Login and authentication methods and systems

    公开(公告)号:US11831648B1

    公开(公告)日:2023-11-28

    申请号:US18079211

    申请日:2022-12-12

    Abstract: Systems, methods, and apparatuses for authenticating requests to access one or more accounts over a network using authenticity evaluations of two or more automated decision engines are discussed. A login request for access to a user account may be submitted to multiple decision engines that each apply different rulesets for authenticating the login request, and output an evaluation of the authenticity of the login request. Based on evaluations from multiple automated decision engines, the login request may be allowed to proceed to validation of user identity and, if user identity is validated, access to the user account may be authorized. Based on the evaluations, the login attempt may also be rejected. One or more additional challenge question may be returned to the computing device used to request account access, and the login request allowed to proceed to validation of identity if the response to the challenge question is deemed acceptable.

    CUMULATIVE SUM MODEL FOR IP DENY LISTS
    4.
    发明公开

    公开(公告)号:US20230353537A1

    公开(公告)日:2023-11-02

    申请号:US18332303

    申请日:2023-06-09

    CPC classification number: H04L63/0236 H04L63/083 H04L63/1416 H04L63/20

    Abstract: In an example aspect, a method includes receiving a plurality of login attempts from a network address over a length of time, querying log data to determine, for the network address, an average number of login failures of the plurality of login attempts over the length of time, calculating a failure rate metric based on the average number of login failures, determining that the failure rate metric exceeds a reference number of login failures for the length of time, the reference number of login failures based on a historical average number of login failures for the length of time, and based in part on the determining, adding the network address to a system deny list.

    Systems and methods for using machine learning for geographic analysis of access attempts

    公开(公告)号:US11356472B1

    公开(公告)日:2022-06-07

    申请号:US16716346

    申请日:2019-12-16

    Abstract: Disclosed herein are systems and methods for using machine learning for geographic analysis of access attempts. In an embodiment, a trained machine-learning model classifies source IP addresses of login attempts to a system as either blacklisted or allowed based on a set of aggregated features that correspond to login attempts to the system from the source IP addresses. The set of aggregated features includes, in association with each respective source IP address, a geographical login-attempt failure rate of login attempts to the system from each of one or more geographical areas that each correspond to the respective source IP address. Source IP addresses that are classified by the machine-learning model as blacklisted are added to a system blacklist, such that the system will disallow login attempts from such source IP addresses.

    System and method for graduated deny list

    公开(公告)号:US11855989B1

    公开(公告)日:2023-12-26

    申请号:US17303777

    申请日:2021-06-07

    CPC classification number: H04L63/101

    Abstract: A method may include receiving a first classification of a network address associated with a login attempt as an AVA, and in response, generating a first random number, selecting a first blocking length of time from a plurality of blocking lengths of time, calculating a first deny list duration based on summing the first random number and the first blocking length of time, and adding the network address to a deny list for the first deny list duration, and adding the network address to a parole list for a parole duration, receiving a second classification of the address as an AVA during the duration; and in response selecting a second blocking length of time from a plurality of blocking lengths, calculating a second deny list duration based on summing the second random number and the second blocking length and adding the address to the deny list for the second duration.

    Cumulative sum model for IP deny lists

    公开(公告)号:US11722459B1

    公开(公告)日:2023-08-08

    申请号:US17303776

    申请日:2021-06-07

    CPC classification number: H04L63/0236 H04L63/083 H04L63/1416 H04L63/20

    Abstract: In an example aspect, a method includes receiving a plurality of login attempts from a network address over a length of time, querying log data to determine, for the network address, an average number of login failures of the plurality of login attempts over the length of time, calculating a failure rate metric based on the average number of login failures, determining that the failure rate metric exceeds a reference number of login failures for the length of time, the reference number of login failures based on a historical average number of login failures for the length of time, and based in part on the determining, adding the network address to a system deny list.

    Login and authentication methods and systems

    公开(公告)号:US10965683B1

    公开(公告)日:2021-03-30

    申请号:US16207807

    申请日:2018-12-03

    Abstract: Systems, methods, and apparatuses for authenticating requests to access one or more accounts over a network using authenticity evaluations of two or more automated decision engines are discussed. A login request for access to a user account may be submitted to multiple decision engines that each apply different rulesets for authenticating the login request, and output an evaluation of the authenticity of the login request. Based on evaluations from multiple automated decision engines, the login request may be allowed to proceed to validation of user identity and, if user identity is validated, access to the user account may be authorized. Based on the evaluations, the login attempt may also be rejected. One or more additional challenge question may be returned to the computing device used to request account access, and the login request allowed to proceed to validation of identity if the response to the challenge question is deemed acceptable.

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