Hi, Iām Yiling He š
- š Iām currently working on Code LLM applications, focusing on the problems of semantics preserving and robustness to drift
- š± Iām always learning recent advances in the related domains and never limit myself to one way
- šÆ Iām looking to collaborate on LLM-powered software security, e.g., for vulnerability detection, malware summary and defense
- š¬ Visit my previous blog at https://e0hyl.github.io/BLOG-OF-E0
- š« How to reach me: yiling-he@ucl.ac.uk (Research Fellow at University College London)
Selection of my recent publications here.
- DeUEDroid: Detecting Underground Economy Apps Based on UTG SimilarityIn Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2023
Experience including internships, services, education, and awards.
Education & Awards
University College London: Research Fellow
January, 2025 - nowS2Lab, Computer Science
Supervisor: Lorenzo CavallaroZhejiang University: PhD degree
September, 2021 - June, 2024Cyberspace Security, College of Computer Science
Supervisor: Kui Ren, Zhan QinZhejiang University: Master's (transferred to PhD in the spring semester)
September, 2019 - June, 2021Cyberspace Security, College of Computer Science
Supervisor: Kui Ren, Zhan QinBeijing University of Posts and Telecommunications: Bachelor degree
September, 2015 - June, 2019Information Security, School of Cyberspace Security
Internships
Tencent: Intelligent Security Research Group, Xuanwu Lab
March, 2021 - August, 2021Professional Services
USENIX Security Symposium (USENIX Security): External Reviewer
2025IEEE Symposium on Security and Privacy (IEEE S&P): External Reviewer
2025ACM SIGSAC Conference on Computer and Communications Security (CCS): External Reviewer
2024, 2022Tsinghua Science and Technology (TST): Reviewer
2025, 2024IEEE Transactions on Circuits and Systems for Video Technology (TCSVT): Reviewer
2024IEEE Transactions on Dependable and Secure Computing (TDSC): Reviewer
2023Selected projects from my Github, visit for more at https://github.com/E0HYL.
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
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
AndrozooDownloader
Download datasets from Androzoo, differentiate by year as well as benign/malicious applications. Supports coroutines, proxies, breakpoint continuation, error retries, etc.python asyncio
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