49 citations · 96 across the 5 of their papers we have counts for
8 papers
WhyGen: Explaining ML-powered Code Generation by Referring to Training Examples
Weixiang Yan, Yuanchun Li
Deep learning has demonstrated great abilities in various code generation tasks. However, despite the great convenience for some developers, many are concerned that the code genera…
DistFL: Distribution-aware Federated Learning for Mobile Scenarios
Bingyan Liu, Yifeng Cai, Ziqi Zhang +5
Federated learning (FL) has emerged as an effective solution to decentralized and privacy-preserving machine learning for mobile clients. While traditional FL has demonstrated its…
ModelDiff: Testing-Based DNN Similarity Comparison for Model Reuse Detection
Yuanchun Li, Ziqi Zhang, Bingyan Liu +2
The knowledge of a deep learning model may be transferred to a student model, leading to intellectual property infringement or vulnerability propagation. Detecting such knowledge r…
DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection
Yuanchun Li, Jiayi Hua, Haoyu Wang +2
Deep learning models are increasingly used in mobile applications as critical components. Unlike the program bytecode whose vulnerabilities and threats have been widely-discussed,…
Dynamic Slicing for Deep Neural Networks
Ziqi Zhang, Yuanchun Li, Yao Guo +2
Program slicing has been widely applied in a variety of software engineering tasks. However, existing program slicing techniques only deal with traditional programs that are constr…
Beyond the Virus: A First Look at Coronavirus-themed Mobile Malware
Liu Wang, Ren He, Haoyu Wang +8
As the COVID-19 pandemic emerged in early 2020, a number of malicious actors have started capitalizing the topic. Although a few media reports mentioned the existence of coronaviru…