Results 201 to 210 of about 141,441 (275)
Meta Reinforcement Learning for Automated Cyber Defence
Applied AI Letters, Volume 7, Issue 1, February 2026.ABSTRACT Reinforcement learning (RL) solutions have shown considerable promise for automating the defense of networks to cyber attacks. However, a limitation to their real world deployment is the sample efficiency and generalizability of RL agents. This means that even small changes to attack types require a new agent to be trained from scratch.
Andrew Thomas, Nick Tillyer
wiley +1 more source
Cardiac devices and cyber attacks: How far are they real? How to overcome? [PDF]
Indian Heart J, 2019 Kapoor A, Vora A, Yadav R.
europepmc +1 more source
Multi‐Agent Reinforcement Learning for Cyber Defence Transferability and Scalability
Applied AI Letters, Volume 7, Issue 1, February 2026.A method for using mutli‐agent reinforcement learning that allows for zero shot transfer across network setups. Diagrams show the local observation construction, training and agent mapping process. The results for novel 15 and 30 node networks show effective transfer and improved scaling performance. ABSTRACT Reinforcement learning (RL) has shown to be
Andrew Thomas +2 more
wiley +1 more source
Crossing the third‐level digital divide through digital literacy programs
Journal of the Association for Information Science and Technology, Volume 77, Issue 2, Page 397-413, February 2026.Abstract Digital literacy programs (DLPs) implemented by community‐anchored organizations have become a key focus toward achieving digital equity. However, there is a notable lack of quantitative empirical research that measures DLPs' effectiveness in supporting the achievement of tangible benefits of digital literacy (DL), beyond simply acquiring it ...
Yeweon Kim +2 more
wiley +1 more source
Engineering Reports, Volume 8, Issue 2, February 2026.This study introduces a two‐phase method for detecting DDoS attacks in cloud environments using ensemble feature fusion and a hybrid CNN‐LSTM model. By combining meta‐heuristic feature selection with deep learning, the approach achieves over 99% accuracy on benchmark datasets, reducing false positives and improving cybersecurity resilience.
Hind Saad Hussein +3 more
wiley +1 more source
Energy Science &Engineering, Volume 14, Issue 2, Page 780-792, February 2026.ABSTRACT System dynamics uncertainties and cyberattacks pose significant challenges to load frequency control in power systems. This paper presents a data‐driven load frequency control strategy for interconnected multi‐area power systems subject to denial‐of‐service attacks that disrupt both feedforward and feedback communication channels.
Yuhao Chen +4 more
wiley +1 more source
Energy Science &Engineering, Volume 14, Issue 2, Page 1036-1066, February 2026.Digital Twin (DT) technology enhances building energy efficiency by enabling continuous monitoring, predictive maintenance, and operational optimization within Building Energy Management Systems. Through real‐time data integration and simulation, DTs provide dynamic feedback loops that optimize performance, reduce operational costs, and improve ...
Suqi Wang +6 more
wiley +1 more source
Journal of Software: Evolution and Process, Volume 38, Issue 2, February 2026.ABSTRACT As software applications get increasingly connected and complex, cybersecurity becomes more and more important to consider during development and evaluation. Software engineers need to be aware of various security threats and the countermeasures that can be taken to mitigate them.
Raffaela Groner +5 more
wiley +1 more source
Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ₁ Regularization. [PDF]
Sensors (Basel), 2018 Hernandez-Suarez A +6 more
europepmc +1 more source