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    PLUGGABLE FAULT DETECTION TESTS FOR DATA PIPELINES
    11.
    发明申请
    PLUGGABLE FAULT DETECTION TESTS FOR DATA PIPELINES 审中-公开

    公开(公告)号：US20200012593A1

    公开(公告)日：2020-01-09

    申请号：US16572404

    申请日：2019-09-16

    Applicant: Palantir Technologies, Inc.

    Inventor： Peter Maag ,  Jacob Albertson ,  Jared Newman ,  Matthew Lynch ,  Maciej Albin ,  Viktor Nordling

    IPC: G06F11/36 ,  G06F11/07

    Abstract: Discussed herein are embodiments of methods and systems which allow engineers or administrators to create modular plugins which represent the logic for various fault detection tests that can be performed on data pipelines and shared among different software deployments. In some cases, the modular plugins each define a particular test to be executed against data received from the pipeline in addition to one or more configuration points. The configuration points represent configurable arguments, such as variables and/or functions, referenced by the instructions which implement the tests and that can be set according to the specific operation environment of the monitored pipeline.

    Pluggable fault detection tests for data pipelines
    12.
    发明授权
    Pluggable fault detection tests for data pipelines 有权

    公开(公告)号：US10417120B2

    公开(公告)日：2019-09-17

    申请号：US15671423

    申请日：2017-08-08

    Applicant: Palantir Technologies, Inc.

    Inventor： Peter Maag ,  Jacob Albertson ,  Jared Newman ,  Matthew Lynch ,  Maciej Albin ,  Viktor Nordling

    IPC: G06F11/36 ,  G06F11/07

    Abstract: Discussed herein are embodiments of methods and systems which allow engineers or administrators to create modular plugins which represent the logic for various fault detection tests that can be performed on data pipelines and shared among different software deployments. In some cases, the modular plugins each define a particular test to be executed against data received from the pipeline in addition to one or more configuration points. The configuration points represent configurable arguments, such as variables and/or functions, referenced by the instructions which implement the tests and that can be set according to the specific operation environment of the monitored pipeline.

    PLUGGABLE FAULT DETECTION TESTS FOR DATA PIPELINES
    15.
    发明申请
    PLUGGABLE FAULT DETECTION TESTS FOR DATA PIPELINES 有权

    公开(公告)号：US20170220403A1

    公开(公告)日：2017-08-03

    申请号：US14877229

    申请日：2015-10-07

    Applicant: Palantir Technologies, Inc.

    Inventor： Peter Maag ,  Jacob Albertson ,  Jared Newman ,  Matthew Lynch ,  Maciej Albin ,  Viktor Nordling

    IPC: G06F11/07

    CPC classification number: G06F11/3692 ,  G06F11/0751 ,  G06F11/0775

    Abstract: Discussed herein are embodiments of methods and systems which allow engineers or administrators to create modular plugins which represent the logic for various fault detection tests that can be performed on data pipelines and shared among different software deployments. In some cases, the modular plugins each define a particular test to be executed against data received from the pipeline in addition to one or more configuration points. The configuration points represent configurable arguments, such as variables and/or functions, referenced by the instructions which implement the tests and that can be set according to the specific operation environment of the monitored pipeline.

    Security sharing system
    16.
    发明授权
    Security sharing system 有权
    安全共享系统

    公开(公告)号：US09009827B1

    公开(公告)日：2015-04-14

    申请号：US14280490

    申请日：2014-05-16

    Applicant: Palantir Technologies Inc.

    Inventor： Jacob Albertson ,  Melody Hildebrandt ,  Harkirat Singh ,  Shyam Sankar ,  Rick Ducott ,  Peter Maag ,  Marissa Kimball

    IPC: H04L29/06

    CPC classification number: H04L63/20 ,  G06F21/50 ,  G06F21/55 ,  H04L63/14 ,  H04L63/1441

    Abstract: Systems and techniques for sharing security data are described herein. Security rules and/or attack data may be automatically shared, investigated, enabled, and/or used by entities. A security rule may be enabled on different entities comprising different computing systems to combat similar security threats and/or attacks. Security rules and/or attack data may be modified to redact sensitive information and/or configured through access controls for sharing.

    Abstract translation: 本文描述了用于共享安全数据的系统和技术。 实体可以自动共享，调查，启用和/或使用安全规则和/或攻击数据。 可以在包括不同计算系统的不同实体上启用安全规则以对抗类似的安全威胁和/或攻击。 可以修改安全规则和/或攻击数据以修正敏感信息和/或通过访问控制进行配置以进行共享。

    Enhanced machine learning refinement and alert generation system
    17.
    发明授权
    Enhanced machine learning refinement and alert generation system 有权

    公开(公告)号：US12261872B2

    公开(公告)日：2025-03-25

    申请号：US17445172

    申请日：2021-08-16

    Applicant: Palantir Technologies Inc.

    Inventor： Corentin Petit ,  Jacob Albertson ,  Marissa Kimball ,  Paul Baseotto ,  Pierre Cholet ,  Timur Iskhakov ,  Victoria Galano

    IPC: H04L9/40 ,  G06F9/451 ,  G06N20/00

    Abstract: Systems and methods are provided for enhanced machine learning refinement and alert generation. An example method includes accessing datasets storing customer information reflecting transactions of customers. Individual risk scores are generated for the customers based on the customer information. Generating the risk score includes providing identified occurrences of scenario definitions and customer information as input to one or more machine learning models, the scenario definitions identifying occurrences of specific information reflected in the datasets, with the machine learning models assign respective risk scores to the customers. An interactive user interface is presented. The interactive user presents summary information associated with the risk scores, with the interactive user interfaces enabling an investigation into whether a particular customer is exhibiting risky behavior, responds to user input indicating feedback usable to update the one or more machine learning models or scenario definitions, with the feedback triggering updating of the machine learning models.

    Joined and coordinated detection, handling, and prevention of cyberattacks
    19.
    发明授权
    Joined and coordinated detection, handling, and prevention of cyberattacks 有权

    公开(公告)号：US11587177B2

    公开(公告)日：2023-02-21

    申请号：US14919506

    申请日：2015-10-21

    Applicant: Palantir Technologies Inc.

    Inventor： Shyam Sankar ,  Jacob Albertson ,  Melody Hildebrandt ,  Harkirat Singh ,  Rick Ducott ,  Peter Maag ,  Marissa Kimball

    IPC: H04L29/06 ,  G06Q40/08 ,  H04L9/40

    Abstract: Methods, devices, systems and computer program products enable monitoring and responding to cyber security attacks. One such system relates to a consortium of monitoring companies and an infrastructure including one or more central monitoring stations or local handling stations for a monitoring company are provided. A central monitoring station of a monitoring company detects a cyberattack that has been launched against a client computer system, and requests a local station to respond to the cyberattack via onsite visits or requests additional resources from other monitoring companies through the consortium system. The central monitoring station also sends to the consortium system updates on a cyberattack that is detected or mitigated by a central monitoring station or local handling station of the monitoring company. The monitoring consortium enables stronger capabilities than any individual monitoring company can offer by the combination and coordination of the efforts and resources of the members.

    Systems and user interfaces for holistic, data-driven investigation of bad actor behavior based on clustering and scoring of related data
    20.
    发明授权
    Systems and user interfaces for holistic, data-driven investigation of bad actor behavior based on clustering and scoring of related data 有权

    公开(公告)号：US11501369B2

    公开(公告)日：2022-11-15

    申请号：US16264983

    申请日：2019-02-01

    Applicant: Palantir Technologies Inc.

    Inventor： Sean Hunter ,  Aditya Kumar ,  Jacob Albertson

    IPC: G06Q40/00 ,  G06Q40/04 ,  G06F3/0482 ,  G06F16/28 ,  G06F16/2457

    Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria, rules, indicators, or scenarios so as to generate scores, reports, alerts, or conclusions that the analyst may quickly and efficiently use to evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a risky trading investigation.

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