Palo Alto Networks, Inc.

Trend Micro Inc.

Zingbox, Ltd.

Mayuresh Ektare

Mei Wang

Gong Cheng

Anthony Isaacson

Howard Chen

Viswa Soubramanien

Peter Shaohong Wei

An Internet of Things (IoT) device profile applicable to an IoT device is determined. Data packets transmitted to and from the IoT device are analyzed. A risk level of the IoT device is determined based at least in part on the data packet analysis. A determination is made that the risk level exceeds a threshold and a remedial action is taken in response.

IoT device risk assessment

Techniques for visualizing IoT device management are disclosed. A system utilizing such techniques can include an IoT device risk assessment system and an IoT device management visualization system. A method utilizing such techniques can include grouping IoT devices into an IoT device dimension group based on IoT device dimensions defining the group and controlling presentation of management data for the IoT devices based on the grouping of the IoT devices into the IoT device dimension group.

IoT device management visualization

A first device governs operation of a second device based on a network security risk posed by the second device. The second device is disposed locally to the first device and in local network communication with the first device. The first device is in network communication with a cloud-based computational service.

Techniques for assessing risks of IoT devices. A system utilizing such techniques can include a packet analysis based IoT device risk assessment system and an IoT device risk assessment system. A method utilizing such techniques can include extraction of IoT device risk factors from a device profile of an IoT device and application of assessment weights to the IoT device risk factors to assess a risk level of an IoT device.

Techniques for assessing risks of IoT device. A system utilizing such techniques can include a packet analysis based IoT device risk assessment system and an IoT device risk assessment system. A method utilizing such techniques can include extraction of IoT device risk factors from a device profile of an IoT device and application of assessment weights to the IoT device risk factors to assess a risk level of an IoT device.

Visualization for presenting event information indicative of a computer security threat is automatically selected from available visualizations. Event information received from data sources is assigned a category prior to being stored in an event log. The event log may be searched for relevant event information using the assigned categories. Visualizations applicable to the relevant event information are retrieved and given an importance score, which may be based on execution of prioritization algorithms using corresponding relevant event information. The retrieved visualizations are ranked based on their importance scores. One or more retrieved visualizations that have the best importance scores relative to other retrieved visualization are selected for rendering.

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Cupertino, CA, United States of America

Mayuresh Ektare