Deep reinforcement learning in production systems: a systematic literature review

M Panzer, B Bender - International Journal of Production Research, 2022 - Taylor & Francis
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …

[HTML][HTML] Industrial cyber-physical systems protection: A methodological review

R Canonico, G Sperlì - Computers & Security, 2023 - Elsevier
Ubiquitous utilization of Information and Communication Technologies in modern
manufacturing plants has transformed them into Cyber-Physical Systems (CPSs), making …

Deep Q-network-based heuristic intrusion detection against edge-based SIoT zero-day attacks

S Shen, C Cai, Z Li, Y Shen, G Wu, S Yu - Applied Soft Computing, 2024 - Elsevier
How to process and classify zero-day attacks due to their huge damage to social Internet of
Things (SIoT) systems has become a hot research issue. To solve this issue, we propose a …

[HTML][HTML] Adversarial machine learning in industry: A systematic literature review

FV Jedrzejewski, L Thode, J Fischbach, T Gorschek… - Computers & …, 2024 - Elsevier
Abstract Adversarial Machine Learning (AML) discusses the act of attacking and defending
Machine Learning (ML) Models, an essential building block of Artificial Intelligence (AI). ML …

Possible applications of edge computing in the manufacturing industry—systematic literature review

K Kubiak, G Dec, D Stadnicka - Sensors, 2022 - mdpi.com
This article presents the results of research with the main goal of identifying possible
applications of edge computing (EC) in industry. This study used the methodology of …

Security in internet of things: a review on approaches based on blockchain, machine learning, cryptography, and quantum computing

S Cherbal, A Zier, S Hebal, L Louail… - The Journal of …, 2024 - Springer
Abstract The Internet of Things (IoT) is an important virtual network that allows remote users
to access linked multimedia devices. The development of IoT and its ubiquitous application …

Toward deep transfer learning in industrial internet of things

X Liu, W Yu, F Liang, D Griffith… - IEEE Internet of things …, 2021 - ieeexplore.ieee.org
Machine learning techniques have been widely adopted to assist in data analysis in a
variety of Internet of Things (IoT) systems. To enable flexible use of trained learning models …

Healthcare internet of things: Security threats, challenges and future research directions

M Adil, MK Khan, N Kumar, M Attique… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Internet of Things (IoT) applications are switching from general to precise in different
industries, eg, healthcare, automation, military, maritime, smart cities, transportation …

Attrition: Attacking static hardware trojan detection techniques using reinforcement learning

V Gohil, H Guo, S Patnaik, J Rajendran - Proceedings of the 2022 ACM …, 2022 - dl.acm.org
Stealthy hardware Trojans (HTs) inserted during the fabrication of integrated circuits can
bypass the security of critical infrastructures. Although researchers have proposed many …

Deep learning for the security of software-defined networks: a review

R Taheri, H Ahmed, E Arslan - Cluster Computing, 2023 - Springer
As the scale and complexity of networks grow rapidly, management, maintenance, and
optimization of them are becoming increasingly challenging tasks for network administrators …