I am currently a Ph.D. student under the supervision of Professor Xiaojing Liao. My primary research interests lie at the intersection of cybersecurity, machine learning, and natural language processing. Specifically, I focus on the following areas:

1. Sociotechnical, with a focus on cybercrime and privacy compliance checks
2. Trustworthy machine learning, particularly in the realms of robustness, privacy, and their interconnections.
3. Data-driven privacy and security, with an emphasis on threat intelligence gathering.

My long-term research goal is to discover and understand critical security and privacy issues in cybersystems or AI systems through data-oriented analysis, and to design and develop innovative solutions to address these issues with robust, private guarantees for different real-world applications.

You can find my CV here: Yue Qin’s CV

Recent Research Areas & Interests

• Privacy compliance check: [Usenix’23]

• AI security and privacy: [CCS’23B][CCS’21] [NAACL’22]

• Cybercrime and threat intelligence: [NDSS’20]

• NLP/ML-assisted vulnerability discovery: [Usenix’19] and management [CCS’23A]

• Risk Detection: [Raid’22] [EMNLP’23]

News

• (10/09/2023) One paper was accepted by EMNLP’23.
• (08/24/2023) Lalaine has been selected for showcasing in the 2023 NSA CAE-R Research Symposium.
• (05/09/2023) Two papers were accepted by CCS’23.
• (02/12/2023) One paper was accepted by USENIX Security’23.
• (11/17/2021) One paper about classifier with global robustness properties was accepted by CCS’2021 and won Best Paper Award runner-up.
• (10/06/2019) One paper about threat intelligence gathering via chatting with cybercriminals was accepted by NDSS’20.
• (05/24/2019) One paper was accepted by USENIX Security’19.

Selected Publications

• 2023

Vulnerability Intelligence Alignment via Masked Graph Attention Networks.
Yue Qin, Yue Xiao, Xiaojing Liao. To appear in Proceedings of ACM Conference on Computer and Communications Security (CCS), 2023. (Acceptance rate: 19.87%)

Stolen Risks of Models with Security Properties.
Yue Qin, Zhuoqun Fu, Chuyun Deng, Xiaojing Liao, Jia Zhang, Haixin Duan. To appear in Proceedings of ACM Conference on Computer and Communications Security (CCS), 2023. (Acceptance rate: 19.87%)

STINMatch: Semi-Supervised Semantic-Topological Iteration Network for Financial Risk Detection via News Label Diffusion.
Xurui Li, Yue Qin (co-first author), Rui Zhu, Tianqianjin Lin, Yongming Fan, Yangyang Kang, Kaisong Song, Fubang Zhap, Changlong Sun, Haixu Tang, Xiaozhong Liu. To appear in Proceedings of Empirical Methods in Natural Language Processing (EMNLP) 2023.

Lalaine: Measuring and Characterizing Non-Compliance of Apple Privacy Labels at Scale.
Yue Xiao, Zhengyi Li, Yue Qin, Xiaolong Bai, Jiale Guan, Xiaojing Liao, Luyi Xing. In Proceedings of USENIX Security Symposium (Security), 2023. (Acceptance rate: 29%)

• 2022

Encrypted Malware Traffic Detection via Graph-based Network Analysis.
Zhuoqun Fu, Mingxuan Liu, Yue Qin, Jia Zhang, Yuan Zou, Qilei Yin, Qi Li, Haixin Duan. In Proceedings of the 25th International Symposium on Research in Attacks, Intrusions and Defenses (RAID), 2022. (Acceptance rate: 25.2%)

ValCAT: Variable-Length Contextualized Adversarial Transformations Using Encoder-Decoder Language Model.
Chuyun Deng, Mingxuan Liu, Yue Qin, Jia Zhang, Hai-Xin Duan, Donghong Sun. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022. (Acceptance rate: 21%).
[code]

• 2021

Learning Security Classifiers with Verified Global Robustness Properties.
Yizheng Chen, Shiqi Wang, Yue Qin, Xiaojing Liao, Suman Jana, David Wagner. In Proceedings of ACM Conference on Computer and Communications Security (CCS), 2021. (Acceptance rate: 22.3%) [code/data]
ACM CCS Best Paper Award runner-up, 2021

• 2020

Into the Deep Web: Understanding E-commerce Fraud from Autonomous Chat with Cybercriminals.
Peng Wang, Xiaojing Liao, Yue Qin, XiaoFeng Wang. In Proceedings of the ISOC Network and Distributed System Security Symposium (NDSS), 2020. (Acceptance rate: 17%). [code/data]

• 2019

Devils in the Guidance: Predicting Logic Vulnerabilities in Payment Syndication Services through Automated Documentation Analysis.
Yi Chen, Luyi Xing, Yue Qin, Xiaojing Liao, XiaoFeng Wang, Kai Chen, Wei Zou. In Proceedings of USENIX Security Symposium (Security), 2019. (Acceptance rate: 16%).
[code/data]

• 2018

Asynchronous Bidirectional Decoding for Neural Machine Translation.
Xiangwen Zhang, Jinsong Su, Yue Qin, Yang Liu, Rongrong Ji, and Hongji Wang. In Proceedings of Association for the Advancement of Artificial Intelligence (AAAI), 2018. (Acceptance rate: 24.7%). [code]