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MALWARE AND ANOMALY DETECTION VIA ACTIVITY RECOGNITION BASED ON SENSOR DATA

机译:基于传感器数据的活动识别进行恶意软件和异常检测

摘要

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.
机译:公开了一种用于基于传感器的经由活动识别的恶意软件和异常检测的系统。该系统可以分析在选定时间段内从与设备相关联的一个或多个传感器收集的传感器数据。一旦传感器数据被分析,当设备处于连接状态时,系统可以确定设备的环境。系统可以基于在所选时间段期间收集的传感器数据来确定设备的环境。系统还可以确定在连接状态期间设备接收或传输的流量是否在白名单中。此外,如果确定业务量不在白名单中,或者为设备确定的上下文指示该上下文与业务量不相关,则系统可以发送警报。

著录项

  • 公开/公告号US2017279842A1

    专利类型

  • 公开/公告日2017-09-28

    原文格式PDF

  • 申请/专利权人 AT&T INTELLECTUAL PROPERTY I L.P.;

    申请/专利号US201715620495

  • 发明设计人 ROGER P. JOVER;ILONA MURYNETS;

    申请日2017-06-12

  • 分类号H04L29/06;H04W12/12;

  • 国家 US

  • 入库时间 2022-08-21 13:51:15

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