The
Network SystEm
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.
09/14/2019 - Our paper "Adversarial Examples Versus Cloud-based Detectors: A Black-box Empirical Study" [PDF] was accepted by IEEE Transactions on Dependable and Secure Computing (TDSC). Congrats to Xurong and Juntao.
08/16/2019 - Our paper "A Survey on Techniques, Applications and Security of Machine Learning Interpretability" [PDF] was accepted by Journal of Computer Research and Development.
07/16/2019 - Our paper "GA-Par: Dependable Microservice Orchestration Framework for Geo-Distributed Clouds" was accepted by IEEE Transactions on Parallel and Distributed Systems (TPDS).
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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.
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Adversarial Learning; Machine Learning Security and Privacy; AI-aided Vulnerability Mining; Smart Fuzzing; and Secure Multi-Party Computing and Learning.
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Graph Privacy; Anonymization and De-anonymization; Differential Privacy; and Web Privacy..
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Social Network Computing and Analytics and Graph and Network Embedding.
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