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    Systems and methods for detecting data exfiltration
    1.
    发明授权
    Systems and methods for detecting data exfiltration 有权

    公开(公告)号：US10915629B2

    公开(公告)日：2021-02-09

    申请号：US15802262

    申请日：2017-11-02

    Applicant: PAYPAL, INC.

    Inventor： Michael Dymshits ,  David Tolpin ,  Eli Strajnik ,  Benjamin Hillel Myara ,  Liron Ben Kimon

    IPC: G06F21/55 ,  G06F21/64 ,  G06F21/60 ,  G06F16/903

    Abstract: Systems and methods for detecting data exfiltration using domain name system (DNS) queries include, in various embodiments, performing operations that include parsing a DNS query to determine whether that DNS query is likely to contain hidden data that is being exfiltrated from a system or network. Statistical methods can be used to analyze the DNS query to determine a likelihood whether each of a plurality of segments of the DNS query are indicative of data exfiltration methods. If one or multiple DNS queries are deemed suspicious based on the analysis, a security action on the DNS query can be performed, including sending an alert and/or blocking the DNS query from being forwarded.

    SYSTEMS AND METHODS FOR DETECTING DATA EXFILTRATION
    2.
    发明申请
    SYSTEMS AND METHODS FOR DETECTING DATA EXFILTRATION 审中-公开

    公开(公告)号：US20190130100A1

    公开(公告)日：2019-05-02

    申请号：US15802262

    申请日：2017-11-02

    Applicant: PAYPAL, INC.

    Inventor： Michael Dymshits ,  David Tolpin ,  Eli Strajnik ,  Benjamin Hillel Myara ,  Liron Ben Kimon

    IPC: G06F21/55 ,  G06F21/60 ,  G06F21/64 ,  G06F17/30

    Abstract: Systems and methods for detecting data exfiltration using domain name system (DNS) queries include, in various embodiments, performing operations that include parsing a DNS query to determine whether that DNS query is likely to contain hidden data that is being exfiltrated from a system or network. Statistical methods can be used to analyze the DNS query to determine a likelihood whether each of a plurality of segments of the DNS query are indicative of data exfiltration methods. If one or multiple DNS queries are deemed suspicious based on the analysis, a security action on the DNS query can be performed, including sending an alert and/or blocking the DNS query from being forwarded.

    PROTECTING AGAINST MALWARE VARIANTS USING RECONSTRUCTED CODE OF MALWARE
    3.
    发明申请
    PROTECTING AGAINST MALWARE VARIANTS USING RECONSTRUCTED CODE OF MALWARE 审中-公开
    使用重新编写的恶意代码保护恶意软件

    公开(公告)号：US20170032120A1

    公开(公告)日：2017-02-02

    申请号：US15230315

    申请日：2016-08-05

    Applicant: PAYPAL, INC.

    Inventor： David Tolpin ,  Shlomi Boutnaru ,  Yuri Shafet

    IPC: G06F21/53 ,  G06F21/56

    CPC classification number: G06F21/53 ,  G06F21/564 ,  G06F21/566 ,  G06F21/567 ,  G06F2221/033 ,  G06F2221/2145 ,  H04L63/1416 ,  H04L63/145

    Abstract: A system for discovering programming variants. The system analyzes system calls from executing a program to generate programming code or executable for a particular OS and/or CPU that would perform the same or similar actions as the program. The code that is generated is then mutated, augmented, and/or changed to create variations of the program which still functions and/or obtains the same objectives as the original code.

    Abstract translation: 用于发现编程变体的系统。 该系统通过执行程序来分析系统调用以产生用于执行与该程序相同或类似动作的特定OS和/或CPU的编程代码或可执行程序。 然后生成的代码被突变，扩充和/或更改，以创建仍然起作用和/或获得与原始代码相同目标的程序的变体。

    Population anomaly detection through deep gaussianization
    4.
    发明授权
    Population anomaly detection through deep gaussianization 有权

    公开(公告)号：US11455517B2

    公开(公告)日：2022-09-27

    申请号：US15794832

    申请日：2017-10-26

    Applicant: PAYPAL, INC.

    Inventor： David Tolpin ,  Amit Batzir ,  Nofar Betzalel ,  Michael Dymshits ,  Benjamin Hillel Myara ,  Liron Ben Kimon

    IPC: G06N3/04 ,  G06N3/08

    Abstract: Anomalies in a data set may be difficult to detect when individual items are not gross outliers from a population average. Disclosed is an anomaly detector that includes neural networks such as an auto-encoder and a discriminator. The auto-encoder and the discriminator may be trained on a training set that does not include anomalies. During training, an auto-encoder generates an internal representation from the training set, and reconstructs the training set from the internal representation. The training continues until data loss in the reconstructed training set is below a configurable threshold. The discriminator may be trained until the internal representation is constrained to a multivariable unit normal. Once trained, the auto-encoder and discriminator identify anomalies in the evaluation set. The identified anomalies in an evaluation set may be linked to transaction, security breach or population trends, but broadly, disclosed techniques can be used to identify anomalies in any suitable population.

    ADVANCED COMPUTER SYSTEM DRIFT DETECTION
    7.
    发明申请
    ADVANCED COMPUTER SYSTEM DRIFT DETECTION 审中-公开

    公开(公告)号：US20190095263A1

    公开(公告)日：2019-03-28

    申请号：US15719279

    申请日：2017-09-28

    Applicant: PayPal, Inc.

    Inventor： Omri Moshe Lahav ,  Raoul Christopher Johnson ,  David Tolpin

    IPC: G06F11/00 ,  G06F11/34 ,  G06F11/30

    CPC classification number: G06F11/004 ,  G06F2201/82 ,  G06F2201/83 ,  G06Q20/405 ,  G07F9/026

    Abstract: Computer system drift can occur when a computer system or a cluster of computer systems deviates from ideal and/or desired behavior. In a server farm, for example, many different machines may be identically configured to work in conjunction with each other to provide an electronic service (serving web pages, processing electronic payment transactions, etc.). Over time, however, one or more of these systems may drift from previous behavior. Early drift detection can be important, especially in large enterprises, to avoiding costly downtime. Changes in a computer's configuration files, network connections, and/or executable processes can indicate ongoing drift, but collecting this information at scale can be difficult. By using certain hashing and min-Hash techniques, however, drift detection can be streamlined and accomplished for large scale operations. Velocity of drift may also be tracked using a decay function.

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