With the integration of mobile devices into daily life, smartphones are privy to increasing
amounts of sensitive information. Sophisticated mobile malware, particularly Android …

Context Static analysis exploits techniques that parse program source code or bytecode,
often traversing program paths to check some program properties. Static analysis …

The drastic increase of Android malware has led to a strong interest in develo** methods
to automate the malware analysis process. Existing automated Android malware detection …

Many program analyses require statically inferring the possible values of composite types.
However, current approaches either do not account for correlations between object fields or …

Most existing mobile malware detection methods (eg, Kirin and DroidMat) are designed
based on the resources required by malwares (eg, permissions, application programming …

Recent years have seen a global adoption of smart mobile devices, particularly those based
on Android. However, Android's widespread adoption is marred with increasingly rampant …

Android developers heavily use reflection in their apps for legitimate reasons, but also
significantly for hiding malicious actions. Unfortunately, current state-of-the-art static analysis …

It is generally challenging to tell apart malware from benign applications. To make this
decision, human analysts are frequently interested in runtime values: targets of reflective …

Due to the portability advantage, HTML5-based mobile apps are getting more and more
popular. Unfortunately, the web technology used by HTML5-based mobile apps has a …

In parallel with the meteoric rise of mobile software, we are witnessing an alarming
escalation in the number and sophistication of the security threats targeted at mobile …