Detecting cybersecurity attacks in internet of things using artificial intelligence methods: A systematic literature review

M Abdullahi, Y Baashar, H Alhussian, A Alwadain… - Electronics, 2022 - mdpi.com
In recent years, technology has advanced to the fourth industrial revolution (Industry 4.0),
where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have …

[HTML][HTML] The big picture on the internet of things and the smart city: a review of what we know and what we need to know

A Rejeb, K Rejeb, S Simske, H Treiblmaier, S Zailani - Internet of Things, 2022 - Elsevier
This study examines how the application of the IoT in smart cities is discussed in the current
academic literature. Based on bibliometric techniques, 1,802 articles were retrieved from the …

PPSF: A privacy-preserving and secure framework using blockchain-based machine-learning for IoT-driven smart cities

P Kumar, R Kumar, G Srivastava… - … on Network Science …, 2021 - ieeexplore.ieee.org
With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of
urbanization. IoT networks allow distributed smart devices to collect and process data within …

A survey on machine learning techniques for cyber security in the last decade

K Shaukat, S Luo, V Varadharajan, IA Hameed… - IEEE …, 2020 - ieeexplore.ieee.org
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …

CorrAUC: a malicious bot-IoT traffic detection method in IoT network using machine-learning techniques

M Shafiq, Z Tian, AK Bashir, X Du… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Identification of anomaly and malicious traffic in the Internet-of-Things (IoT) network is
essential for the IoT security to keep eyes and block unwanted traffic flows in the IoT …

A comprehensive study of DDoS attacks over IoT network and their countermeasures

P Kumari, AK Jain - Computers & Security, 2023 - Elsevier
IoT offers capabilities to gather information from digital devices, infer from their results, and
maintain and optimize these devices in different domains. IoT is heterogeneous in nature …

Cyber security in smart cities: a review of deep learning-based applications and case studies

D Chen, P Wawrzynski, Z Lv - Sustainable Cities and Society, 2021 - Elsevier
On the one hand, smart cities have brought about various changes, aiming to revolutionize
people's lives. On the other hand, while smart cities bring better life experiences and great …

An improved anomaly detection model for IoT security using decision tree and gradient boosting

M Douiba, S Benkirane, A Guezzaz… - The Journal of …, 2023 - Springer
Abstract Internet of Things (IoT) represents a massive deployment of connected, intelligent
devices that communicate directly in private, public, and professional environments without …

IoT malicious traffic identification using wrapper-based feature selection mechanisms

M Shafiq, Z Tian, AK Bashir, X Du, M Guizani - Computers & Security, 2020 - Elsevier
Abstract Machine Learning (ML) plays very significant role in the Internet of Things (IoT)
cybersecurity for malicious and intrusion traffic identification. In other words, ML algorithms …

TP2SF: A Trustworthy Privacy-Preserving Secured Framework for sustainable smart cities by leveraging blockchain and machine learning

P Kumar, GP Gupta, R Tripathi - Journal of Systems Architecture, 2021 - Elsevier
With the advancement in sensor technology and the proliferation of low-cost electronic
circuits, Internet of Things (IoT) is emerging as a promising technology for realization of …