RTX had 13 patents in big data during Q4 2023.RTX Corp filed patents for detecting anomalous network processes using topological data analysis and machine learning, monitoring cargo loading for damage detection without constant human monitoring, calibrating antenna arrays using RF/optical data centers and optical/RF dish calibrators, and detecting anomaly events in hardware-based machine learning anomaly event detectors using predetermined parameter values and neural network outputs. GlobalData’s report on RTX gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

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RTX grant share with big data as a theme is 61% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Cyberattack detection with topological data (Patent ID: US20230412623A1)

The patent filed by RTX Corp discusses devices, systems, and methods for detecting anomalous or malicious processes based on network flow data. The method involves receiving network flow data, implementing a topological data analysis (TDA) algorithm to identify homological classes, appending the resulting pairs to a feature space, and using a machine learning algorithm to determine if the data is associated with a network intrusion. The claims detail the device's configuration, including memory and processing circuitry, the types of network intrusions detected, the use of clustering classifiers, and the specific data elements considered in the network flow data.

The device and method described in the patent focus on network intrusion detection using a combination of TDA algorithms and machine learning techniques. The device's operations involve receiving network flow data, applying a topological algorithm to identify specific pairs, appending them to a feature vector, and using a classifier to determine intrusion. The patent also covers the types of network intrusions detected, the use of clustering classifiers, and the specific data elements considered in the network flow data, such as IP addresses, timestamps, and protocol information. Overall, the patent outlines a comprehensive approach to detecting and classifying network intrusions based on network flow data and topological analysis.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.