Rising sophistication in cyber threats vs. advancements in AI cybersecurity 

✅ Confronting the Reproducibility Crisis: A Case Study of Challenges in Cybersecurity AI

science

:2405.18753v2 Announce Type: cross Abstract: In the rapidly evolving field of cybersecurity, ensuring the reproducibility of AI-driven research is critical to maintaining the reliability and integrity of security systems. This paper addresses the reproducibility crisis within the domain of adversarial robustness -- a key area in AI-based cybersecurity that focuses on defending deep neural networks against malicious perturbations. Through a detailed case study, we attempt to validate results from prior work on certified robustness using the VeriGauge toolkit, revealing significant challenges due to software and hardware incompatibilities, version conflicts, and obsolescence. Our findings underscore the urgent need for standardized methodologies, containerization, and comprehensive documentation to ensure the reproducibility of AI models deployed in critical cybersecurity applications.

arXiv     Aug 20, 2024