The application of emerging technologies, such as Artificial Intelligence (AI), entails risks that
need to be addressed to ensure secure and trustworthy socio-technical infrastructures …

We propose a security methodology for Machine Learning (ML) pipelines, supporting the
definition of key security properties of ML assets, the identification of threats to them as well …

This paper explores how the current paradigm of vulnerability management might adapt to
include machine learning systems through a thought experiment: what if flaws in machine …

" The Cyber Frontier: AI and ML in Next-Gen Threat Detection" explores the transformative
role of Artificial Intelligence (AI) and Machine Learning (ML) in revolutionizing cybersecurity …

In the contemporary digital landscape, the convergence of artificial intelligence (AI) and big
datatechnologies holds immense promise for revolutionizing cybersecurity practices and …

Cyber threats, particularly Advanced Persistent Threats (APTs), pose significant challenges
to organizations' cybersecurity posture. Traditional defense mechanisms often struggle to …

The development of today's critical infrastructure is increasingly dependent on smart
technology and interconnection of networks. This introduces many vulnerabilities to cyber …

The rapid evolution of information and communication technologies, notably the Internet,
has yielded substantial benefits while posing challenges to information system security. With …

This research investigates the tangible quantitative impacts of integrating Artificial
Intelligence (AI) into security frameworks. Quantitative analysis reveals a remarkable 30 …

Recent advancements in artificial intelligence (AI) technologies have induced tremendous
growth in innovation and automation. Although these AI technologies offer significant …