Supervised learning algorithms have shown limited use in the field of anomaly detection due
to the unpredictability and difficulty in acquiring abnormal samples. In recent years …

With the increasing use of mobile devices, malware attacks are rising, especially on Android
phones, which account for 72.2% of the total market share. Hackers try to attack …

With the rapid expansion of the use of smartphone devices, malicious attacks against
Android mobile devices have increased. The Android system adopted a wide range of …

Despite the recency of their conception, Generative Adversarial Networks (GANs) constitute
an extensively-researched machine learning sub-field for the creation of synthetic data …

Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …

Smartphones have become an integral part of our daily lives thanks to numerous reasons.
While benefitting from what they offer, it is critical to be aware of the existence of malware in …

Generative Adversarial Networks (GANs) have seen significant interest since their
introduction in 2014. While originally focused primarily on image-based tasks, their capacity …

Android reflects a revolution in handhelds and mobile devices. It is a virtual machine based,
an open source mobile platform that powers millions of smartphone and devices and even a …

Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …

Abstract Machine learning is significantly used for malware and adversary detection in the
industrial internet of things networks. However, majority of these methods require a …