Herzliya, Israel

Masayuki Nakae


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2021

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1 patent (USPTO):Explore Patents

Title: The Innovations of Masayuki Nakae

Introduction

Masayuki Nakae is an accomplished inventor based in Herzliya, Israel. He has made significant contributions to the field of network security, particularly in the detection of malicious network activity. His innovative approach combines local and global machine-learning models to enhance the monitoring of network traffic.

Latest Patents

Nakae holds a patent for a method of monitoring network traffic in a communication network. This patent describes a sentinel module designed to detect malicious activity. The gateway sentinel module receives network traffic directed through a gateway, which connects the local distribution of the network to its core. The detection of malicious activity is achieved through a combination of a local machine-learning model and a global machine-learning model. The local model identifies malicious activity based on network traffic from the local distribution, while the global model is trained on data from multiple local sentinel modules across various computing nodes.

Career Highlights

Throughout his career, Masayuki Nakae has worked with notable organizations, including NEC Corporation of America and Ben-Gurion University of the Negev Research and Development Authority. His experience in these institutions has allowed him to refine his expertise in network security and machine learning.

Collaborations

Some of Nakae's notable coworkers include Yisroel Avraham Mirsky and Oleg Brodt. Their collaborative efforts have contributed to advancements in the field of network monitoring and security.

Conclusion

Masayuki Nakae's innovative work in detecting malicious network activity showcases his expertise and commitment to enhancing network security. His contributions through patents and collaborations highlight the importance of integrating machine learning in safeguarding communication networks.

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