AI-Enhanced Linux Security and Server Hardening

Authors: Sandeep Phanireddy

DOI: https://doi.org/10.5281/zenodo.15086765

Short DOI: https://doi.org/g89tmt

Country: United States

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Abstract: Linux has long been celebrated for its stability, versatility, and open-source community support. However, even robust Unix-like systems face threats ranging from opportunistic malware to sophisticated nation-state attacks. Traditional server hardening practices file permission lockdowns, process whitelisting, configuration auditing still matters but can be overwhelmed by the complexity of large-scale or fast-changing infrastructures. This paper explores how AI techniques complement established security measures, from anomaly detection in logs to intelligent process monitoring. By marrying core Unix security principles with machine learning (ML)–based analytics, organizations can safeguard mission-critical servers from zero-day exploits, stealthy intrusions, and misconfigurations. We discuss real-world use cases, highlight key tools, and share recommended workflows to deploy AI-driven threat prevention on Linux systems.

Keywords: Linux Security, Server Hardening, AI-driven Detection, Machine Learning, SELinux, Anomaly Detection, Threat Intelligence, Zero-Day Exploits, Infrastructure-as-Code.

Paper Id: 232286

Published On: 2020-05-22

Published In: Volume 8, Issue 3, May-June 2020

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