The various application markets are facing an exponential growth of Android malware. Every
day, thousands of new Android malware applications emerge. Android malware hackers …

Neural architecture search (NAS) has achieved great success in different computer vision
tasks such as object detection and image recognition. Moreover, deep learning models have …

Mobile apps have the potential to request access to private information. Given the far-
reaching negative consequences that misuse of this kind of information can lead to …

Incentivized by monetary gain, some app developers launch fraudulent campaigns to boost
their apps' rankings in the mobile app stores. They pay some service providers for boost …

" Incentivized" advertising platforms allow mobile app developers to acquire new users by
directly paying users to install and engage with mobile apps (eg, create an account, make in …

Download fraud is a prevalent threat in mobile App markets, where fraudsters manipulate
the number of downloads of Apps via various cheating approaches. Purchased fake …

The difficulty of large-scale monitoring of app markets affects our understanding of their
dynamics. This is particularly true for dimensions such as app update frequency, control and …

Browser extensions are popular small applications that allow users to enrich their browsing
experience. Yet browser extensions pose security concerns because they can leak user …

In this paper, we present a framework for fraud intention recognition of public transport bus
operators based on a deep learning approach using a stack of denoising and sparse …

We introduce the fraud de-anonymization problem, that goes beyond fraud detection, to
unmask the human masterminds responsible for posting search rank fraud in online …