This flowchart outlines Zero Trust Architecture (ZTA), a cybersecurity framework that eliminates implicit trust and continuously verifies user and device access. 2.2. The Role of AI in Cybersecurity . Cybersecurity has experienced a radical change because artificial intelligence allows better threat detection combined

With the power of Classification Algorithms in Machine Learning, we will explore in this paper an alternative solution to save time and effort and help maintain the same security posture with less human intervention.

A. Machine Learning algorithms In order to implement machine-learning-based zero-trust framework, we have evaluated the following algorithms to choose the highest accuracy and using the TON_IoT network dataset: • Isolation Forest • KNN • COF • LOF a) Isolation Forest Isolation forest is an algorithm that utilises the use of binary

AI and Machine Learning are pivotal in transforming Zero Trust Security into a dynamic, adaptive defense strategy against evolving cyber threats. By harnessing AI-driven insights and ML-powered analytics, organizations can fortify their cybersecurity posture, elevate threat detection capabilities, and safeguard sensitive data effectively in ...

Machine learning algorithms are also scaling to detect and uncover every active unusual command, unusual privileges requested and used, unusual accounts deployed, unusual resource access histories, and others.

This research paper proposes a machine-learning (ML)-based zero-trust framework that utilises an anomaly detection algorithm. The output of the anomalous detection would inform the observers the trustworthiness of systems in their environments.

The convergence of Zero Trust Network Access (ZTNA) and Machine Learning (ML) presents a compelling opportunity for organizations to enhance anomaly detection capabilities within their dynamic ...

Jul 25, 2024 · More robust and dynamic security paradigms like zero trust network access (ZTNA) are needed. As organizations adopt ZTNA, artificial intelligence (AI) and machine learning (ML) are emerging as pivotal technologies that can significantly enhance the implementation and maturation of these frameworks.

In the Zero-Trust Security context, where each access request is meticulously scrutinized and nothing is trusted by default, artificial intelligence and machine learning elevate decision-making to unprecedented levels of efficiency and efficacy.

Nov 1, 2024 · By analyzing recent advancements, the paper highlights how AI and ML can automate threat detection, streamline access control, and provide real-time security analytics, thereby improving the...