Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review

A Heidari, NJ Navimipour, M Unal - Sustainable Cities and Society, 2022 - Elsevier
The goal of managing smart cities and societies is to maximize the efficient use of finite
resources while enhancing the quality of life. To establish a sustainable urban existence …

Machine-learned wearable sensors for real-time hand-motion recognition: toward practical applications

KR Pyun, K Kwon, MJ Yoo, KK Kim… - National Science …, 2024 - academic.oup.com
Soft electromechanical sensors have led to a new paradigm of electronic devices for novel
motion-based wearable applications in our daily lives. However, the vast amount of random …

[HTML][HTML] Securing the digital world: Protecting smart infrastructures and digital industries with artificial intelligence (AI)-enabled malware and intrusion detection

M Schmitt - Journal of Industrial Information Integration, 2023 - Elsevier
The last decades have been characterized by unprecedented technological advances,
many of them powered by modern technologies such as Artificial Intelligence (AI) and …

Cloud-based intrusion detection approach using machine learning techniques

H Attou, A Guezzaz, S Benkirane… - Big Data Mining and …, 2023 - ieeexplore.ieee.org
Cloud computing (CC) is a novel technology that has made it easier to access network and
computer resources on demand such as storage and data management services. In …

Machine learning in network anomaly detection: A survey

S Wang, JF Balarezo, S Kandeepan… - IEEe …, 2021 - ieeexplore.ieee.org
Anomalies could be the threats to the network that have ever/never happened. To protect
networks against malicious access is always challenging even though it has been studied …

[HTML][HTML] A survey on intrusion detection systems for fog and cloud computing

V Chang, L Golightly, P Modesti, QA Xu, LMT Doan… - Future Internet, 2022 - mdpi.com
The rapid advancement of internet technologies has dramatically increased the number of
connected devices. This has created a huge attack surface that requires the deployment of …

Cybersecurity of multi-cloud healthcare systems: A hierarchical deep learning approach

L Gupta, T Salman, A Ghubaish, D Unal, AK Al-Ali… - Applied Soft …, 2022 - Elsevier
With the increase in sophistication and connectedness of the healthcare networks, their
attack surfaces and vulnerabilities increase significantly. Malicious agents threaten patients' …

A feature similarity machine learning model for ddos attack detection in modern network environments for industry 4.0

S Sambangi, L Gondi, S Aljawarneh - Computers and Electrical …, 2022 - Elsevier
Recent advancements in artificial intelligence and machine learning technologies have laid
the flagstone for the fourth industrial revolution, Industry 4.0. The industry 4.0 is at a very …

Cloud network anomaly detection using machine and deep learning techniques-recent research advancements

A Abdallah, A Alkaabi, G Alameri, SH Rafique… - IEEE …, 2024 - ieeexplore.ieee.org
In the rapidly evolving landscape of computing and networking, the concepts of cloud
networks have gained significant prominence. Although the cloud network offers on-demand …

[HTML][HTML] Comprehensive review on intelligent security defences in cloud: Taxonomy, security issues, ML/DL techniques, challenges and future trends

MM Belal, DM Sundaram - Journal of King Saud University-Computer and …, 2022 - Elsevier
Nowadays, machine learning and deep learning algorithms are used in recent studies as
active security techniques instead of traditional ones to secure the cloud environment based …