الفهرس 
Material and MethodsOnly 14 pages are availabe for public view
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Abstract
As the digital landscape continues to expand, the interconnected nature of modern technology has brought about unprecedented efficiency and convenience [1]. At the forefront of this evolution is the Internet of Things (IoT), which has seamlessly integrated itself into nearly every aspect of human activity, from smart home systems to complex industrial processes.However, this rapid integration of digital technologies also presents a growing vector for cyber threats, which exploit the expanded attack surface presented by interconnected devices and networks [2].The increase in cyber threats is not only more frequent but also more sophisticated, targeting both the information and operational layers of organizations [3]. High-profile breaches and cyber-attacks have shown that the repercussions extend beyond immediate financial losses, posing serious risks to privacy, safety, and trust in digital systems [4]. Traditional cybersecurity measures, while foundational, are proving inadequate against adaptive cyber threats that evolve faster than these defenses can respond [5]. ntrusion Detection Systems (IDS) [6] are critical in this environment, serving as a necessary layer of intelligence that complements conventional security measures such as firewalls and antivirus software [7]. IDS are designed to detect unusual activities and potential threats, offering a proactive security posture. However, traditional IDS face significant challenges, including the management of high volumes of data, the detection of sophisticated, previously unknown attacks, and maintaining performance without overwhelming the systems they protect [8].