Malware threats and detection for industrial mobile-IoT networks
Industrial IoT networks deploy heterogeneous IoT devices to meet a wide range of user
requirements. These devices are usually pooled from private or public IoT cloud providers. A …
requirements. These devices are usually pooled from private or public IoT cloud providers. A …
Malware detection in edge devices with fuzzy oversampling and dynamic class weighting
Abstract In Internet-of-things (IoT) domain, edge devices are used increasingly for data
accumulation, preprocessing, and analytics. Intelligent integration of edge devices with …
accumulation, preprocessing, and analytics. Intelligent integration of edge devices with …
Analyzing and detecting emerging Internet of Things malware: A graph-based approach
The steady growth in the number of deployed Internet of Things (IoT) devices has been
paralleled with an equal growth in the number of malicious software (malware) targeting …
paralleled with an equal growth in the number of malicious software (malware) targeting …
Iot botnet detection framework from network behavior based on extreme learning machine
IoT devices have been affected by fundamental security flaws in recent years, rendering
them exposed to various threats and viruses, particularly IoT botnets. In contrast to …
them exposed to various threats and viruses, particularly IoT botnets. In contrast to …
BoostedEnML: Efficient technique for detecting cyberattacks in IoT systems using boosted ensemble machine learning
Following the recent advances in wireless communication leading to increased Internet of
Things (IoT) systems, many security threats are currently ravaging IoT systems, causing …
Things (IoT) systems, many security threats are currently ravaging IoT systems, causing …
Detection of malicious activities in internet of things environment based on binary visualization and machine intelligence
H Naeem - Wireless Personal Communications, 2019 - Springer
Abstract Internet of Things (IoT) devices are increasingly deployed for different purposes
such as data sensing, collecting and controlling. IoT improves user experiences by allowing …
such as data sensing, collecting and controlling. IoT improves user experiences by allowing …
Detection of malware by deep learning as CNN-LSTM machine learning techniques in real time
MS Akhtar, T Feng - Symmetry, 2022 - mdpi.com
Cyber-attacks on the numerous parts of today's fast developing IoT are only going to
increase in frequency and severity. A reliable method for detecting malicious attacks such as …
increase in frequency and severity. A reliable method for detecting malicious attacks such as …
A multikernel and metaheuristic feature selection approach for IoT malware threat hunting in the edge layer
H Haddadpajouh, A Mohtadi… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Internet-of-Things (IoT) devices are increasingly targeted, partly due to their presence in a
broad range of applications (including home and corporate environments). In this article, we …
broad range of applications (including home and corporate environments). In this article, we …
Malware detection using genetic cascaded support vector machine classifier in Internet of Things
SK Gupta, B Pattnaik, V Agrawal… - 2022 Second …, 2022 - ieeexplore.ieee.org
The Internet of Things (IoT) is a network of computing devices that can transmit and obtain
data across a network without human intervention. In the last couple of decades, software …
data across a network without human intervention. In the last couple of decades, software …
DÏoT: A federated self-learning anomaly detection system for IoT
IoT devices are increasingly deployed in daily life. Many of these devices are, however,
vulnerable due to insecure design, implementation, and configuration. As a result, many …
vulnerable due to insecure design, implementation, and configuration. As a result, many …