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Hi, I’m Yiling He 👋

  • 🌱 My Chinese name is 贺弋玲. My last name (the first character) sounds like “her,” with a flatter tongue position, and in Chinese it means “congrats.”
  • 🔭 I’m always learning recent advances in the related domains and never limit myself to one way
  • 👯 I currently work on LLM-powered software analysis, designing systems that are both highly effective and trustworthy. If you’re also excited about advancing AI for software security and understanding, I’d love to collaborate.
  • 💬 Visit my previous blog at https://e0hyl.github.io/BLOG-OF-E0
  • 📫 How to reach me: yiling-he@ucl.ac.uk (Research Fellow at University College London)

Contact Me

Selection of my publications here. 📧 denotes corresponding author.

  1. Combating Concept Drift with Explanatory Detection and Adaptation for Android Malware Classification
    Yiling He, Junchi Lei, Zhan Qin, Kui Ren, and Chun Chen
    In Proceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security (CCS) 2025
    PDF Code CCF A Conference Security Top 4
  2. On Benchmarking Code LLMs for Android Malware Analysis
    Yiling He, Hongyu She, Xingzhi Qian, Xinran Zheng, Zhuo Chen, Zhan Qin, and Lorenzo Cavallaro
    In Proceedings of the 34th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2025
    PDF Code Data CCF A Workshop
  3. LAMD: Context-driven Android Malware Detection and Classification with LLMs
    Xingzhi Qian, Xinran Zheng, Yiling He📧, Shuo Yang, and Lorenzo Cavallaro
    In 2025 IEEE Security and Privacy Workshops (SPW) 2025
    PDF Data CCF A Workshop Best Paper Award
  4. Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature Attribution
    Shuo Shao, Yiming Li, Hongwei Yao, Yiling He, Zhan Qin, and Kui Ren
    In Network and Distributed System Security Symposium (NDSS) 2025
    PDF Code Slides CCF A Conference Security Top 4
  5. Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey
    Xinyu She, Yue Liu, Yanjie Zhao, Yiling He, Li Li, Chakkrit Tantithamthavorn, Zhan Qin, and Haoyu Wang
    ACM Transactions on Software Engineering and Methodology (TOSEM) 2025
    PDF Data CCF A Journal
  6. Distilling Benign Knowledge with Fine-Grained AST Fragments for Precise Real-World Web Shell Detection
    Mingzhe Gao, Ligeng Chen, Yiling He📧, Yuhang Chen, Lingyun Ying, and Wang Yang
    In 2025 IEEE/ACM 33rd International Symposium on Quality of Service (IWQoS) 2025
    PDF Code CCF B Conference
  7. FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security Analysis
    Yiling He, Jian Lou, Zhan Qin, and Kui Ren
    In Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS) 2023
    PDF Code CCF A Conference Security Top 4
  8. DeUEDroid: Detecting Underground Economy Apps Based on UTG Similarity
    Zhuo Chen, Jie Liu, Yubo Hu, Lei Wu, Yajin Zhou, Yiling He, Xianhao Liao, Ke Wang, Jinku Li, and Zhan Qin
    In Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2023
    PDF Code CCF A Conference
  9. MsDroid: Identifying Malicious Snippets for Android Malware Detection
    Yiling He, Yiping Liu, Lei Wu, Ziqi Yang, Kui Ren, and Zhan Qin
    IEEE Transactions on Dependable and Secure Computing (TDSC) 2022
    PDF Code CCF A Journal

Experience including internships, services, education, and awards.

Education & Awards

University College London: Research Fellow

January, 2025 - now

S2Lab, Computer Science

Supervisor: Lorenzo Cavallaro

Zhejiang University: PhD degree

September, 2021 - June, 2024

Cyberspace Security, College of Computer Science

Supervisor: Kui Ren, Zhan Qin
Awards: Outstanding Graduate of Zhejiang University (2024) ZJU Outstanding PhD Dissertation Funding Recipient (2023) ZJU Graduate Student of Five Merits (2022) ZJU Outstanding Graduate Student (2021~2022) Higgs University Student Extracurricular Innovation Scholarship (2021)

Zhejiang University: Master's (transferred to PhD in the spring semester)

September, 2019 - June, 2021

Cyberspace Security, College of Computer Science

Supervisor: Kui Ren, Zhan Qin
Awards: ZJU Outstanding Graduate Student (2019)

Beijing University of Posts and Telecommunications: Bachelor degree

September, 2015 - June, 2019

Information Security, School of Cyberspace Security

Awards: Beijing Outstanding Graduation Design (2019) First prize in National College Student Information Security Contest (2018) National Scholarship (2018) Rui'an Tech Scholarship (2017)

Internships

Tencent: Intelligent Security Research Group, Xuanwu Lab

March, 2021 - August, 2021
Outcomes: BrutePrint: Expose Smartphone Fingerprint Authentication to Brute-force Attack PDF Issues

Professional Services

ACM SIGSAC Conference on Computer and Communications Security (CCS): Program Committee Member

2026

IEEE Symposium on Security and Privacy (IEEE S&P): Program Committee Member

2026

ACM Workshop on Artificial Intelligence and Security (AISec, co-located with CCS): Program Committee Member

2025

Workshop on Rethinking Malware Analysis (WoRMA, co-located with IEEE EuroS&P): Program Committee Member

2025

ACM SIGSAC Conference on Computer and Communications Security (CCS),
IEEE Symposium on Security and Privacy (IEEE S&P)*, USENIX Security Symposium (USENIX Security)*: External Reviewer

2022, 2024,
2025*(2)

IEEE Transactions on Dependable and Secure Computing (TDSC), ACM Transactions on Privacy and Security (TOPS), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), Tsinghua Science and Technology (TST), Int'l Journal of Software Engineering and Knowledge Engineering (IJSEKE): Journal Reviewer

2023~

Selected projects from my Github, visit for more at https://github.com/E0HYL.

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FINER-explain
The framework to fine-tune existing malware/vulnerability classifiers with explanations and generate component-based explanations with feature attribution XAI methods, improving explanation fidelity and intelligibility. Refer to our CCS 2023 paper for more details.
tensorflow lime shap My Related Blogs: LIME & SHAP Toolkit GradientExplainer
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MsDroid
Represent android malware with a set of graphs, classify them with GNN, and explain the decisions with techniques including GNN-Explainer. Refer to our TDSC 2023 paper for more details.
pytorch pytorch-geometric My Related Blogs: GNN Basis PyG Dataset GNNExplainer
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AndrozooDownloader
Download datasets from Androzoo, differentiate by year as well as benign/malicious applications. Supports coroutines, proxies, breakpoint continuation, error retries, etc.
python asyncio
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AI4Code-Framework
This repo is no longer maintained but the Android malware feature extraction methods in related papers, i.e., Drebin, DAMD, MaMaDroid, Hindroid, and MsDroid, are ready to be used, which I re-implemented with androguard v3.4.
python androguard
  

Credit to - base theme design: Tyler Butler, See it on GitHub