About me
- I am a final-year PHD candidate from Department of Computer Science at Rutgers University, advised by Prof. Shiqing Ma.
- My research focuses on system security and artificial intelligence, particularly at the intersection of AI-driven security as well as the security of AI systems.
- I am especially interested in leveraging AI to automate traditional system security solutions, including anomaly/threat detection, forensics, large-scale security data analysis (e.g., logs, provenance, graph databases, and security-related documents), and program analysis.
- Additionally, I work on enhancing the trustworthiness and robustness of AI systems, with a focus on mitigating backdoor and adversarial attacks, developing explainable AI models, and addressing emerging threats in large language models (LLMs).
This summer, I was a security and privacy research intern at IBM Research. I was a machine learning and AI research intern at Bell Lab where I focused on data mining on large-scale industry logs in Summer 2023. Before joining Rutgers, I obtained my B.E. from Central South University in 2020.
- I am on the market and look for a full time job!
News
- [2024-08] One paper is accepted by ACSAC 2024.
- [2024-05] I joined IBM Research as a security and privacy intern!
- [2024-04] One paper is accepted by ASPLOS 2024.
- [2023-09] I am invited as a reviewer of NeurIPS BUGs 2023, ICLR 2024, ICML 2024.
- [2023-06] I joined Bell Lab as a Machine Learning and AI intern (2023 summer).
- [2023-05] Two papers are accepted to Usenix Security 2023.
- [2023-04] I am invited as a reviewer of NeurIPS 2023.
- [2022-09] Two papers are accepted to NeurIPS 2022.
- [2022-01] I am invited as a reviewer of ICML 2022.
- [2022-01] I am a member of Usenix Security 2022 Artifact Evaluation Committee.
- [2021-09] One paper is accepted to Usenix Security 2021.
Publication
Madeline: Continuous and Low-cost Monitoring with Graph-free Representations to Combat Cyber Threats
Wenjia Song, Hailun Ding, Na Meng, Peng Gao, Danfeng (Daphne) Yao (ACSAC 2024)Merlin: Multi-tier Optimization of eBPF Code for Performance and Compactness
Jinsong Mao, Hailun Ding, Juan Zhai, Shiqing Ma
Architectural Support for Programming Languages and Operating Systems 2024 (ASPLOS 2024)AirTag: Towards Automated Attack Investigation by Unsupervised Learning with Log Texts
Hailun Ding, Juan Zhai, Yuhong Nan, Shiqing Ma
USENIX Security Symposium 2023 (Usenix security 2023)The Case for Learned Provenance Graph Storage Systems
Hailun Ding, Juan Zhai, Dong Deng, Shiqing Ma
USENIX Security Symposium 2023 (Usenix security 2023)Rethinking the Reverse-engineering of Trojan Triggers
Zhenting Wang, Kai Mei, Hailun Ding, Juan Zhai, Shiqing Ma
Proceedings of Neural Information Processing Systems 2022 (NeurIPS 2022)Training with More Confidence: Mitigating Injected and Natural Backdoors During Training
Zhenting Wang, Hailun Ding, Juan Zhai, Shiqing Ma
Proceedings of Neural Information Processing Systems 2022 (NeurIPS 2022)ELISE: A Storage Efficient Logging System Powered by Redundancy Reduction and Representation Learning
Hailun Ding, Shenao Yan, Juan Zhai, Shiqing Ma
USENIX Security Symposium 2021 (Usenix security 2021)Procedural Learning With Robust Visual Features via Low Rank Prior
Haifeng Li, Li Chen, Hailun Ding, Qi Li, Bingyu Sun, Guohua Wu
IEEE Access 2019A Data-driven Adversarial Examples Recognition Framework via Adversarial Feature Genome
Li Chen, Hailun Ding, Qi Li, Jiawei Zhu, Jian Peng, Haifeng Li
Arxiv 2019Understanding the Importance of Single Directions via Representative Substitution
Li Chen, Hailun Ding, Qi Li, Zhuo Li, Jian Peng, Haifeng Li
AAAI 2019 Workshop on Network Interpretability for Deep Learning**
Service
- Program Committee, AAAI 2025
- Reviewer, TIFS
- SubReviewer, CODASPY 2024
- Reviewer, ICLR 2024, 2025
- Reviewer, NeurIPS Workshop on Backdoors in Deep Learning: The Good, the Bad, and the Ugly (BUGS) 2023
- Reviewer, NeurIPS 2023
- Reviewer, International Conference on Machine Learning (ICML), 2022, 2024
- Artifact Evaluation Committee, USENIX Security Symposium, 2022
Award
- National Scholarship (2017, 2019, 0.2% of Chinese undergraduate students)
- First Level Scholarship of Central South University (2017, 2018, 2019, Top 3%)
- Diamond Scholarship (2017, 15 person in 30,000 undergraduate students)
- First Prize in The Hack, Hack Shanghai (2018)