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    IDENTIFYING A COMMON ACTION FLOW
    72.
    发明申请
    IDENTIFYING A COMMON ACTION FLOW 审中-公开

    公开(公告)号：US20170315822A1

    公开(公告)日：2017-11-02

    申请号：US15655726

    申请日：2017-07-20

    Applicant: EntIT Software LLC

    Inventor： Igor NOR ,  Eyal KENIGSBERG ,  Ola GALKIN

    IPC: G06F9/44 ,  G06F11/30 ,  G06F11/34

    CPC classification number: G06F9/451 ,  G06F11/30 ,  G06F11/3003 ,  G06F11/3438 ,  G06F11/3452 ,  G06F2201/81 ,  G06F2201/865 ,  G06F2201/88

    Abstract: A common action flow for an application is identified by processing session data maintained for a plurality of users to identify a plurality of action flows. Each action flow represents a series of actions taken by one of the users navigating the application's user interface during a session. A data structure is generated from the plurality of action flows. That data structure is indicative of a plurality of candidate sub-flows. The data structure is analyzed to identify a selected one of the candidate sub-flows repeated in multiple ones of the plurality of action flows. That identified sub-flow is the common action flow. Data representative of the identified common action flow can then be communicated.

    Machine learning model-based dynamic prediction of estimated query execution time taking into account other, concurrently executing queries
    73.
    发明授权
    Machine learning model-based dynamic prediction of estimated query execution time taking into account other, concurrently executing queries 有权

    公开(公告)号：US11971793B2

    公开(公告)日：2024-04-30

    申请号：US16292990

    申请日：2019-03-05

    Applicant: ENTIT Software LLC

    Inventor： Yuanzhe Bei ,  Zhihao Zheng

    IPC: G06F16/00 ,  G06F7/00 ,  G06F11/30 ,  G06F16/2453 ,  G06F16/901

    CPC classification number: G06F11/3006 ,  G06F16/24542 ,  G06F16/9027

    Abstract: Current physical resources utilization of a computing system as a whole is monitored. The number of queries concurrently being executed against a database by a database management system (DBMS) running on a computing system is monitored. A query plan for a received query to be executed against the database is generated. The query plan includes operators; the generation of the query plan includes generation of query-based statistics for the received query on a per-operator basis without consideration of the queries concurrently being executed. An estimated execution time of the received query is dynamically predicted using a machine-learning model based on the query-based statistics generated for the received query on the per-operator basis, the current physical resources utilization of the computing system, and the number of queries concurrently being executed. The received query is executed against the database based on the dynamically predicted estimated execution time for the received query.

    Source entities of security indicators
    74.
    发明授权
    Source entities of security indicators 有权

    公开(公告)号：US11962609B2

    公开(公告)日：2024-04-16

    申请号：US16076274

    申请日：2016-02-12

    Applicant: ENTIT SOFTWARE LLC

    Inventor： Tomas Sander ,  Brian Frederik Hosea Che Hein ,  Nadav Cohen ,  Ted Ross

    IPC: H04L29/00 ,  H04L9/40

    CPC classification number: H04L63/1433 ,  H04L63/1408 ,  H04L63/20

    Abstract: Examples disclosed herein relate to source entities of security indicators. Some examples disclosed herein enable identifying, in a security information sharing platform, a security indicator that is originated from a source entity where the security indicator comprises an observable. Some examples further enable determining a reliability level of the source entity based on at least one of: security events, sightings of the observable, a first set of user feedback information that is submitted for the security indicator by users of the security information sharing platform, or a second set of user feedback information that is collected from external resources that are external to the security information sharing platform.

    Machine learning-based network device profiling
    76.
    发明授权
    Machine learning-based network device profiling 有权

    公开(公告)号：US11611569B2

    公开(公告)日：2023-03-21

    申请号：US16428422

    申请日：2019-05-31

    Applicant: ENTIT SOFTWARE LLC

    Inventor： Tamir Mitelman ,  Tammy Torbert

    IPC: H04L29/06 ,  H04L9/40 ,  G06K9/62 ,  G06F16/9038 ,  G06N20/20

    Abstract: A method includes applying, by a computer, supervised machine learning to classify a network device that is associated with a security event occurring in a computer system based on data representing features of the network device. The security event is associated with a potential security threat to the computer system, and the classification of the network device by the supervised machine learning is associated with a confidence. The technique includes, in response to the confidence being below a threshold, applying an active machine learning classifier to the data to learn a classification for the data and using the classification learned by the active machine learning classifier to adapt the supervised machine learning to recognize the classification.

    MOBILE DEVICE LOCATOR
    77.
    发明申请
    MOBILE DEVICE LOCATOR 有权

    公开(公告)号：US20220283261A1

    公开(公告)日：2022-09-08

    申请号：US17703474

    申请日：2022-03-24

    Applicant: ENTIT SOFTWARE LLC

    Inventor： Wei LI ,  Jie ZHOU ,  Xiaoqiang WANG

    IPC: G01S5/02 ,  H04W4/029

    Abstract: Examples herein involve estimating a first position of a mobile device based on first communication signals, assigning a first set of particles to a number of respective first sampling locations within a threshold distance of the first position, adjusting the assignment of the first set of particles to second sampling locations based on movement of the mobile device, and estimating a second position of the mobile device based on the second sampling locations.

    System for protecting sensitive data with distributed tokenization
    78.
    发明授权
    System for protecting sensitive data with distributed tokenization 有权

    公开(公告)号：US11423504B2

    公开(公告)日：2022-08-23

    申请号：US14060186

    申请日：2013-10-22

    Applicant: ENTIT SOFTWARE LLC

    Inventor： Terence Spies ,  Richard T. Minner

    IPC: H04L9/06 ,  G06Q99/00 ,  H04L9/08

    Abstract: A token generating organization may include distributed tokenization systems for generating tokens corresponding to sensitive information. Sensitive information may include sensitive numbers such as social security numbers, credit card numbers or other private numbers. A tokenization system may include multiple physically distinct hardware platforms each having a tokenization server and a database. A tokenization server may run portions of a sensitive number through a predetermined number of rounds of a Feistel network. Each round of the Feistel network may include tokenizing portions of the sensitive number using a fractional token table stored an associated database and modifying the tokenized portions by reversibly adding portions of the sensitive number to the tokenized portions. The fractional token table may include partial sensitive numbers and corresponding partial tokens. A sensitive-information-recovery request including the token may be directed to the token generating organization from the token requestor to recover sensitive information.

    Log event cluster analytics management
    79.
    发明授权
    Log event cluster analytics management 有权

    公开(公告)号：US11423053B2

    公开(公告)日：2022-08-23

    申请号：US16071767

    申请日：2016-01-30

    Applicant: ENTIT SOFTWARE LLC

    Inventor： Christopher Byrd

    IPC: G06F16/28 ,  G06F17/40 ,  G06F11/34 ,  G06F16/23

    Abstract: A log event cluster analytics management method may involve storing a first portion of an entire cluster dictionary in a transient memory, storing at least a second portion of the entire cluster dictionary in a persistent database and comparing a new log event message to the first portion of the overall cluster dictionary. In response to not assigning the new log event message to any cluster in the first portion of the entire cluster dictionary in the transient memory, selecting a subset of clusters of the at least second portion of the cluster dictionary in the persistent database, comparing the new log event message to a cluster of the selected subset of clusters and assigning the new log event message to the cluster of the selected subset of clusters based upon the comparison.

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