Smartphone app usage analysis: datasets, methods, and applications

T Li, T **a, H Wang, Z Tu, S Tarkoma… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
As smartphones have become indispensable personal devices, the number of smartphone
users has increased dramatically over the last decade. These personal devices, which are …

User profiling from their use of smartphone applications: A survey

S Zhao, S Li, J Ramos, Z Luo, Z Jiang, AK Dey… - Pervasive and Mobile …, 2019 - Elsevier
The number and popularity of smartphone applications is rising dramatically. Users install
and use applications depending on their needs and interests. Applications on smartphones …

To what extent we repeat ourselves? Discovering daily activity patterns across mobile app usage

T Li, Y Li, MA Hoque, T **a… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the prevalence of smartphones, people have left abundant behavior records in
cyberspace. Discovering and understanding individuals' cyber activities can provide useful …

Understanding the long-term evolution of mobile app usage

T Li, Y Fan, Y Li, S Tarkoma… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The prevalence of smartphones has promoted the popularity of mobile apps in recent years.
Although significant effort has been made to understand mobile app usage, existing studies …

A privacy-preserving federated learning system for android malware detection based on edge computing

RH Hsu, YC Wang, CI Fan, B Sun, T Ban… - 2020 15th Asia Joint …, 2020 - ieeexplore.ieee.org
This paper presents a privacy-preserving federated learning (PPFL) system for the detection
of android malware. The proposed PPFL allows mobile devices to collaborate together for …

Deepapp: a deep reinforcement learning framework for mobile application usage prediction

Z Shen, K Yang, W Du, X Zhao, J Zou - Proceedings of the 17th …, 2019 - dl.acm.org
This paper aims to predict the apps a user will open on her mobile device next. Such an
information is essential for many smartphone operations, eg, app pre-loading and content …

” what apps did you use?”: Understanding the long-term evolution of mobile app usage

T Li, M Zhang, H Cao, Y Li, S Tarkoma… - Proceedings of the web …, 2020 - dl.acm.org
The prevalence of smartphones has promoted the popularity of mobile apps in recent years.
Although significant effort has been made to understand mobile app usage, existing studies …

When sharing economy meets iot: Towards fine-grained urban air quality monitoring through mobile crowdsensing on bike-share system

D Wu, T **ao, X Liao, J Luo, C Wu, S Zhang… - Proceedings of the …, 2020 - dl.acm.org
Air pollution is a serious global issue impacting public health and social economy. In
particular, exposure to small particulate matter of 2.5 microns or less in diameter (PM2. 5) …

A parallel genetic algorithm framework for transportation planning and logistics management

DI Arkhipov, D Wu, T Wu, AC Regan - Ieee Access, 2020 - ieeexplore.ieee.org
Small to medium sized transportation and logistics companies are usually constrained by
limited computing and IT professional resources on implementing an efficient parallel …

Fedhgcdroid: An adaptive multi-dimensional federated learning for privacy-preserving android malware classification

C Jiang, K Yin, C **a, W Huang - Entropy, 2022 - mdpi.com
With the popularity of Android and its open source, the Android platform has become an
attractive target for hackers, and the detection and classification of malware has become a …