Security & PrivAcy (NESA) Research Lab, directed by Dr. Shouling Ji, works at the intersection of the network systems, data
analytics, and information security fields. The lab seeks to develop theories, techniques, and systems to enable a more
secure and efficient network infrastructure, with computer systems that are more accountable and less vulnerable to
attacks and abuse.
Our current research focuses on four areas: (1) Data-Driven Security, (2) AI Security, (3) Privacy, and (4) Big Data Analysis.
07/10/2018 - Our paper "Pre-Patch: Find Hidden Threats in Open Software based on Machine Learning Method" won the Best Paper Award of SCF 2018.
07/01/2018 - Our paper "Adversarial Example Attacks and Defenses of Deep Learning Systems" was accepted by Communications of the CCF.
04/18/2018 - Dr. Shouling Ji was invited to serve on the Technical Program Committee (TPC) of IEEE MASS 2018.
NESA Lab looks for highly motivated undergrads, grads, and postdocs to join the group. If you are interested in our research, please come to visit our lab and/or send us your resume.
Cyber Threat/Crime Mining and Analysis; Fraud Detection and Analysis; Medical Application/Data Security and Privacy; Password Security; and CAPTCHA Security.read more
Adversarial Learning; Machine Learning Security and Privacy; AI-aided Vulnerability Mining; Smart Fuzzing; and Secure Multi-Party Computing and Learning.read more
Graph Privacy; Anonymization and De-anonymization; Differential Privacy; and Web Privacy..read more
Social Network Computing and Analytics and Graph and Network Embedding.read more