Publications

2024

1. USENIX Security’24

   

   Malla: Demystifying Real-world Large Language Model Integrated Malicious Services

   Zilong Lin, Jian Cui, Xiaojing Liao, and XiaoFeng Wang

   The 33rd USENIX Security Symposium, 2024

   • Award: Top-15 finalist in 2024 CSAW Best Applied Research Competition

   • Media Coverage: Le Monde, The Wall Street Journal, Tech Policy Press, Fast Company, Cryptopolitan

   Awarded HTML PDF Video Code

   

   Top-15 finalist in 2024 CSAW Best Applied Research Competition

2. IEEE S&P’24

   

   MAWSEO: Adversarial Wiki Search Poisoning for Illicit Online Promotion

   Zilong Lin, Zhengyi Li, Xiaojing Liao, XiaoFeng Wang, and Xiaozhong Liu

   The 45th IEEE Symposium on Security and Privacy (SP), 2024

   HTML PDF Video

   
3. ACM CCS’24

   

   Understanding Cross-Platform Referral Traffic for Illicit Drug Promotion

   Mingming Zha, Zilong Lin, Siyuan Tang, Xiaojing Liao, Yuhong Nan, and XiaoFeng Wang

   The ACM Conference on Computer and Communications Security (CCS), 2024, 2024

   HTML PDF

   

2022

1. NDSS’22

   

   Demystifying local business search poisoning for illicit drug promotion

   Peng Wang^*, Zilong Lin^*, Xiaojing Liao, and XiaoFeng Wang

   ISOC Network and Distributed System Security Symposium (NDSS), 2022

   • Award: Top-10 finalist in 2022 CSAW Best Applied Research Competition

   Awarded Bib HTML PDF

   

   Top-10 finalist in 2022 CSAW Best Applied Research Competition

   @article{wang2022demystifying,
     title = {Demystifying local business search poisoning for illicit drug promotion},
     author = {Wang, Peng and Lin, Zilong and Liao, Xiaojing and Wang, XiaoFeng},
     journal = {ISOC Network and Distributed System Security Symposium (NDSS)},
     year = {2022},
   }

2. PAKDD’22

   IDSGAN: Generative adversarial networks for attack generation against intrusion detection

   Zilong Lin, Yong Shi, and Zhi Xue

   The 26th Pacific-Asia conference on knowledge discovery and data mining (PAKDD), 2022

   • Media Coverage: Analytics India Magazine, Towards Data Science, AI Front

   Bib HTML PDF

   

   @article{lin2022idsgan,
     title = {IDSGAN: Generative adversarial networks for attack generation against intrusion detection},
     author = {Lin, Zilong and Shi, Yong and Xue, Zhi},
     journal = {The 26th Pacific-Asia conference on knowledge discovery and data mining (PAKDD)},
     pages = {79--91},
     year = {2022},
     organization = {Springer},
     media = {
       <a href="https://analyticsindiamag.com/ai-features/heres-the-truth-gans-easily-can-fool-intrusion-detection-systems/">Analytics India Magazine</a>,
       <a href="https://medium.com/data-science/the-potential-of-an-intrusion-detection-system-generative-adversarial-network-idsgan-892e0c5c2b2a">Towards Data Science</a>,
       <a href="https://mp.weixin.qq.com/s/qXcgfHQyzYHL24Lc28USNQ">AI Front</a>
       }
   }

2018

1. IJCNN’18

   Character-level intrusion detection based on convolutional neural networks

   Zilong Lin, Yong Shi, and Zhi Xue

   International Joint Conference on Neural Networks (IJCNN), 2018

   HTML