Welcome to CURIOSITY!
CURIOSITY is a cybersecurity research group led by Prof. Zhenkai Liang at NUS.
Our research mainly focuses on system security, covering provenance, anomaly detection, trusted computing, Android malware detection, cyber range and attack replay, vulnerability detection and management, program analysis, fuzzing and testing, AI for security, etc.
Group Motto: Understanding systems, abstracting knowledge, and connecting facts.
理解系统，提炼知识，参悟规律。
Latest News
🎉 Our recent work on high-assurance system observability protection is accepted in CCS'24!
🎉 Our recent work on mobile malware detection is accepted in ASE'24!
🎉 Our recent work on cryptographic misuse detection is accepted in RAID'24!
🎉 Our recent work on kernel vulnerability reproduction is accepted in RAID'24 and wins the Best Practical Paper Award!
🎉 Our VulZoo vulnerability intelligence dataset is released!
🎉 Our recent work on Android UI similarity is accepted in USENIX Security'24!
Selected Publications
Refer to this link for the full list of publications.
The HitchHiker's Guide to High-Assurance System Observability Protection with Efficient Permission Switches
In Proceedings of the 31th ACM Conference on Computer and Communications Security, 2024.
MaskDroid: Robust Android Malware Detection with Masked Graph Representations
In Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering, 2024.
CrypTody: Cryptographic Misuse Analysis of IoT Firmware via Data-flow Reasoning
In 27th International Symposium on Research in Attacks, Intrusions and Defenses (RAID 2024).
KernJC: Automated Vulnerable Environment Generation for Linux Kernel Vulnerabilities
In 27th International Symposium on Research in Attacks, Intrusions and Defenses (RAID 2024).
UIHASH: Detecting Similar Android UIs through Grid-Based Visual Appearance Representation
In Proceedings of the 33rd USENIX Security Symposium, 2024.
Detecting Logic Bugs in Graph Database Management Systems via Injective and Surjective Graph Query Transformation
In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024.
Learning Graph-based Code Representations for Source-level Functional Similarity Detection
In Proceedings of the 45th International Conference on Software Engineering, 2023.
PalanTír: Optimizing Attack Provenance with Hardware-enhanced System Observability
In Proceedings of the 29th ACM Conference on Computer and Communications Security, 2022.
FlowMatrix: GPU-Assisted Information-Flow Analysis through Matrix-Based Representation
In Proceedings of the 31st USENIX Security Symposium, 2022.
Tell: Log Level Suggestions via Modeling Multi-level Code Block Information
In Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, 2022.
ShadeWatcher: Recommendation-guided Cyber Threat Analysis using System Audit Records
In Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022.
Watson: Abstracting Behaviors from Audit logs via Aggregation of Contextual Semantics
In Proceedings of the 28th Annual Network and Distributed System Security Symposium, 2021.