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    Malicious software detection in a computing system
    2.
    发明授权
    Malicious software detection in a computing system 有权
    计算系统中的恶意软件检测

    公开(公告)号：US09043894B1

    公开(公告)日：2015-05-26

    申请号：US14616080

    申请日：2015-02-06

    Applicant: Palantir Technologies Inc.

    Inventor： Drew Dennison ,  Geoff Stowe ,  Adam Anderson

    IPC: H04L29/06

    CPC classification number: H04L63/145 ,  G06F17/30867 ,  G06F21/552 ,  G06F21/566 ,  G06F2221/033 ,  G06N99/005 ,  H04L63/1408 ,  H04L63/1425

    Abstract: A computer system identifies malicious Uniform Resource Locator (URL) data items from a plurality of unscreened data items that have not been previously identified as associated with malicious URLs. The system can execute a number of pre-filters to identify a subset of URLs in the plurality of data items that are likely to be malicious. A scoring processor can score the subset of URLs based on a plurality of input vectors using a suitable machine learning model. Optionally, the system can execute one or more post-filters on the score data to identify data items of interest. Such data items can be fed back into the system to improve machine learning or can be used to provide a notification that a particular resource within a local network is infected with malicious software.

    Abstract translation: 计算机系统从未被先前识别为与恶意URL相关联的多个未被筛选的数据项中识别恶意统一资源定位符（URL）数据项。 系统可以执行多个预过滤器以识别可能是恶意的多个数据项中的URL的子集。 评分处理器可以使用合适的机器学习模型基于多个输入向量来评分URL的子集。 可选地，系统可以对得分数据执行一个或多个后置过滤器以识别感兴趣的数据项。 这样的数据项目可以反馈到系统中以改进机器学习，或者可以用于提供本地网络中的特定资源被恶意软件感染的通知。

    ANOMALOUS NETWORK MONITORING, USER BEHAVIOR DETECTION AND DATABASE SYSTEM
    3.
    发明申请
    ANOMALOUS NETWORK MONITORING, USER BEHAVIOR DETECTION AND DATABASE SYSTEM 审中-公开

    公开(公告)号：US20190081971A1

    公开(公告)日：2019-03-14

    申请号：US16186801

    申请日：2018-11-12

    Applicant: Palantir Technologies Inc.

    Inventor： Samuel Jones ,  Timothy Yousaf ,  Drew Dennison ,  Vivek Lakshmanan ,  Joseph Staehle ,  Samuel Kremin ,  Maxim Kesin ,  Taylor Heroux

    IPC: H04L29/06 ,  G06F21/55 ,  H04L29/08

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for network monitoring, user account compromise determination, and user behavior database system. The system monitors network actions of user accounts including user account access across multitudes of network accessible systems, determines user account transitions, and determines different types of high-risk user behavior indicative of compromise. Network actions can be obtained from generated information by the network accessible systems, and correlated across additional data sets including contextual ones. User interfaces are generated describing network actions of user accounts, and are configured for user interaction, which cause generation of updated user interfaces and access to electronic data sources to determine information relevant to the user interaction.

    Malicious software detection in a computing system
    4.
    发明授权
    Malicious software detection in a computing system 有权

    公开(公告)号：US10135863B2

    公开(公告)日：2018-11-20

    申请号：US15378567

    申请日：2016-12-14

    Applicant: Palantir Technologies Inc.

    Inventor： Drew Dennison ,  Geoff Stowe ,  Adam Anderson

    IPC: G06F11/00 ,  G06F12/14 ,  G06F12/16 ,  G08B23/00 ,  H04L29/06 ,  G06N99/00 ,  G06F17/30

    Abstract: A computer system identifies malicious Uniform Resource Locator (URL) data items from a plurality of unscreened data items that have not been previously identified as associated with malicious URLs. The system can execute a number of pre-filters to identify a subset of URLs in the plurality of data items that are likely to be malicious. A scoring processor can score the subset of URLs based on a plurality of input vectors using a suitable machine learning model. Optionally, the system can execute one or more post-filters on the score data to identify data items of interest. Such data items can be fed back into the system to improve machine learning or can be used to provide a notification that a particular resource within a local network is infected with malicious software.

    Malicious software detection in a computing system
    6.
    发明授权
    Malicious software detection in a computing system 有权

    公开(公告)号：US11496509B2

    公开(公告)日：2022-11-08

    申请号：US16935045

    申请日：2020-07-21

    Applicant: Palantir Technologies Inc.

    Inventor： Drew Dennison ,  Geoff Stowe ,  Adam Anderson

    IPC: H04L29/06 ,  H04L9/40 ,  G06F21/56 ,  G06N20/00 ,  G06F21/55

    Abstract: A computer system identifies malicious Uniform Resource Locator (URL) data items from a plurality of unscreened data items that have not been previously identified as associated with malicious URLs. The system can execute a number of pre-filters to identify a subset of URLs in the plurality of data items that are likely to be malicious. A scoring processor can score the subset of URLs based on a plurality of input vectors using a suitable machine learning model. Optionally, the system can execute one or more post-filters on the score data to identify data items of interest. Such data items can be fed back into the system to improve machine learning or can be used to provide a notification that a particular resource within a local network is infected with malicious software.

    Malicious software detection in a computing system
    7.
    发明授权
    Malicious software detection in a computing system 有权

    公开(公告)号：US10728277B2

    公开(公告)日：2020-07-28

    申请号：US16148241

    申请日：2018-10-01

    Applicant: Palantir Technologies Inc.

    Inventor： Drew Dennison ,  Geoff Stowe ,  Adam Anderson

    IPC: H04L29/06 ,  G06F21/56 ,  G06F21/55

    Abstract: A computer system identifies malicious Uniform Resource Locator (URL) data items from a plurality of unscreened data items that have not been previously identified as associated with malicious URLs. The system can execute a number of pre-filters to identify a subset of URLs in the plurality of data items that are likely to be malicious. A scoring processor can score the subset of URLs based on a plurality of input vectors using a suitable machine learning model. Optionally, the system can execute one or more post-filters on the score data to identify data items of interest. Such data items can be fed back into the system to improve machine learning or can be used to provide a notification that a particular resource within a local network is infected with malicious software.

    MALICIOUS SOFTWARE DETECTION IN A COMPUTING SYSTEM
    8.
    发明申请
    MALICIOUS SOFTWARE DETECTION IN A COMPUTING SYSTEM 审中-公开

    公开(公告)号：US20190036945A1

    公开(公告)日：2019-01-31

    申请号：US16148241

    申请日：2018-10-01

    Applicant: Palantir Technologies Inc.

    Inventor： Drew Dennison ,  Geoff Stowe ,  Adam Anderson

    IPC: H04L29/06 ,  G06N99/00 ,  G06F17/30 ,  G06F21/56 ,  G06F21/55

    Abstract: A computer system identifies malicious Uniform Resource Locator (URL) data items from a plurality of unscreened data items that have not been previously identified as associated with malicious URLs. The system can execute a number of pre-filters to identify a subset of URLs in the plurality of data items that are likely to be malicious. A scoring processor can score the subset of URLs based on a plurality of input vectors using a suitable machine learning model. Optionally, the system can execute one or more post-filters on the score data to identify data items of interest. Such data items can be fed back into the system to improve machine learning or can be used to provide a notification that a particular resource within a local network is infected with malicious software.

    Anomalous network monitoring, user behavior detection and database system
    10.
    发明授权
    Anomalous network monitoring, user behavior detection and database system 有权

    公开(公告)号：US11470102B2

    公开(公告)日：2022-10-11

    申请号：US16186801

    申请日：2018-11-12

    Applicant: Palantir Technologies Inc.

    Inventor： Samuel Jones ,  Timothy Yousaf ,  Drew Dennison ,  Vivek Lakshmanan ,  Joseph Staehle ,  Samuel Kremin ,  Maxim Kesin ,  Taylor Heroux

    IPC: H04L9/40 ,  G06F21/55 ,  H04L67/306

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for network monitoring, user account compromise determination, and user behavior database system. The system monitors network actions of user accounts including user account access across multitudes of network accessible systems, determines user account transitions, and determines different types of high-risk user behavior indicative of compromise. Network actions can be obtained from generated information by the network accessible systems, and correlated across additional data sets including contextual ones. User interfaces are generated describing network actions of user accounts, and are configured for user interaction, which cause generation of updated user interfaces and access to electronic data sources to determine information relevant to the user interaction.

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