MALWARE DETECTION VIA REPUTATION SYSTEM
    1.
    发明申请
    MALWARE DETECTION VIA REPUTATION SYSTEM 有权
    通过报警系统的恶意检测

    公开(公告)号:US20110162070A1

    公开(公告)日:2011-06-30

    申请号:US12693765

    申请日:2010-01-26

    IPC分类号: G06F21/00 G06F11/00

    CPC分类号: G06F21/564 G06F21/56

    摘要: A computer network device receives a digital file and extracts a plurality of high level features from the file. The plurality of high level features are evaluated using a classifier to determine whether the file is benign or malicious. The file is forwarded to a requesting computer if the file is determined to be benign, and blocked if the file is determined to be malicious.

    摘要翻译: 计算机网络设备接收数字文件并从文件中提取多个高级特征。 使用分类器评估多个高级特征以确定文件是良性还是恶意的。 如果文件被确定为良性,则将文件转发到请求计算机,如果该文件被确定为恶意文件,则该文件被阻止。

    Malware detection via reputation system
    2.
    发明授权
    Malware detection via reputation system 有权
    通过声誉系统检测恶意软件

    公开(公告)号:US08719939B2

    公开(公告)日:2014-05-06

    申请号:US12693765

    申请日:2010-01-26

    IPC分类号: H04L29/06

    CPC分类号: G06F21/564 G06F21/56

    摘要: A computer network device receives a digital file and extracts a plurality of high level features from the file. The plurality of high level features are evaluated using a classifier to determine whether the file is benign or malicious. The file is forwarded to a requesting computer if the file is determined to be benign, and blocked if the file is determined to be malicious.

    摘要翻译: 计算机网络设备接收数字文件并从文件中提取多个高级特征。 使用分类器评估多个高级特征以确定文件是良性还是恶意的。 如果文件被确定为良性,则将文件转发到请求计算机,如果该文件被确定为恶意文件,则该文件被阻止。

    SYSTEM AND METHOD FOR BOTNET DETECTION BY COMPREHENSIVE EMAIL BEHAVIORAL ANALYSIS
    5.
    发明申请
    SYSTEM AND METHOD FOR BOTNET DETECTION BY COMPREHENSIVE EMAIL BEHAVIORAL ANALYSIS 审中-公开
    通过综合电子邮件行为分析进行网络检测的系统和方法

    公开(公告)号:US20130247192A1

    公开(公告)日:2013-09-19

    申请号:US13037988

    申请日:2011-03-01

    IPC分类号: G06F21/00

    CPC分类号: H04L63/1425 H04L2463/144

    摘要: A method is provided in one example embodiment that includes receiving message sender traits associated with email senders, and receiving a dataset of known malware identifiers and network addresses from a spamtrap. The message sender traits may include behavior features and/or content resemblance factors in various embodiments. The method further includes classifying the email senders as malicious or benign based on the behavior features, and further classifying the malicious senders by malware identifiers based on similarity of content resemblance factors and the dataset of known malware identifiers and network addresses. In certain specific embodiments, a supervised classifier, such as a support vector machine, may be used to classify the malicious senders by malware identifiers.

    摘要翻译: 在一个示例实施例中提供了一种方法,其包括接收与电子邮件发送者相关联的消息发送者特征,以及从垃圾邮件捕获接收已知恶意软件标识符和网络地址的数据集。 消息发送者特征可以包括各种实施例中的行为特征和/或内容相似性因素。 该方法还包括基于行为特征将电子邮件发送者分类为恶意或良性,并且基于内容相似性因素与已知恶意软件标识符和网络地址的数据集的恶意软件标识符进一步对恶意发送者进行分类。 在某些具体实施例中,监督分类器(例如支持向量机)可用于通过恶意软件标识符对恶意发送者进行分类。