18419024. Network Anomaly Detection simplified abstract (Google LLC)

Network Anomaly Detection

Organization Name

Google LLC

Inventor(s)

Mikhal Shemer of Tel Aviv (IL)

Roee Engelberg of Tel Aviv (IL)

Yonit Tova Halperin Worzel of Tel Aviv (IL)

Alex Gontmakher of Holon (IL)

Alexander Goldshtein of Tel Aviv (IL)

Gal Elidan of Modiin (IL)

Benjamin Dov Kessler of Jerusalem (IL)

Network Anomaly Detection - A simplified explanation of the abstract

This abstract first appeared for US patent application 18419024 titled 'Network Anomaly Detection

Simplified Explanation

A cloud network is a complex environment where multiple users can host, create, modify, and develop virtual machines with unknown behaviors. The patent application discloses methods, systems, and apparatuses to monitor the environment for network anomalies using machine learning techniques, as well as techniques to adapt to user feedback for tuning the models.

• Monitoring complex cloud networks for network anomalies using machine learning techniques
• Adapting models based on user feedback for specific use cases, virtual machine types, and users

Potential Applications

The technology can be applied in various industries such as cybersecurity, cloud computing, and network management.

Problems Solved

1. Detection of network anomalies in complex cloud environments 2. Adapting machine learning models based on user feedback for better performance

Benefits

1. Improved security and performance in cloud networks 2. Enhanced adaptability to changing user requirements

Potential Commercial Applications

Optimizing cloud network performance, enhancing cybersecurity measures, and improving network management tools.

Possible Prior Art

One possible prior art could be traditional network monitoring tools that may not have the adaptability and machine learning capabilities described in the patent application.

Unanswered Questions

How does the technology handle scalability in large cloud networks?

The article does not provide details on how the technology can scale to monitor and adapt to network anomalies in large cloud environments.

What are the potential limitations of using machine learning techniques in cloud network monitoring?

The article does not discuss any potential drawbacks or limitations of relying on machine learning for detecting network anomalies in cloud environments.

Original Abstract Submitted

A cloud network is a complex environment in which hundreds and thousands of users or entities can each host, create, modify, and develop multiple virtual machines. Each virtual machine can have complex behavior unknown to the provider or maintainer of the cloud. Technologies disclosed include methods, systems, and apparatuses to monitor the complex environment to detect network anomalies using machine learning techniques. In addition, techniques to modify and adapt to user feedback are provided allowing the developed models to be tuned for specific use cases, virtual machine types, and users.