Android is the most popular mobile operating system with a market share of over 80%[1].
Due to its popularity and also its open source nature, Android is now the platform most …

The convergence of extremely high levels of hardware concurrency and the effective overlap
of computation and communication in asynchronous executions has resulted in increasing …

Malware classification for the Android ecosystem can be performed using a range of
techniques. One major technique that has been gaining ground recently is dynamic analysis …

This paper presents graphkit-learn, the first Python library for efficient computation of graph
kernels based on linear patterns, able to address various types of graphs. Graph kernels …

Graph kernels are powerful tools to bridge the gap between machine learning and data
encoded as graphs. Most graph kernels are based on the decomposition of graphs into a set …

Malicious applications have become increasingly numerous. This demands adaptive,
learning-based techniques for constructing malware detection engines, instead of the …

Malware threats are continuing to grow in volume and sophistication. Current anti-virus
software is ineffective on the new generation malware threats. Ongoing developments in …

Graphs are able to represent a wide range of real-world data due to the nature of their
structure and their rich expressiveness. With the advance of state-of-the-artmachine learning …

The Android operating system, as well as smartphone apps for just about everything, is
widely available in the official Google Play store and several third-party markets …

Because optical diffusion imaging is a highly nonlinear inverse problem, iterative inversion
algorithms based on the Born approximation have usually been employed as reconstruction …