publications

2026

1. TAISAP

   The Obvious Invisible Threat: Vulnerabilities of LLM-Powered GUI Agents to Adversarial UI Manipulations in Web Interaction Tasks

   Chaoran Chen, Zhiping Zhang, Bingcan Guo, Shang Ma, Ibrahim Khalilov, Simret A Gebreegziabher, Bingsheng Yao, Dakuo Wang, Yanfang Ye, Ziang Xiao, Yaxing Yao, Tianshi Li, and Toby Jia-Jun Li

   ACM Transactions on AI Security and Privacy, 2026

   DOI Bib PDF

   @article{chen2026obvious,
     title = {The Obvious Invisible Threat: Vulnerabilities of LLM-Powered GUI Agents to Adversarial UI Manipulations in Web Interaction Tasks},
     author = {Chen, Chaoran and Zhang, Zhiping and Guo, Bingcan and Ma, Shang and Khalilov, Ibrahim and Gebreegziabher, Simret A and Yao, Bingsheng and Wang, Dakuo and Ye, Yanfang and Xiao, Ziang and Yao, Yaxing and Li, Tianshi and Li, Toby Jia-Jun},
     journal = {ACM Transactions on AI Security and Privacy},
     year = {2026},
     doi = {10.1145/3807953},
   }

2. COLM

   PreScam: A Benchmark for Predicting Scam Progression from Early Conversations

   Weixiang Sun, Shang Ma, Yiyang Li, Tianyi Ma, Zehong Wang, Colby Nelson, Xusheng Xiao, and Yanfang Ye

   In Conference on Language Modeling (COLM), 2026

   arXiv Bib Code

   @inproceedings{sun2026prescam,
     title = {PreScam: A Benchmark for Predicting Scam Progression from Early Conversations},
     author = {Sun, Weixiang and Ma, Shang and Li, Yiyang and Ma, Tianyi and Wang, Zehong and Nelson, Colby and Xiao, Xusheng and Ye, Yanfang},
     booktitle = {Conference on Language Modeling (COLM)},
     year = {2026},
   }

3. AACL

   Agent+P: Guiding UI Agents via Symbolic Planning

   Shang Ma, Xusheng Xiao, and Yanfang Ye

   In Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL), Main Conference, 2026

   Oral presentation

   arXiv Bib Code

   @inproceedings{ma2026agentp,
     title = {Agent+P: Guiding UI Agents via Symbolic Planning},
     author = {Ma, Shang and Xiao, Xusheng and Ye, Yanfang},
     booktitle = {Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL), Main Conference},
     note = {Oral presentation},
     year = {2026},
   }

4. Preprint

   The Anatomy of Scam Scenarios: Large-Scale Characterization and Conversation-Aware Detection

   Shang Ma, Chen Yanai, Avichai Ben, Zichen Liu, Yanfang Ye, and Xusheng Xiao

   arXiv preprint, 2026

   arXiv Bib

   @article{ma2026scenarios,
     title = {The Anatomy of Scam Scenarios: Large-Scale Characterization and Conversation-Aware Detection},
     author = {Ma, Shang and Yanai, Chen and Ben, Avichai and Liu, Zichen and Ye, Yanfang and Xiao, Xusheng},
     journal = {arXiv preprint},
     year = {2026},
     recent_preprint = {true},
   }

5. Preprint

   From UI to Code: Mobile Ads Detection via LLM-Unified Static-Dynamic Analysis

   Shang Ma, Wei Cheng, Yanfang Ye, and Xusheng Xiao

   arXiv preprint, 2026

   arXiv Bib

   @article{ma2026adwise,
     title = {From UI to Code: Mobile Ads Detection via LLM-Unified Static-Dynamic Analysis},
     author = {Ma, Shang and Cheng, Wei and Ye, Yanfang and Xiao, Xusheng},
     journal = {arXiv preprint},
     year = {2026},
     recent_preprint = {true},
   }

2025

1. EMNLP

   PsyScam: A Benchmark for Psychological Techniques in Real-World Scams

   Shang Ma, Tianyi Ma, Jiahao Liu, Wei Song, Zhenkai Liang, Xusheng Xiao, and Yanfang Ye

   In Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025

   arXiv Bib Code

   @inproceedings{ma2025psyscam,
     title = {PsyScam: A Benchmark for Psychological Techniques in Real-World Scams},
     author = {Ma, Shang and Ma, Tianyi and Liu, Jiahao and Song, Wei and Liang, Zhenkai and Xiao, Xusheng and Ye, Yanfang},
     booktitle = {Conference on Empirical Methods in Natural Language Processing (EMNLP)},
     year = {2025},
   }

2. NDSS

   Careful About What App Promotion Ads Recommend! Detecting and Explaining Malware Promotion via App Promotion Graph

   Shang Ma, Chaoran Chen, Shao Yang, Shifu Hou, Toby Jia-Jun Li, Xusheng Xiao, Tao Xie, and Yanfang Ye

   In Network and Distributed System Security Symposium (NDSS), 2025

   Bib PDF Code

   @inproceedings{ma2025adgpe,
     title = {Careful About What App Promotion Ads Recommend! Detecting and Explaining Malware Promotion via App Promotion Graph},
     author = {Ma, Shang and Chen, Chaoran and Yang, Shao and Hou, Shifu and Li, Toby Jia-Jun and Xiao, Xusheng and Xie, Tao and Ye, Yanfang},
     booktitle = {Network and Distributed System Security Symposium (NDSS)},
     year = {2025},
   }

2024

1. ECML PKDD

   Symbolic Prompt Tuning Completes the App Promotion Graph

   Zhongyu Ouyang, Chunhui Zhang, Shifu Hou, Shang Ma, Chaoran Chen, Toby Li, Xusheng Xiao, Chuxu Zhang, and Yanfang Ye

   In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2024

   Bib HTML

   @inproceedings{ouyang2024symbolic,
     title = {Symbolic Prompt Tuning Completes the App Promotion Graph},
     author = {Ouyang, Zhongyu and Zhang, Chunhui and Hou, Shifu and Ma, Shang and Chen, Chaoran and Li, Toby and Xiao, Xusheng and Zhang, Chuxu and Ye, Yanfang},
     booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)},
     year = {2024},
   }

2023

1. GLFrontiers

   Prompt Learning Unlocked for App Promotion in the Wild

   Zhongyu Ouyang, Shifu Hou, Shang Ma, Chaoran Chen, Chunhui Zhang, Toby Li, Xusheng Xiao, Chuxu Zhang, and Yanfang Ye

   In NeurIPS Workshop: New Frontiers in Graph Learning (GLFrontiers), 2023

   Bib PDF

   @inproceedings{ouyang2023prompt,
     title = {Prompt Learning Unlocked for App Promotion in the Wild},
     author = {Ouyang, Zhongyu and Hou, Shifu and Ma, Shang and Chen, Chaoran and Zhang, Chunhui and Li, Toby and Xiao, Xusheng and Zhang, Chuxu and Ye, Yanfang},
     booktitle = {NeurIPS Workshop: New Frontiers in Graph Learning (GLFrontiers)},
     year = {2023},
   }

2022

1. TNSM

   Federated Anomaly Detection on System Logs for the Internet of Things: A Customizable and Communication-Efficient Approach

   Beibei Li, Shang Ma, Ruilong Deng, Kim-Kwang Raymond Choo, and Jin Yang

   IEEE Transactions on Network and Service Management, 2022

   Bib

   @article{li2022federated,
     title = {Federated Anomaly Detection on System Logs for the Internet of Things: A Customizable and Communication-Efficient Approach},
     author = {Li, Beibei and Ma, Shang and Deng, Ruilong and Choo, Kim-Kwang Raymond and Yang, Jin},
     journal = {IEEE Transactions on Network and Service Management},
     year = {2022},
     volume = {19},
     number = {2},
     pages = {1705--1716},
   }

2021

1. ISCC

   FlPhish: Reputation-based Phishing Byzantine Defense in Ensemble Federated Learning

   Beibei Li, Peiran Wang, Hanyuan Huang, Shang Ma, and Yukun Jiang

   In IEEE Symposium on Computers and Communications (ISCC), 2021

   Best Paper Bib

   Best Paper

   @inproceedings{li2021flphish,
     title = {FlPhish: Reputation-based Phishing Byzantine Defense in Ensemble Federated Learning},
     author = {Li, Beibei and Wang, Peiran and Huang, Hanyuan and Ma, Shang and Jiang, Yukun},
     booktitle = {IEEE Symposium on Computers and Communications (ISCC)},
     year = {2021},
   }