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 …
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
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 …
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 …
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
The explosive growth of smart objects and their dependency on wireless technologies for
communication increases the vulnerability of Internet of Things (IoT) to cyberattacks …
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 …
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 …
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
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 …
IoT survey: An SDN and fog computing perspective
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 …
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 …
(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 …
significantly large amounts of data (commonly known as big data) being communicated and …