A comprehensive survey on deep learning based malware detection techniques
M Gopinath, SC Sethuraman - Computer Science Review, 2023 - Elsevier
Recent theoretical and practical studies have revealed that malware is one of the most
harmful threats to the digital world. Malware mitigation techniques have evolved over the …
harmful threats to the digital world. Malware mitigation techniques have evolved over the …
Machine learning in IoT security: Current solutions and future challenges
The future Internet of Things (IoT) will have a deep economical, commercial and social
impact on our lives. The participating nodes in IoT networks are usually resource …
impact on our lives. The participating nodes in IoT networks are usually resource …
Federated deep learning for zero-day botnet attack detection in IoT-edge devices
Deep learning (DL) has been widely proposed for botnet attack detection in Internet of
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …
Hybrid deep learning for botnet attack detection in the internet-of-things networks
Deep learning (DL) is an efficient method for botnet attack detection. However, the volume of
network traffic data and memory space required is usually large. It is, therefore, almost …
network traffic data and memory space required is usually large. It is, therefore, almost …
Machine learning for intrusion detection in industrial control systems: Applications, challenges, and recommendations
Methods from machine learning are used in the design of secure Industrial Control Systems.
Such methods focus on two major areas: detection of intrusions at the network level using …
Such methods focus on two major areas: detection of intrusions at the network level using …
Intelligent dynamic malware detection using machine learning in IP reputation for forensics data analytics
In the near future, objects have to connect with each other which can result in gathering
private sensitive data and cause various security threats and cyber crimes. To prevent cyber …
private sensitive data and cause various security threats and cyber crimes. To prevent cyber …
A new network forensic framework based on deep learning for Internet of Things networks: A particle deep framework
With the prevalence of Internet of Things (IoT) systems, inconspicuous everyday household
devices are connected to the Internet, providing automation and real-time services to their …
devices are connected to the Internet, providing automation and real-time services to their …
Deep-learning-enabled security issues in the internet of things
Z Lv, L Qiao, J Li, H Song - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
In order to explore the application value of deep learning denoising autoencoder (DAE) in
Internet-of-Things (IoT) fusion security, in this study, a hierarchical intrusion security …
Internet-of-Things (IoT) fusion security, in this study, a hierarchical intrusion security …
Reliability in Internet of Things: Current status and future perspectives
L Xing - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) aims to transform the human society toward becoming intelligent,
convenient, and efficient with potentially enormous economic and environmental benefits …
convenient, and efficient with potentially enormous economic and environmental benefits …
A systematic review on Deep Learning approaches for IoT security
The constant spread of smart devices in many aspects of our daily life goes hand in hand
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …