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arXiv · 2504.08227

DaemonSec: Examining the Role of Machine Learning for Daemon Security in Linux Environments

Sheikh Muhammad Farjad
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Abstract

DaemonSec is an early-stage startup exploring machine learning (ML)-based security for Linux daemons, a critical yet often overlooked attack surface. While daemon security remains underexplored, conventional defenses struggle against adaptive threats and zero-day exploits. To assess the perspectives of IT professionals on ML-driven daemon protection, a systematic interview study based on semi-structured interviews was conducted with 22 professionals from industry and academia. The study evaluates adoption, feasibility, and trust in ML-based security solutions. While participants recognized the potential of ML for real-time anomaly detection, findings reveal skepticism toward full automation, limited security awareness among non-security roles, and concerns about patching delays creating attack windows. This paper presents the methods, key findings, and implications for advancing ML-driven daemon security in industry.

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Sheikh Muhammad Farjad. 2025-04-11. DaemonSec: Examining the Role of Machine Learning for Daemon Security in Linux Environments. https://arxiv.org/abs/2504.08227

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