14 citations · 84 across the 12 of their papers we have counts for
5 papers · 1 filter
SeqMobile: A Sequence Based Efficient Android Malware Detection System Using RNN on Mobile Devices
Ruitao Feng, Jing Qiang Lim, Sen Chen +2
With the proliferation of Android malware, the demand for an effective and efficient malware detection system is on the rise. The existing device-end learning based solutions tend…
An Empirical Evaluation of GDPR Compliance Violations in Android mHealth Apps
Ming Fan, Le Yu, Sen Chen +6
The purpose of the General Data Protection Regulation (GDPR) is to provide improved privacy protection. If an app controls personal data from users, it needs to be compliant with G…
A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devices
Ruitao Feng, Sen Chen, Xiaofei Xie +3
Currently, Android malware detection is mostly performed on server side against the increasing number of malware. Powerful computing resource provides more exhaustive protection fo…
Advanced Evasion Attacks and Mitigations on Practical ML-Based Phishing Website Classifiers
Yusi Lei, Sen Chen, Lingling Fan +2
Machine learning (ML) based approaches have been the mainstream solution for anti-phishing detection. When they are deployed on the client-side, ML-based classifiers are vulnerable…
Why an Android App is Classified as Malware? Towards Malware Classification Interpretation
Bozhi Wu, Sen Chen, Cuiyun Gao +4
Machine learning (ML) based approach is considered as one of the most promising techniques for Android malware detection and has achieved high accuracy by leveraging commonly-used…