Design of a Monitoring System for Detecting ARP Spoofing on a Rule-Based Wifi Network

Authors

  • Alfi Fahira Salsabila Universitas Ibrahimy, Situbondo, Jawa Timur, Indonesia
  • Ayu Dia Wulandari Universitas Ibrahimy, Situbondo, Jawa Timur, Indonesia
  • Ifda Khanifatu Zahro Universitas Ibrahimy, Situbondo, Jawa Timur, Indonesia
  • A Hamdani Universitas Ibrahimy, Situbondo, Jawa Timur, Indonesia

DOI:

https://doi.org/10.51903/4cykf888

Keywords:

ARP Spoofing, Rule-Based, Network Security, IDS, Wi-Fi

Abstract

The rapid development of information technology has increased the complexity of cybersecurity threats, including ARP spoofing attacks. This attack exploits the ARP protocol to intercept and modify network traffic, potentially leading to Man-in-the-Middle (MITM) attacks and data theft. This study aims to design and implement a multi-criteria security monitoring system capable of detecting ARP spoofing attacks in WiFi networks. The system was developed as an Intrusion Prevention System (IPS) that monitors ARP packets and applies detection rules, such as IP–MAC inconsistencies, excessive changes in network attributes, and abnormal packet frequency. Real-time notifications are sent to administrators when anomalies are detected. The research employed a Research and Development (R&D) approach, including requirements analysis, algorithm design for detection, and system testing. Experiments were conducted to evaluate detection effectiveness and memory efficiency. The results demonstrate that the system can accurately detect ARP spoofing while using memory efficiently. Its implementation reduces the risk of MITM attacks and data theft, making it suitable for deployment in campus and organizational networks. The contribution of this study lies in expanding the network security literature by focusing on ARP spoofing, which has received less attention than DNS spoofing and brute-force attacks. Future work suggests integrating rule-based methods with machine learning to enhance adaptability to emerging, complex attack patterns.

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Published

2026-01-21

Issue

Vol. 5 No. 1 (2026): January: Jurnal Ilmiah Sistem Informasi

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Articles

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Copyright (c) 2026 Alfi Fahira Salsabila, Ayu Dia Wulandari, Ifda Khanifatu Zahro, A Hamdani

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