Autors: Ilieva, R. I., Stoilova, G. O.
Title: Challenges of AI-Driven Cybersecurity
Keywords: Adversarial Attacks, Arms Race, Artificial Intelligence (AI), Cybersecurity, Machine learning, Model Vulnerabilities

Abstract: Artificial intelligence (AI) has significantly transformed the cybersecurity landscape, offering enhanced threat detection, predictive analytics, and automated responses. However, this integration also introduces a range of complex challenges. This abstract explores the multifaceted problems associated with AI-driven cybersecurity, including the susceptibility of AI models to adversarial attacks, inherent vulnerabilities, and ethical concerns related to data privacy and bias. Additionally, it addresses the escalating arms race between cybersecurity professionals and malicious actors employing sophisticated AI techniques. Understanding and mitigating these issues is crucial for effectively leveraging AI's potential to secure digital environments.

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Issue

2024 33rd International Scientific Conference Electronics, ET 2024 - Proceedings, pp. 1-4, 2024, Bulgaria, https://doi.org/10.1109/ET63133.2024.10721572

Copyright IEEE Explore

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Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus