Machine learning approaches to IoT security: A systematic literature review

R Ahmad, I Alsmadi - Internet of Things, 2021 - Elsevier
With the continuous expansion and evolution of IoT applications, attacks on those IoT
applications continue to grow rapidly. In this systematic literature review (SLR) paper, our …

[HTML][HTML] A survey of IoT malware and detection methods based on static features

QD Ngo, HT Nguyen, VH Le, DH Nguyen - ICT express, 2020 - Elsevier
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 …

A survey on IoT intrusion detection: Federated learning, game theory, social psychology, and explainable AI as future directions

S Arisdakessian, OA Wahab, A Mourad… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
In the past several years, the world has witnessed an acute surge in the production and
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …

Deep learning based cross architecture internet of things malware detection and classification

R Chaganti, V Ravi, TD Pham - Computers & Security, 2022 - Elsevier
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 …

The Circle of life: A {large-scale} study of the {IoT} malware lifecycle

O Alrawi, C Lever, K Valakuzhy, K Snow… - 30th USENIX Security …, 2021 - usenix.org
Our current defenses against IoT malware may not be adequate to remediate an IoT
malware attack similar to the Mirai botnet. This work seeks to investigate this matter by …

Iot malware analysis using federated learning: A comprehensive survey

M Venkatasubramanian, AH Lashkari, S Hakak - IEEE Access, 2023 - ieeexplore.ieee.org
The Internet of Things (IoT) has paved the way to a highly connected society where all things
are interconnected and exchanging information has become more accessible through the …

Industrial internet-of-things security enhanced with deep learning approaches for smart cities

N Magaia, R Fonseca, K Muhammad… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
The significant evolution of the Internet of Things (IoT) enabled the development of
numerous devices able to improve many aspects in various fields in the industry for smart …

A multi-perspective malware detection approach through behavioral fusion of api call sequence

E Amer, I Zelinka, S El-Sappagh - Computers & Security, 2021 - Elsevier
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 …

Attention-based multidimensional deep learning approach for cross-architecture IoMT malware detection and classification in healthcare cyber-physical systems

V Ravi, TD Pham, M Alazab - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A literature survey shows that the number of malware attacks is gradually growing over the
years due to the growing trend of Internet of Medical Things (IoMT) devices. To detect and …

[HTML][HTML] Tools and Techniques for Collection and Analysis of Internet-of-Things malware: A systematic state-of-art review

S Madan, S Sofat, D Bansal - Journal of King Saud University-Computer …, 2022 - Elsevier
IoT devices which include wireless sensors, software, actuators, and computer devices
operated through the Internet, enable the transfer of data among objects or people …