Cybersecurity Perspective
Cybersecurity research is intensely focused on leveraging artificial intelligence (AI) to enhance defenses and understand evolving threats. Current efforts concentrate on applying machine learning algorithms, including deep learning models like convolutional neural networks, transformers, and generative adversarial networks, to tasks such as intrusion detection, phishing website identification, and vulnerability analysis. This work is crucial for improving the security of diverse systems, from individual computers to critical infrastructure, and for developing more robust and adaptable security measures against increasingly sophisticated attacks. The integration of AI also necessitates research into ethical considerations, explainability of AI-driven security decisions, and the potential for AI itself to become a target for malicious actors.
Papers
Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness
David Fernández Llorca, Ronan Hamon, Henrik Junklewitz, Kathrin Grosse, Lars Kunze, Patrick Seiniger, Robert Swaim, Nick Reed, Alexandre Alahi, Emilia Gómez, Ignacio Sánchez, Akos Kriston
SISSA: Real-time Monitoring of Hardware Functional Safety and Cybersecurity with In-vehicle SOME/IP Ethernet Traffic
Qi Liu, Xingyu Li, Ke Sun, Yufeng Li, Yanchen Liu
A Review of Digital Twins and their Application in Cybersecurity based on Artificial Intelligence
MohammadHossein Homaei, Oscar Mogollon Gutierrez, Jose Carlos Sancho Nunez, Mar Avila Vegas, Andres Caro Lindo
Artificial Intelligence Ethics Education in Cybersecurity: Challenges and Opportunities: a focus group report
Diane Jackson, Sorin Adam Matei, Elisa Bertino