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Florida Atlantic Undergraduate Research Journal

College

College of Engineering and Computer Science

Department

Electrical Engineering and Computer Science

Co-Author Type 1

Graduate Student

Keywords

Cybersecurity, Internet of Things (IoT), Intrusion Detection Systems (IDS), Zeek, Network security, Network traffic analysis, cyberattack, detection, real-time, threat, reconnaissance, Denaial of Service (DoS), Distributed Denial of Service (DDoS), Brute-force, attack, Man-in-the-Middle (MitM), Spoofing, Botnets, malware, network, pseudocode, open-source, security

Document Type

Article

Abstract

As cybersecurity threats increase in scale and complexity, the ability to distinguish hostile traffic from benign network activity is essential. This research examines five prevalent cyberattack categories that impact IoT environments and outlines detection strategies utilizing the open-source Intrusion Detection System (IDS) Zeek. This study provides practical detection methods designed for scalable, real-time environments by classifying five commonly encountered attacks, namely: Reconnaissance, Denial of Service (DoS) and Distributed Denial of Service (DDoS), Brute Force, Man-in-the-Middle (MitM) and Spoofing, and Botnet and Malware Behavior. For each attack, we analyze the prevalence, operational impact, and associated indicators. We also present Zeekbased pseudocode strategies structured by attack type. The findings emphasize the value of detection mechanisms and emphasize Zeek’s versatility across IoT networks.

Advisors

Imadeldin Mahgoub

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