Objectives To investigate whether and what user data are collected by health related mobile
applications (mHealth apps), to characterise the privacy conduct of all the available mHealth …

The popularity and open‐source nature of Android devices have resulted in a dramatic
growth of Android malware. Malware developers are also able to evade the detection …

Mobile-application fingerprinting of network traffic is valuable for many security solutions as
it provides insights into the apps active on a network. Unfortunately, existing techniques …

Traffic classification groups similar or related traffic data, which is one main stream
technique of data fusion in the field of network management and security. With the rapid …

Modern smartphone platforms implement permission-based models to protect access to
sensitive data and system resources. However, apps can circumvent the permission model …

We present a scalable dynamic analysis frame-work that allows for the automatic evaluation
of the privacy behaviors of Android apps. We use our system to analyze mobile apps' …

The app economy is largely reliant on data collection as its primary revenue model. To
comply with legal requirements, app developers are often obligated to notify users of their …

China is one of the largest Android markets in the world. As Chinese users cannot access
Google Play to buy and install Android apps, a number of independent app stores have …

Network traffic classification has long been a pivotal topic in network security. In the past two
decades, methods like port-based classification, deep packet inspection, and machine …

Nowadays, security incidents have become a familiar" nuisance," and they regularly lead to
the exposure of private and sensitive data. The root causes for such incidents are rarely …