Beibei Li

Title: Beibei Li: Innovator in Intrusion Detection Systems

Introduction

Beibei Li is a prominent inventor based in Chengdu, China. She has made significant contributions to the field of industrial control systems, particularly in the area of intrusion detection. Her innovative approach utilizes advanced machine learning techniques to enhance security measures in critical infrastructures.

Latest Patents

Beibei Li holds a patent for a "Few-shot learning based intrusion detection method of industrial control system." This patent describes a method that involves dividing an original data set extracted from the data flow of the industrial control system into a detection model training set and a basic model training set. The process includes using principal component analysis to reduce the dimension of a continuous data matrix and employing one-hot encoding for a discrete data matrix. The method constructs few-shot training tasks required for basic model training and trains a basic model based on convolutional neural networks. Ultimately, this approach enables effective real-time detection of attacks in data streams.

Career Highlights

Beibei Li is affiliated with Sichuan University, where she continues to advance her research in machine learning and security systems. Her work has garnered attention for its practical applications in safeguarding industrial control systems.

Collaborations

Beibei collaborates with notable colleagues, including Tao Li and Yuankai Ouyang, who contribute to her research endeavors and enhance the impact of her innovations.

Conclusion

Beibei Li's contributions to the field of intrusion detection systems exemplify the intersection of technology and security. Her innovative methods are paving the way for more secure industrial environments.