Palo Alto Networks had seven patents in internet of things during Q1 2024. Palo Alto Networks Inc has filed patents for IoT device application workload capture and an anomalous behavior detector using the LOF algorithm with novelty detection. The IoT device application workload capture involves selecting a target IoT device, determining and tagging its flow, admitting packets into a ring buffer, and performing extraction on a portion of the packets. The anomalous behavior detector is designed to detect novel behavioral changes of devices based on network traffic data, using feature vectors representing stability or similarity of network traffic variables chosen as device identifiers and behavioral indicators. GlobalData’s report on Palo Alto Networks gives a 360-degree view of the company including its patenting strategy. Buy the report here.

Palo Alto Networks grant share with internet of things as a theme is 42% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Iot device application workload capture (Patent ID: US20240098062A1)

The patent filed by Palo Alto Networks Inc. pertains to a system and method for capturing IoT device application workloads. The system involves selecting a target IoT device, determining and tagging the associated flow, admitting packets into a ring buffer, receiving an indication for packet extraction, and extracting the specified portion of packets. The target IoT device selection can be based on risk score elevation, known exploit applicability, observed exploit attempts, or communication URLs. The extracted packets can be provided to a network traffic analysis system, and the system can also stop admitting packets based on predefined criteria.

The method outlined in the patent involves similar steps as the system, including selecting a target IoT device, tagging the associated flow, admitting packets into a ring buffer, receiving an indication for extraction, and extracting the specified portion of packets. Additionally, the patent includes a computer program product with instructions for implementing the method. Overall, the patent focuses on efficiently capturing and analyzing IoT device application workloads to enhance network security and threat detection, with specific criteria for target device selection and packet extraction based on risk factors and communication patterns.

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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.