activity
20172022
most citedAn Empirical Evaluation of GDPR Compliance Violations in Android mHealth Apps

14 citations · 84 across the 12 of their papers we have counts for

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Showing cs.CRShow all

8 papers · 1 filter

cs.CR20216 cited

SEC4SR: A Security Analysis Platform for Speaker Recognition

Guangke Chen, Zhe Zhao, Fu Song +3

Adversarial attacks have been expanded to speaker recognition (SR). However, existing attacks are often assessed using different SR models, recognition tasks and datasets, and only…

cs.CR20203 cited

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…

cs.CR2020

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…

cs.CR20206 cited

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…

cs.CR2020

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…

cs.CR20195 cited

A Large-Scale Empirical Study on Industrial Fake Apps

Chongbin Tang, Sen Chen, Lingling Fan +4

While there have been various studies towards Android apps and their development, there is limited discussion of the broader class of apps that fall in the fake area. Fake apps and…