An explainable machine learning framework for intrusion detection systems

M Wang, K Zheng, Y Yang, X Wang - IEEE Access, 2020 - ieeexplore.ieee.org
In recent years, machine learning-based intrusion detection systems (IDSs) have proven to
be effective; especially, deep neural networks improve the detection rates of intrusion …

A deep recurrent neural network based approach for internet of things malware threat hunting

H HaddadPajouh, A Dehghantanha, R Khayami… - Future Generation …, 2018 - Elsevier
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 …

Exponential disruptive technologies and the required skills of industry 4.0

O Bongomin, G Gilibrays Ocen… - Journal of …, 2020 - Wiley Online Library
The 21st century has witnessed precipitous changes spanning from the way of life to the
technologies that emerged. We have entered a nascent paradigm shift (industry 4.0) where …

Internet of things forensics: Recent advances, taxonomy, requirements, and open challenges

I Yaqoob, IAT Hashem, A Ahmed, SMA Kazmi… - Future Generation …, 2019 - Elsevier
The explosive growth of smart objects and their dependency on wireless technologies for
communication increases the vulnerability of Internet of Things (IoT) to cyberattacks …

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 …

[HTML][HTML] An overview of shared mobility

CAS Machado, NPM de Salles Hue, FT Berssaneti… - Sustainability, 2018 - mdpi.com
In a wider understanding, shared mobility can be defined as trip alternatives that aim to
maximize the utilization of the mobility resources that a society can pragmatically afford …

A new network forensic framework based on deep learning for Internet of Things networks: A particle deep framework

N Koroniotis, N Moustafa, E Sitnikova - Future Generation Computer …, 2020 - Elsevier
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 …

IoT survey: An SDN and fog computing perspective

O Salman, I Elhajj, A Chehab, A Kayssi - Computer Networks, 2018 - Elsevier
Recently, there has been an increasing interest in the Internet of Things (IoT). While some
analysts disvalue the IoT hype, several technology leaders, governments, and researchers …

[HTML][HTML] Security requirements for the internet of things: A systematic approach

S Pal, M Hitchens, T Rabehaja, S Mukhopadhyay - Sensors, 2020 - mdpi.com
There has been a tremendous growth in the number of smart devices and their applications
(eg, smart sensors, wearable devices, smart phones, smart cars, etc.) in use in our everyday …

Fuzzy pattern tree for edge malware detection and categorization in IoT

EM Dovom, A Azmoodeh, A Dehghantanha… - Journal of Systems …, 2019 - Elsevier
The surging pace of Internet of Things (IoT) development and its applications has resulted in
significantly large amounts of data (commonly known as big data) being communicated and …