TY - GEN
T1 - Convolutional Neural Network Based Classification of WeChat Mini-Apps
AU - Jin, Yihao
AU - Liu, Xuanyu
AU - Fu, Xiao
AU - Luo, Bin
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In recent years, a novel mobile computing paradigm has been evolving rapidly, with a host app allowing users to install and run mini-apps inside the app itself. However, the current classification mechanism of mini-apps is blurry and coarse-grained, making users unable to clearly understand mini-app functions, which can result in a series of privacy issues. In this study, an automatic convolutional neural network (CNN)-based classification approach is proposed for Wechatmini-apps. The proposed method integrates the static and dynamic features of WeChat mini-apps to achieve precise classification. Our approach was evaluated in a real-world testbed and the results showed that it can effectively classify Wechatmini-apps into proper categories, helping users better understand the functions of WeChat mini-apps while reducing user privacy violations.
AB - In recent years, a novel mobile computing paradigm has been evolving rapidly, with a host app allowing users to install and run mini-apps inside the app itself. However, the current classification mechanism of mini-apps is blurry and coarse-grained, making users unable to clearly understand mini-app functions, which can result in a series of privacy issues. In this study, an automatic convolutional neural network (CNN)-based classification approach is proposed for Wechatmini-apps. The proposed method integrates the static and dynamic features of WeChat mini-apps to achieve precise classification. Our approach was evaluated in a real-world testbed and the results showed that it can effectively classify Wechatmini-apps into proper categories, helping users better understand the functions of WeChat mini-apps while reducing user privacy violations.
KW - CNN
KW - Wechat
KW - mini-app classification
KW - mobile computing
UR - http://www.scopus.com/inward/record.url?scp=85178281628&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85178281628&partnerID=8YFLogxK
U2 - 10.1109/ICC45041.2023.10279007
DO - 10.1109/ICC45041.2023.10279007
M3 - Conference contribution
AN - SCOPUS:85178281628
T3 - IEEE International Conference on Communications
SP - 747
EP - 752
BT - ICC 2023 - IEEE International Conference on Communications
A2 - Zorzi, Michele
A2 - Tao, Meixia
A2 - Saad, Walid
T2 - 2023 IEEE International Conference on Communications, ICC 2023
Y2 - 28 May 2023 through 1 June 2023
ER -