Real-Time Network Attack Detection and APP Implementation for Wi-Fi Based IP Cameras Using Machine Learning 


Vol. 50,  No. 8, pp. 1279-1289, Aug.  2025
10.7840/kics.2025.50.8.1279


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  Abstract

Recent hacking attacks targeting IP cameras, and the resulting invasion of privacy issues have drawn attention. In particular, there have been frequent cases where the IP addresses of leaked videos could not be identified, leaving victims unaware of their exposure. To address these issues, we propose a machine learning-based real-time network attack detection method. Using the CIC IoT 2023 open dataset, we analyze network traffic and design an APP capable of detecting attacks based on the MAC address of the user’s IP camera. The proposed APP provides immediate alerts to users upon attack detection and includes a network log monitoring feature. This study aims to enhance the overall security of IoT environments by offering a real-time security solution that enables IP camera users to detect and respond to network attacks quickly.

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[IEEE Style]

M. Choi, A. Cho, S. Lee, "Real-Time Network Attack Detection and APP Implementation for Wi-Fi Based IP Cameras Using Machine Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 8, pp. 1279-1289, 2025. DOI: 10.7840/kics.2025.50.8.1279.

[ACM Style]

Minyoung Choi, Ahyoung Cho, and Sunwoo Lee. 2025. Real-Time Network Attack Detection and APP Implementation for Wi-Fi Based IP Cameras Using Machine Learning. The Journal of Korean Institute of Communications and Information Sciences, 50, 8, (2025), 1279-1289. DOI: 10.7840/kics.2025.50.8.1279.

[KICS Style]

Minyoung Choi, Ahyoung Cho, Sunwoo Lee, "Real-Time Network Attack Detection and APP Implementation for Wi-Fi Based IP Cameras Using Machine Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 8, pp. 1279-1289, 8. 2025. (https://doi.org/10.7840/kics.2025.50.8.1279)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880