About our lab: SQSLab, short for Software Quality and Security, is interested in working with emerging problems in the era of cloud computing and big data analysis. Particular topics include Software Engineering, Performance Guarantee in Cloud Computing, Mobile Security and Energy Saving on Mobile Devices.
For software engineering, we mainly focus on software analysis and testing techniques. We developed a model-based continuous verification system, Eunomia, to bi-directionally verify the consistency between software model with its implementation.
For mobile security, we are working on malware detection and classification. KuafuDet is developed for android malware detection using machine learning in the adversarial environment; and Begonia is developed to trade off the classification accuracy and time cost through Pareto ensemble learning .
We are still looking for new talented Masters and Ph.D. students.
Please send me email(firstname.lastname@example.org).
Lingling Fan, Ting Su, Sen Chen, Guozhu Meng, Yang Liu, Lihua Xu, Geguang Pu and Zhendong Su, "Large-Scale Analysis of Framework-Specific Exceptions in Android Apps", The 40th International Conference on Software Engineering (ICSE), 2018. (acceptance rate: 20%)
Sen Chen, Minhui Xue, Lingling Fan, Shuang Hao, Lihua Xu, Haojin Zhu, and Li Bo, "Automated Poisoning Attacks and Defenses in Malware Detection System: An Adversarial Machine Learning Approach", Elsevier Computers & Security, 2017. (accepted)
Wenqi Bu, Minhui Xue, Lihua Xu, Yajin Zhou, Zhushou Tang, and Tao Xie. When Program Analysis Meets Mobile Security: An Industrial Study of Misusing Android Internet Sockets. In Proc. ESEC/FSE, Industrial Track, 2017.
Fei Xu, Fangming Liu, Hai Jin, Heterogeneity and Interference-Aware Virtual Machine Provisioning for Predictable Performance in the Cloud, IEEE Transactions on Computers, 2016.
Congratulations to Sen Chen, who has received the MobiCom 2016 Travel Grant Award, ACM/SIGMOBILE, August, 2016.