. The system may analyze sensor data collected during a selected time period from one or more sensors that are associated with a device. Once the sensor data is analyzed, the system may determine a context of the device when the device is in a connected state. The system may determine the context of the device based on the sensor data collected during the selected time period. The system may also determine if traffic received or transmitted by the device during the connected state is in a white list. Furthermore, the system may transmit an alert if the traffic is determined to not be in the white list or if the context determined for the device indicates that the context does not correlate with the traffic.

    Abstract translation: 公开了一种通过基于传感器的活动识别的恶意软件和异常检测系统。 系统可以分析在与设备相关联的一个或多个传感器的选定时间段期间收集的传感器数据。 一旦分析了传感器数据，当设备处于连接状态时，系统可以确定设备的上下文。 系统可以基于在所选择的时间段期间收集的传感器数据来确定设备的上下文。 系统还可以确定在连接状态期间由设备接收或发送的业务是白名单。 此外，如果业务被确定为不在白名单中，或者如果为设备确定的上下文指示上下文与业务不相关，则系统可以发送警报。

    Malware and anomaly detection via activity recognition based on sensor data
    9.
    发明授权
    Malware and anomaly detection via activity recognition based on sensor data 有权

    公开(公告)号：US10516686B2

    公开(公告)日：2019-12-24

    申请号：US15620495

    申请日：2017-06-12

    Applicant: AT&T Intellectual Property I, L.P.

    Inventor： Roger P. Jover ,  Ilona Murynets

    IPC: H04L29/06 ,  H04W12/12 ,  H04W12/00

    Abstract: A system for malware and anomaly detection via activity recognition based on sensor is disclosed. The system may analyze sensor data collected during a selected time period from one or more sensors that are associated with a device. Once the sensor data is analyzed, the system may determine a context of the device when the device is in a connected state. The system may determine the context of the device based on the sensor data collected during the selected time period. The system may also determine if traffic received or transmitted by the device during the connected state is in a white list. Furthermore, the system may transmit an alert if the traffic is determined to not be in the white list or if the context determined for the device indicates that the context does not correlate with the traffic.

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