A deep recurrent neural network based approach for internet of things malware threat hunting
Abstract Internet of Things (IoT) devices are increasingly deployed in different industries and
for different purposes (eg sensing/collecting of environmental data in both civilian and …
for different purposes (eg sensing/collecting of environmental data in both civilian and …
Robust malware detection for internet of (battlefield) things devices using deep eigenspace learning
A Azmoodeh, A Dehghantanha… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Internet of Things (IoT) in military settings generally consists of a diverse range of Internet-
connected devices and nodes (eg, medical devices and wearable combat uniforms). These …
connected devices and nodes (eg, medical devices and wearable combat uniforms). These …
Machine learning algorithm for malware detection: Taxonomy, current challenges, and future directions
Malware has emerged as a cyber security threat that continuously changes to target
computer systems, smart devices, and extensive networks with the development of …
computer systems, smart devices, and extensive networks with the development of …
Distributed deep neural-network-based middleware for cyber-attacks detection in smart IoT ecosystem: A novel framework and performance evaluation approach
Cyberattacks always remain the major threats and challenging issues in the modern digital
world. With the increase in the number of internet of things (IoT) devices, security challenges …
world. With the increase in the number of internet of things (IoT) devices, security challenges …
MTHAEL: Cross-architecture IoT malware detection based on neural network advanced ensemble learning
D Vasan, M Alazab, S Venkatraman… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The complexity, sophistication, and impact of malware evolve with industrial revolution and
technology advancements. This article discusses and proposes a robust cross-architecture …
technology advancements. This article discusses and proposes a robust cross-architecture …
A novel detection and multi-classification approach for IoT-malware using random forest voting of fine-tuning convolutional neural networks
The Internet of Things (IoT) is prone to malware assaults due to its simple installation and
autonomous operating qualities. IoT devices have become the most tempting targets of …
autonomous operating qualities. IoT devices have become the most tempting targets of …
An ensemble of deep recurrent neural networks for detecting IoT cyber attacks using network traffic
M Saharkhizan, A Azmoodeh… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Internet-of-Things (IoT) devices and systems will be increasingly targeted by cybercriminals
(including nation state-sponsored or affiliated threat actors) as they become an integral part …
(including nation state-sponsored or affiliated threat actors) as they become an integral part …
Malware detection in internet of things (IoT) devices using deep learning
Internet of Things (IoT) devices usage is increasing exponentially with the spread of the
internet. With the increasing capacity of data on IoT devices, these devices are becoming …
internet. With the increasing capacity of data on IoT devices, these devices are becoming …
Detection of botnet attacks against industrial IoT systems by multilayer deep learning approaches
Industry 4.0 is the next revolution in manufacturing technology that is going to change the
production and distribution of goods and services within the following decade. Powered by …
production and distribution of goods and services within the following decade. Powered by …
MCFT-CNN: Malware classification with fine-tune convolution neural networks using traditional and transfer learning in Internet of Things
S Kumar - Future Generation Computer Systems, 2021 - Elsevier
With ever-increasing, internet-connected devices provide an opportunity to fulfil the
attacker's malicious intention. They use malicious programs to compromise the devices and …
attacker's malicious intention. They use malicious programs to compromise the devices and …