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1. 发明授权

US08935788B1 Two stage virus detection 有权
标题翻译：两级病毒检测
公开(公告)号：US08935788B1
公开(公告)日：2015-01-13
申请号：US12252205
申请日：2008-10-15
申请人： Lili Diao , Vincent Chan , Patrick Mg Lu
发明人： Lili Diao , Vincent Chan , Patrick Mg Lu
IPC分类号： G06F11/30 , G06F21/56
CPC分类号： G06F21/564 , G06F21/561
摘要： A two stage virus detection system detects viruses in target files. In the first stage, a training application receives a master virus pattern file recording all known virus patterns and generates a features list containing fundamental virus signatures from the virus patterns, a novelty detection model, a classification model, and a set of segmented virus pattern files. In the second stage, a detection application scans a target file for viruses using the generated outputs from the first stage rather than using the master virus pattern file directly to do traditional pattern matching. The results of the scan can vary in detail depending on a fuzzy scan level. For fuzzy scan level “1,” the existence of a virus is returned. For fuzzy scan level “2,” the grant virus type found is returned. For fuzzy scan level “3,” the exact virus name is returned. This invention provides a solution for the problems caused by traditional virus detection solution: slow scanning speed, big pattern file, big burden on computation resource (CPU, RAM etc.), as well as heavy pattern updating traffic via networks.
摘要翻译：两级病毒检测系统检测目标文件中的病毒。在第一阶段，训练应用程序接收记录所有已知病毒模式的主病毒模式文件，并生成包含病毒模式的基本病毒签名的功能列表，新颖性检测模型，分类模型和一组分段病毒模式文件。在第二阶段，检测应用程序使用来自第一阶段的生成输出来扫描目标文件以获取病毒，而不是直接使用主病毒码文件来进行传统的模式匹配。根据模糊扫描级别，扫描结果可能会有详细的变化。对于模糊扫描级别“1”，返回病毒的存在。对于模糊扫描级别“2”，返回发现的授权病毒类型。对于模糊扫描级别“3”，返回确切的病毒名称。本发明为传统病毒检测解决方案提供了一个解决方案：扫描速度慢，格式文件大，计算资源负担大（CPU，RAM等），以及通过网络大量更新流量。

2. 发明授权

US08023974B1 Lightweight SVM-based content filtering system for mobile phones 有权
标题翻译：用于手机的基于SVM的轻量级内容过滤系统
公开(公告)号：US08023974B1
公开(公告)日：2011-09-20
申请号：US11706539
申请日：2007-02-15
申请人： Lili Diao , Vincent Chan , Patrick MG Lu
发明人： Lili Diao , Vincent Chan , Patrick MG Lu
IPC分类号： H04W4/00
CPC分类号： G06K9/6269 , H04L51/12 , H04W12/12
摘要： In one embodiment, a content filtering system generates a support vector machine (SVM) learning model in a server computer and provides the SVM learning model to a mobile phone for use in classifying text messages. The SVM learning model may be generated in the server computer by training a support vector machine with sample text messages that include spam and legitimate text messages. A resulting intermediate SVM learning model from the support vector machine may include a threshold value, support vectors and alpha values. The SVM learning model in the mobile phone may include the threshold value, the features, and the weights of the features. An incoming text message may be parsed for the features. The weights of features found in the incoming text message may be added and compared to the threshold value to determine whether or not the incoming text message is spam.
摘要翻译：在一个实施例中，内容过滤系统在服务器计算机中生成支持向量机（SVM）学习模型，并将SVM学习模型提供给移动电话以用于分类文本消息。 SVM学习模型可以在服务器计算机中通过训练具有包括垃圾邮件和合法文本消息的示例文本消息的支持向量机来生成。来自支持向量机的得到的中间SVM学习模型可以包括阈值，支持向量和α值。移动电话中的SVM学习模型可以包括阈值，特征和特征的权重。可能会为特征解析输入的文本消息。可以添加传入文本消息中发现的功能的权重并将其与阈值进行比较，以确定传入的文本消息是否为垃圾邮件。

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