Publication: Model Aggregation for Distributed Content Anomaly Detection
Publication: Unsupervised Anomaly-based Malware Detection using Hardware...
Publication: Synthetic Data Generation and Defense in Depth Measurement of Web...
Publication: Measuring Drive-by Download Defense in Depth
The Intrusion Detection Systems Group at Columbia University aims to build next-generation tools to detect stealthy and malicious intruders in computer systems. This includes research into anomaly detection, collaborative intrusion detection, attacker modeling, malicious code, and secure wireless networks. Headed by Professor Salvatore J. Stolfo, IDS includes seven PhD students and a number of Masters and undergraduate students. Several IDS technologies from our lab have been successfully commercialized and deployed in protecting network infrastructure.