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    BIAS SCORING OF MACHINE LEARNING PROJECT DATA
    31.
    发明公开
    BIAS SCORING OF MACHINE LEARNING PROJECT DATA 审中-公开

    公开(公告)号：US20240256926A1

    公开(公告)日：2024-08-01

    申请号：US18632608

    申请日：2024-04-11

    Applicant: AT&T Intellectual Property I, L.P.

    Inventor： Emily Dodwell ,  Balachander Krishnamurthy ,  Rajat Malik ,  Ritwik Mitra

    IPC: G06N5/04 ,  G06F16/28 ,  G06N20/00

    CPC classification number: G06N5/04 ,  G06F16/285 ,  G06N20/00

    Abstract: Aspects of the subject disclosure may include, for example, system and apparatus that enable operations that may include receiving, by a processing system, project data defining a proposed machine learning (ML) project of an entity and storing the project data in a project database with other project data for other projects. The operations may further include extracting extracted features of the proposed project and, based on the extracted features, determining a clustering assignment for the proposed project. Determining the clustering assignment may comprise comparing information about the proposed project including the extracted features with information about the other projects and assigning the proposed project to a cluster including one or more projects having similar bias characteristics as the proposed project. The operations may further include determining a risk of potential bias for the proposed project and, based on the risk of bias, recommending a corrective action to reduce the risk of bias. Machine learning models may be used for project clustering and bias score determination and may be readily updated as new ML projects are evaluated. Other embodiments are disclosed.

    INCREASING INCLUSIVITY IN MACHINE LEARNING OUTPUTS
    33.
    发明申请
    INCREASING INCLUSIVITY IN MACHINE LEARNING OUTPUTS 有权

    公开(公告)号：US20220327419A1

    公开(公告)日：2022-10-13

    申请号：US17227311

    申请日：2021-04-10

    Applicant: AT&T Intellectual Property I, L.P.

    Inventor： Cheryl Brooks ,  Balachander Krishnamurthy ,  Subhabrata Majumdar

    IPC: G06N20/00 ,  G06F16/901

    Abstract: A method includes constructing an information graph based on a set of training data provided to a machine learning algorithm, identifying an area of the information graph in which to increase an inclusion of the information graph, wherein the inclusion comprises a consideration of a population that is underrepresented in the information graph, collecting, from an auxiliary data source, auxiliary data about the population for use in increasing the inclusion of the information graph, utilizing the auxiliary data to increase the inclusion of the information graph, to generate an updated information graph, using the updated information graph to generate a test output that incorporates information from the auxiliary data, generating, when the test output satisfies an inclusion criterion, a runtime output using the updated information graph, receiving user feedback regarding the runtime output, and determining, in response to the user feedback, whether to further increase inclusion of the runtime output.

    SOFTWARE DEFINED PROBER
    35.
    发明申请
    SOFTWARE DEFINED PROBER 审中-公开

    公开(公告)号：US20200021536A1

    公开(公告)日：2020-01-16

    申请号：US16031502

    申请日：2018-07-10

    Applicant: AT&T INTELLECTUAL PROPERTY I, L.P.

    Inventor： Yaron Kanza ,  Balachander Krishnamurthy ,  Sivaramakrishnan Ramanathan

    IPC: H04L12/927 ,  H04L12/26 ,  H04L12/721 ,  H04L12/24 ,  H04L12/841 ,  H04L12/911

    Abstract: In one embodiment, a method includes determining, by one or more processors, a weight of a link between a first node and a second node of a network, wherein the weight is proportional to a probability value of forwarding a probe packet from the first node to the second node of the network. The method also includes adjusting, by the processors, the weight of the link between the first node and the second node using binary exponential backoff. The method further includes determining, by the processors, to forward the probe packet to the second node of the network based on the adjusted weight of the link and one or more field values of the probe packet.

    Method and Apparatus for Identifying Phishing Websites in Network Traffic Using Generated Regular Expressions
    38.
    发明申请
    Method and Apparatus for Identifying Phishing Websites in Network Traffic Using Generated Regular Expressions 有权
    使用生成的正则表达式识别网络流量中的网络钓鱼网站的方法和装置

    公开(公告)号：US20130031630A1

    公开(公告)日：2013-01-31

    申请号：US13644055

    申请日：2012-10-03

    Applicant: AT&T INTELLECTUAL PROPERTY I, L.P.

    Inventor： Balachander Krishnamurthy ,  Oliver Spatscheck ,  Jacobus Van Der Merwe ,  Anirudh Ramachandran

    IPC: G06F21/00

    CPC classification number: G06F21/552 ,  G06F21/566 ,  H04L63/10 ,  H04L63/1441 ,  H04L63/1483

    Abstract: According to an aspect of this invention, a method to detect phishing URLs involves: creating a whitelist of URLs using a first regular expression; creating a blacklist of URLs using a second regular expression; comparing a URL to the whitelist; and if the URL is not on the whitelist, comparing the URL to the blacklist. False negatives and positives may be avoided by classifying Internet domain names for the target organization as “legitimate”. This classification leaves a filtered set of URLs with unknown domain names which may be more closely examined to detect a potential phishing URL. Valid domain names may be classified without end-user participation.

    Abstract translation: 根据本发明的一个方面，一种检测网络钓鱼URL的方法包括：使用第一正则表达式创建URL的白名单; 使用第二个正则表达式创建URL黑名单; 将网址与白名单进行比较; 如果该网址不在白名单中，请将该URL与黑名单进行比较。 通过将目标组织的互联网域名分类为合法，可以避免虚假的否定和积极性。 此类别会留下一组经过筛选的未知域名的URL，可以更仔细地检查以检测潜在的网络钓鱼URL。 有效的域名可能没有最终用户的参与分类。

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