A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions

M Ozkan-Ozay, E Akin, Ö Aslan, S Kosunalp… - IEEE …, 2024 - ieeexplore.ieee.org
Given the continually rising frequency of cyberattacks, the adoption of artificial intelligence
methods, particularly Machine Learning (ML), Deep Learning (DL), and Reinforcement …

Local government cybersecurity landscape: A systematic review and conceptual framework

ST Hossain, T Yigitcanlar, K Nguyen, Y Xu - Applied Sciences, 2024 - mdpi.com
Local governments face critical challenges in the era of digital transformation, balancing the
responsibility of safeguarding resident information and administrative documents while …

Unbalanced web phishing classification through deep reinforcement learning

A Maci, A Santorsola, A Coscia, A Iannacone - Computers, 2023 - mdpi.com
Web phishing is a form of cybercrime aimed at tricking people into visiting malicious URLs to
exfiltrate sensitive data. Since the structure of a malicious URL evolves over time, phishing …

Enhancing cybersecurity capability investments: Evidence from an experiment

A Pigola, PR Da Costa, M Ferasso, LFC da Silva - Technology in Society, 2024 - Elsevier
In recent years, investments in cybersecurity capabilities (CC) have emerged as an essential
practice in reducing cyberattacks and optimizing the usage of technologies. Therefore …

Canaries and Whistles: Resilient Drone Communication Networks with (or without) Deep Reinforcement Learning

C Hicks, V Mavroudis, M Foley, T Davies… - Proceedings of the 16th …, 2023 - dl.acm.org
Communication networks able to withstand hostile environments are critically important for
disaster relief operations. In this paper, we consider a challenging scenario where drones …

Secure knowledge management and cybersecurity in the era of artificial intelligence

S Samtani, Z Zhao, R Krishnan - Information Systems Frontiers, 2023 - Springer
Over the past half-decade, numerous federal funding agencies such as the National Science
Foundation (NSF), National Academies of Science (NAS), and National Security and …

Simulated autonomous driving using reinforcement learning: A comparative study on unity's ML-agents framework

Y Savid, R Mahmoudi, R Maskeliūnas, R Damaševičius - Information, 2023 - mdpi.com
Advancements in artificial intelligence are leading researchers to find use cases that were
not as straightforward to solve in the past. The use case of simulated autonomous driving …

A Comprehensive Review on Cyber-attacks in Power Systems: Impact Analysis, Detection and Cyber security

N Tatipatri, SL Arun - IEEE Access, 2024 - ieeexplore.ieee.org
Continuous communication and information technology advancements facilitate the
modernization of the conventional energy grid into an integrated platform. Internet-of-Things …

[HTML][HTML] Improved sand cat swarm optimization with deep learning based enhanced malicious activity recognition for cybersecurity

N Almakayeel, EL Lydia - Alexandria Engineering Journal, 2024 - Elsevier
The main concept of a smart city is to join manual items with electronics, software, sensors,
and network connectivity for data contact via Internet of Things (IoT) gadgets. IoT improves …

Securing Patient Information in Connected Healthcare Systems in the Age of Pervasive Data Collection

A Dimitrievski, T Loncar-Turukalo… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
This paper explores the ethical and security challenges of integrating Internet of Things
technologies into health-care systems. We examine real-world ethical dilemmas, including …