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 …
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 …
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 …
Deep learning based cross architecture internet of things malware detection and classification
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 …
more number of these devices connected to the internet with default settings. The devices …
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 …
DeepPower: Non-intrusive and deep learning-based detection of IoT malware using power side channels
The vulnerability of Internet of Things (IoT) devices to malware attacks poses huge
challenges to current Internet security. The IoT malware attacks are usually composed of …
challenges to current Internet security. The IoT malware attacks are usually composed of …
IMIDS: An intelligent intrusion detection system against cyber threats in IoT
The increasing popularity of the Internet of Things (IoT) has significantly impacted our daily
lives in the past few years. On one hand, it brings convenience, simplicity, and efficiency for …
lives in the past few years. On one hand, it brings convenience, simplicity, and efficiency for …
Generative adversarial network to detect unseen Internet of Things malware
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 …
industrial internet of things networks. However, majority of these methods require a …
CNN-based malware variants detection method for internet of things
Q Li, J Mi, W Li, J Wang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Malware has become one of the most serious security threats to the Internet of Things (IoT).
Detection of malware variants can inhibit the spread of malicious code from the traditional …
Detection of malware variants can inhibit the spread of malicious code from the traditional …
On-device malware detection using performance-aware and robust collaborative learning
The proliferation of the Internet-of-Things (IoT) devices has facilitated smart connectivity and
enhanced computational capabilities. Lack of proper security protocols in such devices …
enhanced computational capabilities. Lack of proper security protocols in such devices …