Cox Communications, Inc.

Jignesh B Patel

Kyle Allen Cooper

Marco Antonio Valero

Pavan Chandrashekar

Derek Bantug

Ted Boone

Richard Brown

Pavan Kumar Surapaneni

Ron Lev

Matthew Edwin Carothers

Harry Tang

Kenny Chau

Disclosed are systems and methods for proactive service health detection. An example method may include receiving, by a first computing system, first data associated with a first application at a first time and second data associated with the first application at a second time. The example method may also include receiving an indication of an anomaly associated with the first application at the second time. The example method may also include comparing, by a first natural language processing model on the first computing system, the second data and the first data. The example method may also include determining, by the first natural language processing model and based on the comparison, a first difference indicative that a portion of the first data is different than a same portion of the second data. The example method may also include receiving third data associated with the first application. The example method may also include determining, by the first natural language processing model, that the first difference exists in the third data. The example method may also include automatically initiating a first action to prevent or mitigate a second anomaly associated with the first application.

Systems and methods for proactive service health detection

A method performed in real-time includes receiving and storing time-based data over a specific time period and dividing the specific time period into a plurality of time windows. The method further includes determining that data associated with two or more proximate time windows are within a predetermined variance of one another and responsive to the determination: generating a mathematical function representative of the data associated with the two or more proximate time windows, deleting the data associated with the two or more proximate time windows, and generating a representation of the deleted data from the mathematical function. In certain embodiments, the data comprises empirical network telemetry data.

Lossy statistical data compression

Disclosed are systems and methods for network configuration management systems and methods. In some embodiments, the discloses systems and methods may involve receiving data from one or more nodes within a particular network. The data may include, for example, topology, telemetry, geographical, and other data relating to the nodes, the network, and/or the functionality of the nodes or network. Once received, such data may be cleaned and processing may be performed on the data. Such processing may involve clustering the data into groups based on various parameters and performing forecasting on the data to determine future usage rates and capacity information, for example. The clustering and forecasting results may be fed to a rules engine and/or an optimization engine, which may then determine appropriate actions to take on the network (e.g., changes to various nodes in terms of technology and/or number of nodes).

Systems and methods for network configuration management

Devices, systems, and methods are provided for performing secured analytics using encrypted data. The method may include receiving first data and second data, the first data and the second data being homomorphically encrypted, the first data associated with a first type of data, and the second data associated with a second type of data. The method may include retrieving third data associated with the first type of data, and retrieving fourth data associated with the second type of data. The method may include determining a first proximity between the first data and the third data, and determining a second proximity between the second data and the fourth data. The method may include determining, based on the first proximity and the second proximity, a risk score, and determining, based on the risk score, a fraudulent action associated with the first data and the second data.

Secured analytics using encrypted data

Growing community of inventors

Lilburn, GA, United States of America

Jignesh B Patel