The areas of research associated with Yinglian Xie, based on the dblp dataset, primarily focus on computer science domains such as cybersecurity, network analysis, and systems security. Key research topics include the detection and analysis of spamming botnets, anonymization techniques on the internet, and privacy protection in search systems. There is also significant work on network-level spam detection, botnet signatures, and web security. Yinglian Xie's publications span various conferences like IEEE Symposium on Security and Privacy, ACM SIGCOMM, and NDSS, highlighting a strong emphasis on both theoretical and practical aspects of security and privacy in distributed systems. Additionally, Xie has explored topics related to graph mining and anomaly detection in large networks.
DataVisor, founded by Yinglian Xie and Fang Yu, uses unsupervised machine learning to detect emerging fraud schemes before significant losses occur, focusing on real-time clustering of fraudulent activities.
