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Artificial Intelligence Methods and Techniques to Cybersecurity

Submission Deadline: 10 November 2025 View: 581 Submit to Special Issue

Guest Editors

Prof. José Braga de Vasconcelos

Email: jose.vasconcelos@ulusofona.pt

Affiliation: Faculty of Natural Sciences, Engineering and Tecnology ,Lusófona University, 400098, Porto, Portugal

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Research Interests: Knowledge Management, Knowledge Engineering, Software Engineering, Data Science, Artificial Intelligence, Machine Learning

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Dr. Hugo Barbosa

Email: hugo.barbosa@ulusofona.pt

Affiliation: Faculty of Natural Sciences, Engineering and Tecnology ,Lusófona University, 400098, Porto, Portugal

Homepage:

Research Interests: Cybersecurity, Computer Networks, Serious Games, Virtual Reality, Simulation, Player Adaptability

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Summary

The rapid evolution of cyber threats, including sophisticated phishing attacks, ransomware, and advanced persistent threats, demands innovative defense mechanisms. Artificial Intelligence (AI) has emerged as a transformative technology in cybersecurity, offering automated threat detection, intelligent risk assessment, and real-time response mechanisms to mitigate cyber risks effectively.


This Special Issue aims to explore cutting-edge AI techniques and methodologies applied to digital privacy and security. It will bring together researchers, industry professionals, and policymakers to present the latest advancements in AI-driven cybersecurity solutions, from deep learning-based intrusion detection to AI-powered encryption and anomaly detection. The issue will also examine ethical considerations, privacy risks, and the balance between AI-driven security and user rights.


Suggested Themes:

AI-powered threat detection and prevention in cybersecurity

Machine learning for anomaly and intrusion detection

AI-driven privacy-preserving techniques

Deep learning applications in digital forensics and malware analysis

The role of AI in identity management and authentication security

Ethical AI in cybersecurity: bias, fairness, and privacy concerns

AI for cloud security, IoT security, and blockchain-based protection

Adversarial AI and its implications for digital security


Keywords

Artificial Intelligence, Cybersecurity, Machine Learning, Security, Threat Detection, IoT, Cloud Security, Privacy, Data Encryption

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