Dr. Guozhu Meng obtained his Ph.D degree from the School of Computer Science and Engineering, Nanyang Technological University, Singapore at 2017. His supervisors are Assoc Prof. Liu Yang and Assoc Prof. Zhang Jie. In addition, he has been working closely with Dr. Xue Yinxing.
He joined Institute of Information Engineering of Chinese Academy of Sciences as Associate Professor in 2018. His research focuses on system security with a specialization on mobile computing as follows:
Android security. Conducted a work to analyze Android malware and detect malware (ISSTA 2016 paper, IJCNN 2016 paper), and a work to evaluate existing anti-malware tools (AsiaCCS 2016 paper). Another work has been done, with regard to Android ecosystem, to analyze the spread model of Android malware across multiple markets, and security patches of apps across verions.
Big data analysis. We have collected millions of Android apps and malware, and conducted a work to try to learn knowledge from the big data such as bug detection and crash analysis (FSE 2017 paper, ICSE 2018 paper), automated GUI code generation (ICSE 2018 paper), malware characteristics, evolution and trend. The main techniques include machine learning, deep learning and statistics inference.
Mobile energy analysis and optimization. We have conducted a work to study the issues of power consumption, and propose optimizing solutions to raise the efficiency of battery on mobile device (TMC 2016 paper, ICCPS 2017 paper). In addition, we carry on a work to detect energy bugs in Android apps in order to optimize energy usage at application level.
Vulnerability detection. We attempt to detect vulnerabilities existing in Android OS and Android apps. We have instrumented Android OS and Android apps to mark the execution path and trace, and employed testing technology to explore all possible execution paths. We have started to work on the detection of logic vulnerability in Android OS, and security flaws in some security-critical apps such as financial apps.
- Our paper “RoLMA: A Practical Adversarial Attack against Deep Learning-based LPR Systems” has been accepted for publication in Inscrypt 2019.
- Won 2019 ACM SIGSAC China Arising Star Award.
- Our paper “Characterizing Android Signature Issues” has been accepted for publication in ASE 2019.
- We are organizing an issus on “Data-driven Security” for Cybersecurity journal with Dr. Liu Yang, Dr. Ou xinming, and Dr. Xing Xinyu. Please refer to the following link about this issue. https://mp.weixin.qq.com/s/hn8wUtyTnpay_yDcuWj5KA. All the intiative and empirical artifacts on security are welcome.
- The 2th International Workshop on Advances in Mobile App Analysis is open, please submit your paper at the following link: https://2019.ase-conferences.org/home/a-mobile-2019#Call-for-Papers (A-Mobile: https://a-mobile.github.io/)
- Our paper “Securing Android App Markets via Modelling and Predicting Malware Spread between Markets” has been accepted for publication in the IEEE Transactions on Information Forensics and Security.
- We are organizing an exciting workshop on mobile app analysis (A-Mobile: https://a-mobile.github.io/ as a satellite event of the prestigious software engineering conference ASE 2018. We welcome all relevant submissions via easychair link: https://easychair.org/conferences/?conf=amobile2018
- Our ICSE 2018 paper "Larget-Scale Analysis of Framework-Specific Exceptions in Android Apps" won ACM SIGSOFT Distinguished Paper Award
- Our two research papers on empirical study of framework exception in Android, and deep learning based code generation from Android GUI designs is accepted by ICSE 2018
- Our Automated Android App Testing tool-Stoat won the First Prize of Tool Demo in NASAC 2017
- Our research paper on mining design templates for Java projects is accepted by ASE 2017
- Our research paper on model-based Android app testing is accepted by ESEC/FSE 2017