Tel Aviv, Israel

Mathias A M Scherman


Average Co-Inventor Count = 2.0

ph-index = 1

Forward Citations = 10(Granted Patents)


Company Filing History:


Years Active: 2022-2024

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2 patents (USPTO):

Title: Mathias A M Scherman: Innovator in Security Alert Detection

Introduction

Mathias A M Scherman is a notable inventor based in Tel Aviv, Israel. He has made significant contributions to the field of network security through his innovative patents. With a total of two patents to his name, Scherman is recognized for his expertise in utilizing machine learning to enhance security protocols.

Latest Patents

Scherman's latest patents focus on detecting missing security alerts using a machine learning model. The methods, systems, and apparatuses he developed involve receiving an alert sequence generated by a network security provider. By applying this alert sequence to a security incident model, the system can identify whether the sequence corresponds to a security incident defined by a predetermined sequence of alerts. This includes at least one alert that may be missing from the received alert sequence. The innovation generates a notification to the network security provider, indicating the security incident or the missing alerts. The security incident model is created by providing a set of historical alerts and security incidents to a machine learning algorithm, which enhances its accuracy and effectiveness.

Career Highlights

Mathias A M Scherman is currently associated with Microsoft Technology Licensing, LLC. His work at this prominent company allows him to leverage his skills in developing advanced security solutions. Scherman's contributions are vital in addressing the challenges faced by network security providers in detecting and responding to potential threats.

Collaborations

One of Scherman's notable collaborators is Roy Levin. Their partnership exemplifies the collaborative spirit in the field of technology and innovation.

Conclusion

Mathias A M Scherman is a distinguished inventor whose work in security alert detection has the potential to significantly improve network security. His innovative approach using machine learning models showcases the importance of technology in safeguarding information systems.

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