公开(公告)号：EP3207680A1

公开(公告)日：2017-08-23

申请号：EP15757108.4

申请日：2015-08-20

Applicant: Qualcomm Incorporated

Inventor： GUPTA, Rajarshi ,  PATNE, Satyajit Prabhakar

IPC: H04L29/06 ,  H04W12/06 ,  H04W12/08

CPC classification number: G06F21/31 ,  G06F21/316 ,  G06F21/577 ,  G06F2221/034 ,  H04L63/08 ,  H04L63/105 ,  H04L63/1425 ,  H04L63/1433 ,  H04L63/145 ,  H04L2463/082 ,  H04W12/06 ,  H04W12/08

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, and/or otherwise respond to malicious or performance-degrading behaviors of the computing device. As part of these operations, the processor may perform multifactor authentication operations that include determining one or more of a transaction type criticality value, a user confidence value, a software integrity confidence value, and a historical behavior value, using the one or more of these values to determine a number of authentication factors that are be evaluated when authenticating a user of the computing device, and authenticating the user by evaluating the determined number of authentication factors.

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，纠正和/或以其他方式对计算设备的恶意或性能退化行为做出响应的方法。 作为这些操作的一部分，处理器可执行多因素认证操作，其包括使用这些中的一个或多个来确定交易类型关键性值，用户置信度值，软件完整性置信度值和历史行为值中的一个或多个 值以确定在对计算设备的用户进行认证时被评估的认证因素的数量，以及通过评估所确定的认证因子的数量来认证用户。

公开(公告)号：EP3053319A1

公开(公告)日：2016-08-10

申请号：EP14790806.5

申请日：2014-09-19

Applicant: Qualcomm Incorporated

Inventor： SRIDHARA, Vinay ,  PATNE, Satyajit Prabhakar ,  GUPTA, Rajarshi

IPC: H04L29/06 ,  H04W12/12 ,  H04L12/24 ,  G06F21/57

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 (102) 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 (102) to anticipate malicious behaviors before a malicious behavior begins rather than after the malicious behavior has begun. In the various aspects, a network server (116) may receive behavior vector information from multiple mobile computing devices (102) 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 (116) may inform mobile computing devices (102) of identified malicious configurations and the corresponding pathway configurations, thereby enabling mobile computing devices (102) to anticipate and prevent malicious behavior from beginning by recognizing when they have entered a pathway configuration leading to malicious behavior.