Shudong Li

Title: Innovations by Shudong Li in APT Organization Identification

Introduction

Shudong Li is an accomplished inventor based in Guangzhou, China. He has made significant contributions to the field of cybersecurity, particularly in the identification of Advanced Persistent Threat (APT) organizations. His innovative approach combines machine learning techniques with behavior analysis to enhance the detection of malicious activities.

Latest Patents

Shudong Li holds a patent for a "Stacking-ensemble-based APT organization identification method and system, and storage medium." This patent describes a method that utilizes a TF-IDF algorithm combined with n-gram techniques to extract and vectorize behavior features from malware samples. The process involves calculating correlations and chi-square values to refine the feature set, ultimately leading to the construction of a multi-model fusion stacking ensemble. This model significantly improves the identification of new APT attacks by enhancing recognition accuracy and efficiency.

Career Highlights

Shudong Li is affiliated with Guangzhou University, where he continues to advance research in cybersecurity. His work focuses on developing innovative solutions that address the complexities of data sets in the context of APT identification. His contributions have been instrumental in improving the automatic identification efficiency of new malicious samples.

Collaborations

Shudong Li has collaborated with notable colleagues, including Qianqing Zhang and Xiaobo Wu. Their joint efforts have furthered the research and development of advanced identification methods in cybersecurity.

Conclusion

Shudong Li's innovative work in APT organization identification showcases the potential of combining machine learning with behavior analysis. His contributions are paving the way for more effective cybersecurity measures in an increasingly complex digital landscape.