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ON-LINE BEHAVIORAL ANALYSIS ENGINE IN MOBILE DEVICE WITH MULTIPLE ANALYZER MODEL PROVIDERS

机译:具有多个分析器模型提供程序的移动设备中的在线行为分析引擎

摘要

Methods, systems and devices for generating data models in a client-cloud communication system may include applying machine learning techniques to generate a first family of classifier models that describe a cloud corpus of behavior vectors. Such vectors may be analyzed to identify factors in the first family of classifier models that have the highest probability of enabling a mobile device to better determine whether a mobile device behavior is malicious or benign. Based on this analysis, a second family of classifier models may be generated that identify significantly fewer factors and data points as being relevant for enabling the mobile device to better determine whether the mobile device behavior is malicious or benign based on the determined factors. A mobile device classifier module based on the second family of classifier models may be generated and made available for download by mobile devices, including devices contributing behavior vectors.
机译:用于在客户端-云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描述行为向量的云主体的分类器模型的第一族。可以对这样的向量进行分析以识别第一类分类器模型中的因素,这些因素具有使移动设备能够更好地确定移动设备行为是恶意还是良性的最高可能性。基于该分析,可以生成第二类分类器模型,该第二类分类器模型基于所确定的因素来识别与使移动设备能够更好地确定移动设备行为是恶意还是良性相关的重要因素和数据点。基于第二家族分类器模型的移动设备分类器模块可以被生成并且可以由包括贡献行为矢量的设备的移动设备下载。

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