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公开(公告)号：US12032520B2
公开(公告)日：2024-07-09
申请号：US18149787
申请日：2023-01-04
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Paul Ireifej , Mohammad Omar Khalid Mirza , Prince Paulraj , Heather Wighton , Christopher Kim , Stephen Grandinetti , Mger Babayan
CPC classification number: G06F16/168 , G06F16/256 , G06F16/258
Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.
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公开(公告)号：US11902308B2
公开(公告)日：2024-02-13
申请号：US17338646
申请日：2021-06-03
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Edmond Abrahamian , Maisam Shahid Wasti , Andrew Campbell , Ana Armenta , Prince Paulraj
IPC: H04L29/06 , G06N20/00 , G06F40/134 , H04L9/40
CPC classification number: H04L63/1425 , G06F40/134 , G06N20/00 , H04L63/08 , H04L63/10 , H04L63/1491 , H04L2463/082
Abstract: A method for detecting threat pathways using sequence graphs includes constructing a sequence graph from a set of data containing information about activities in a telecommunications service provider network, where the sequence graph represents a subset of the activities that occurs as a sequence, providing an embedding of the sequence graph as input to a machine learning model, wherein the machine learning model has been trained to detect when an input embedding of a sequence graph is likely to indicate a threat activity, determining, based on an output of the machine learning model, whether the subset of the activities is indicative of the threat activity, and initiating a remedial action to mitigate the threat activity.
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公开(公告)号：US20230401512A1
公开(公告)日：2023-12-14
申请号：US17839260
申请日：2022-06-13
Applicant: AT&T INTELLECTUAL PROPERTY I, L.P.
Inventor： Brandon Bolong Lee , Andrew Campbell , Ana Armenta , Prince Paulraj
CPC classification number: G06Q10/0637 , G06N20/00 , G06N5/025
Abstract: Mitigation of temporal generalization losses a target machine learning model is disclosed. Mitigation can be based on identifying, removing, modifying, transforming, etc., features, explanatory variables, models, etc., that can have an unstable relationship with a target outcome over time. Implementation of a more stable representation can be initiated. Temporal stability measures (TSMs) for one or more model feature(s) can be determined based on one or more variable performance metrics (VPMs). A group of one or more VPMs can be selected based on features of a model in either a development or production environment. Model feature modification can be recommended based on a TSM, which can prune a feature, transform a feature, add a feature, etc. Temporal stability information can be presented, e.g., via a dashboard-type user interface. Models can be updated based on mutations of a model comprising a feature modification(s), including competitive champion/challenger model updating.
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公开(公告)号：US20230252014A1
公开(公告)日：2023-08-10
申请号：US18298353
申请日：2023-04-10
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Prince Paulraj , Shilpi Harpavat , Weiping Liu , Shreyash Taywade , Arjun Coimbatore Nagarasan , Yukun Zeng , Prabhu Gururaj
IPC: G06F16/22 , G06N20/00 , G06Q40/02 , G06Q30/0201 , G06Q30/016 , G06N5/04
CPC classification number: G06F16/2272 , G06N20/00 , G06Q40/02 , G06Q30/0201 , G06Q30/016 , G06N5/04
Abstract: In another example, a device includes a processor and a computer-readable medium storing instructions which, when executed by the processor, cause the processor to perform operations. The operations include acquiring a plurality of data items from a plurality of data sources, wherein the at least two data sources data sources of the plurality of data sources are maintained by different entities, normalizing attributes of the plurality of data items, using a first machine learning technique, matching at least two data items of the plurality of data items to form a grouping, wherein the matching is based on similarities observed in the attributes of the at least two data items subsequent to the normalizing, and creating a single profile for an individual associated with the at least two data items, based on the grouping, wherein the single profile consolidates the attributes of the at least two data items.
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公开(公告)号：US20230214711A1
公开(公告)日：2023-07-06
申请号：US17646708
申请日：2021-12-31
Applicant: AT&T INTELLECTUAL PROPERTY I, L.P.
Inventor： Prince Paulraj , Christopher Kim , Eric Zavesky , Prathiba Sugumaran , James Pratt , Cuong Vo
Abstract: A method performed by a processing system including at least one processor includes detecting that new data has been added to a repository of reusable machine learning models and machine learning model features, applying data protection to the new data, testing the new data for bias, merging at least a portion of the new data with stored data from the repository to build a new machine learning model in which the data protection is preserved, and publishing the new machine learning model in the repository.
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Patent Agency Ranking
公开(公告)号：US20230142895A1
公开(公告)日：2023-05-11
申请号：US17520144
申请日：2021-11-05
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Andrew Campbell , Shreyash Taywade , Prince Paulraj
CPC classification number: G06F9/505 , G06F11/3433 , G06F11/0709
Abstract: Determining a recommendation to convert a block of code into a serverless function based on analysis of code in execution in a cloud computing environment is disclosed. The block of code can be correlated to high levels of computing resource utilization that can inflate a cost of deploying a corresponding application in the cloud computing environment by prophylactically increasing an amount of provisioned computing resources to accommodate the high-utilization of the block of code. Converting the block of code into a serverless function can reduce the cost via offloading the functionality from the code into a function call supported by the cloud computing environment in an as-needed capacity, thereby reducing the amount of prophylactically provisioned computing resources. The recommendation can occur continuously in a production environment and cot-to-utilization information can render to facilitate identification of code block conversion targets.
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公开(公告)号：US20220329328A1
公开(公告)日：2022-10-13
申请号：US17225784
申请日：2021-04-08
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Prince Paulraj , Ana Armenta , Lauren Savage
Abstract: A processing system may determine a plurality of input features of a first machine learning model that is deployed in a telecommunication network for a prediction task associated with an operation of the telecommunication network and apply a time series forecast model to a historical data set of a first data source associated with at least one of the plurality of input features to generate a forecast upper bound of a first characteristic of the first data source for a first time period and a forecast lower bound of the first characteristic of the first data source for the first time period. The processing system may then detect that the first characteristic exceeds one of the forecast upper bound or the forecast lower bound during the first time period and generate an alert that an output of the first machine learning model may be faulty, in response to the detecting.
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公开(公告)号：US12192400B2
公开(公告)日：2025-01-07
申请号：US17566905
申请日：2021-12-31
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Surya Murali , Edmond J. Abrahamian , Ana Armenta , Prince Paulraj , Elijah Hall
Abstract: A processing system may maintain a relationship graph that includes nodes and edges representing phone numbers and device identifiers having associations with the phone numbers. The processing system may obtain an identification of a first phone number or a first device identifier for a fraud evaluation and extract features from the relationship graph associated with at least one of the first phone number or the first device identifier. The plurality of features may include one or more device identifiers associated with the first phone number, or one or more phone numbers associated with the first device identifier. The processing system may then apply the features to a prediction model that is implemented by the processing system and that is configured to output a fraud risk value of the first phone number or the first device identifier and implement at least one remedial action in response to the fraud risk value.
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29.发明公开公开(公告)号：US20240171558A1
公开(公告)日：2024-05-23
申请号：US17989284
申请日：2022-11-17
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Antoine Diffloth , Prince Paulraj , James Pratt
CPC classification number: H04L63/08 , G06F21/316 , H04L2463/082
Abstract: A processing system including at least one processor may obtain a first input data set associated with a telephone number from a first service provider that implements a multi-factor authentication process for permitting an access to a service of the first service provider and may apply at least the first input data set to a machine learning model implemented by the processing system to obtain a risk score associated with the telephone number for a subscriber identity module swap of a subscriber identity module, where the machine learning model is trained to generate the risk score associated with the telephone number in accordance with at least the first input data set. The processing system may then perform at least one remedial action associated with the telephone number and the subscriber identity module, in response to the risk score.
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公开(公告)号：US11979521B2
公开(公告)日：2024-05-07
申请号：US17321279
申请日：2021-05-14
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Ryan Steckel , Ana Armenta , Prince Paulraj , Chih Chien Huang
CPC classification number: H04M7/0078 , H04L51/21 , H04M3/22 , G06Q20/4016
Abstract: Data stream based event sequence anomaly detection for mobility customer fraud analysis is presented herein. A system obtains a sequence of events comprising respective modalities of communication that correspond to a subscriber identity associated with a communication service—the sequence of events having occurred within a defined period. Based on defined classifiers representing respective fraudulent sequences of events, the system determines, via a group of machine learning models corresponding to respective machine learning processes, whether the sequence of events satisfies a defined condition with respect to likelihood of representing a fraudulent sequence of events of the respective fraudulent sequences of events. In response to the sequence of events being determined to satisfy the defined condition, the system sends, via a user interface of the system, a notification indicating that the sequence of events has been determined to represent the fraudulent sequence of events.
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