Due to a lack of security design as well as the specific characteristics of IoT devices such as
the heterogeneity of processor architecture, IoT malware detection has to deal with very …

IoT devices which include wireless sensors, software, actuators, and computer devices
operated through the Internet, enable the transfer of data among objects or people …

The number of publicly exposed Internet of Things (IoT) devices has been increasing, as
more number of these devices connected to the internet with default settings. The devices …

We explore the task of Android malware detection based on dynamic analysis of application
activity sequences using deep learning techniques. We show that analyzing a sequence of …

Security of networking in cyber-physical systems is an important feature in recent computing.
Information that comes to the network needs preevaluation. Our solution presented in this …

Cryptomining malware (also referred to as cryptojacking) has changed the cyber threat
landscape. Such malware exploits the victim's CPU or GPU resources with the aim of …

The complexity, sophistication, and impact of malware evolve with industrial revolution and
technology advancements. This article discusses and proposes a robust cross-architecture …

The widespread development of the malware industry is considered the main threat to our e-
society. Therefore, malware analysis should also be enriched with smart heuristic tools that …

In the last few years, attackers have been shifting aggressively to the IoT devices in
industrial Internet of things (IIoT). Particularly, IoT botnet has been emerging as the most …

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 …