CV

You can also find my CV in the PDF file [CV]

Education

• B.S. in School Software Engineering, Tianjin University, 2009
• M.S. in School of Computer Science and Technology, Tianjin University, 2012
• Ph.D in School of Computer Science and Engineering, Nanyang Technological University, 2017

Work experience

• Visting Research Fellow (2017.09.01 - 2017.11.31)
  • University of Luxembourg, Luxembourg
  • Duties included: Android vulnerbaility analysis, detection, automated exploit generation
  • Supervisor: Prof. Sjourke Mauw, Dr. Olga Gadyatskaya
• Research Fellow (2017.08 - )
  • Nanyang Technological University, Singapore
  • Duties included: Android security, including malware detection and generation, Android testing, large-scale app analysis (e.g., financial apps), Android performance analysis
  • Supervisor: Dr. Liu Yang
• Research Associate (2013.02 - 2017.07)
  • Nanyang Technological University, Singapore
  • Duties included: Android security, including malware detection and generation, Android testing, large-scale app analysis (e.g., financial apps), Android performance analysis
  • Supervisor: Dr. Liu Yang
• Associate Scientist (2011.12 - 2013.01)
  • National University of Singapore, Singapore
  • Duties included: Formal verification of web authentication protocol
  • Supervisor: Dr. Liu Yang

Publications

AuthScan: Automatic Extraction of Web Authentication Protocols from Implementations

Collaborative Security: A Survey and Taxonomy

Mystique: Evolving Android Malware for Auditing Anti-Malware Tools

Semantic Modelling of Android Malware for Effective Malware Comprehension, Detection, and Classification

Contextual Weisfeiler-Lehman Graph Kernel for Malware Detection

Auditing Anti-Malware Tools by Evolving Android Malware and Dynamic Loading Technique

Battery State-of-Health Estimation for Mobile Devices

Battery-Aware Mobile Data Service

Guided, Stochastic Model-Based GUI Testing of Android Apps

Mining Implicit Design Templates for Actionable Code Reuse

AndroVault: Constructing Knowledge Graph from Millions of Android Apps for Automated Analysis

Large-Scale Analysis of Framework-Specific Exceptions in Android Apps

From UI Design Image to GUI Skeleton: A Neural Machine Translator to Bootstrap Mobile GUI Implementation

DroidEcho: An In-depth Dissection of Malicious Behaviors in Android Applications

Efficiently Manifesting Asynchronous Programming Errors in Android Apps

Are Mobile Banking Apps Secure? What can be Improved?

Securing Android App Markets via Modelling and Predicting Malware Spread between Markets

Securing Android Applications via Edge Assistant Third-party Library Detection

Large-Scale Empirical Studies on Effort-Aware Security Vulnerability Prediction Methods

Characterizing Android App Signing Issues

RoLMA: A Practical Adversarial Attack against Deep Learning-based LPR Systems

An Empirical Assessment of Security Risks of Global Android Banking Apps

A Large-Scale Empirical Study on Vulnerability Distribution within Projects and the Lessons Learned

A3IDENT: A Two-phased Approach to Identify the Leading Authors of Android Apps

A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devices

Towards Security Threats of Deep Learning Systems: A Survey

Have You been Properly Notified? Automatic Compliance Analysis of Privacy Policy Text with GDPR Article 13

SEPAL: Towards a Large-scale Analysis of SEAndroid Policy Customization

DRMI: A Dataset Reduction Technology based on Mutual Information for Black-box Attacks

VALL-NUT: Principled Anti-Greybox-Fuzzing

Why is Your Trojan NOT Responding? A Quantitative Analysis of Failures in Backdoor Attacks of Neural Networks

Learning Program Semantics with Code Representations: An Empirical Study

MalRadar: Demystifying Android Malware in the New Era

TransRepair: Context-aware Program Repair for Compilation Errors

Understanding Real-world Threats to Deep Learning Models in Android Apps

GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Search

ContraBERT: Enhancing Code Pre-trained Models via Contrastive Learning

Aliasing Backdoor Attacks on Pre-trained Models

Differential Testing of Cross Deep Learning Framework APIs: Revealing Inconsistencies and Vulnerabilities

Good-looking but Lacking Faithfulness: Understanding Local Explanation Methods through Trend-based Testing

Talks

Mystique: Evolving Android Malware for Auditing Anti-Malware Tools

June 01, 2016

Conference Proceedings Talk at Xi'an, China, Xi'an, China

Semantic Modelling of Android Malware for Malware Comprehension, Detection, and Classification

July 06, 2016

Conference proceedings talk at Saarland University, Germany, Saarland, Germany

Ensuring Android Security: From Malware Detection, Anvirus Software Assessment, to Android Security Testing

June 16, 2017

Conference proceedings talk at University of Beihang, Beijing, China, Beijing, China

Guided, Stochastic Model-based GUI Testing of Android Apps

September 19, 2017

Conference proceedings talk at University of Luxembourg, Luxembourg, Luxembourg

Taming the Stubbon in Android Apps: Malware, Crashes, and Vulnerabilities

September 30, 2018

Invited Talk at Tianjin University, Tianjin, China

Taming the Stubbon in Android Apps: Malware, Crashes, and Vulnerabilities

October 19, 2018

Invited Talk at Southern University of Science and Technology, Shenzhen, China

Theories and Practices of the Intelligentization of System Security

July 21, 2019

Invited Talk at Zhejiang Hotel, Hangzhou, China

Teaching

Static Analysis for Mobile Applications Permalink

Mobile Application Security and Evaluation Permalink

Literature Reading Permalink

Mobile Application Security and Evaluation Permalink

Artificial Intelligence Security Permalink