The
Network SystEm
Security & PrivAcy (NESA) Research Lab, directed by Dr. Shouling Ji, works at the intersection of AI, 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 and Security, (3) Software and System Security, and (4) Big Data Mining and Analysis.
11/14/2026 - Our paper "DIFPA: Boosting Adversarial Transferability via Diffusion-based Importance-aware Feature Pyramid Attack" won the Best Paper Award of ACM Multimedia 2026. Congrats to Bin Chen!
11/8/2026 - 恭喜林型双论文"PROMFUZZ: Leveraging LLM-Driven and Bug-Oriented Composite Analysis for Detecting Functional Bugs in Smart Contracts"入选"2026年度中国电子学会区块链分会顶会顶刊论文激励计划"！
10/13/2026 - Our paper "Label-Aware Distribution-based Dynamic Weighting Aggregation for Hierarchical Backdoor Defense in Federated Learning" was accepted by IEEE Transactions on Information Forensics & Security (TIFS). Congrats to Xi!
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ZJU NESA LAB 2026级有3-4个博士名额、3-4个硕士名额，研究方向：AI安全（算法能力强者优先）、软件与系统安全（代码能力强者优先），欢迎申请！
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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