Implementation of rate limiting and Telegram bot for HTTP GET Flood attack mitigation

Authors

  • Bagas Satya Dharma Universitas Merdeka Malang
  • Ahmad Rofiqul Muslikh Universitas Merdeka Malang

DOI:

https://doi.org/10.26905/jisad.v3i1.15398

Keywords:

cyber security, denial of service, rate limiting

Abstract

Distributed Denial of Service (DDoS) attacks pose a serious cybersecurity threat by overwhelming web servers with excessive traffic, rendering them inaccessible. One of the most common types is HTTP Flood, where massive HTTP GET and POST requests continuously drain server resources, leading to performance degradation or system failure. This study aims to analyze the impact of HTTP Flood DDoS attacks on web servers and evaluate the effectiveness of mitigation strategies using firewalls, rate limiting, and Telegram bot notifications. The research was conducted through experimental testing on an Apache server hosted on a Digital Ocean VPS, where server performance was measured before and after mitigation. The results indicate that a combination of firewalls configured with iptables and rate limiting successfully reduced CPU load by over 90%, maintaining server stability even under attack. Additionally, Telegram bot played a crucial role in real-time attack detection and response, enabling administrators to take immediate action. In conclusion, the applied mitigation techniques effectively reduced the impact of DDoS attacks and enhanced server resilience.

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References

[1] F. A. A. Putra, A. R. Jatmiko, R. M. A. Arief, and M. I. A. Ardiansa, “Rancang Bangun Sistem Informasi Kepegawaian dan Inventaris Di Universitas Merdeka Malang Berbasis Web Menggunakan Framework Codeigniter,” Jurnal RESTIKOM : Riset Teknik Informatika dan Komputer, vol. 5, no. 2, 2023, doi: 10.52005/restikom.v5i2.149.

[2] F. Hamdani, Y. B. Fitriana, and N. Oper, “Analisis Keamanan Website Terhadap Serangan DDOS Menggunakan Metode National Institute of Standards and Technology (NIST),” KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 3, no. 6, 2023.

[3] N. Mamuriyah, S. E. Prasetyo, and A. O. Sijabat, “Rancangan Sistem Keamanan Jaringan dari serangan DDoS Menggunakan Metode Pengujian Penetrasi,” Jurnal Teknologi Dan Sistem Informasi Bisnis, vol. 6, no. 1, 2024, doi: 10.47233/jteksis.v6i1.1124.

[4] E. Nofarita, “Implementasi Aplikasi Software Natural Network Mendeteksi Tingkatan Serangan DDoS Pada Jaringan Komputer,” Elkom : Jurnal Elektronika dan Komputer, vol. 14, no. 2, 2021, doi: 10.51903/elkom.v14i2.501.

[5] M. N. Faiz, O. Somantri, and A. W. Muhammad, “Rekayasa Fitur Berbasis Machine Learning untuk Mendeteksi Serangan DDoS,” Jurnal Nasional Teknik Elektro dan Teknologi Informasi, vol. 11, no. 3, 2022, doi: 10.22146/jnteti.v11i3.3423.

[6] S. Park, Y. Kim, H. Choi, Y. Kyung, and J. Park, “HTTP DDoS flooding attack mitigation in software-defined networking,” IEICE Trans Inf Syst, vol. E104D, no. 9, 2021, doi: 10.1587/transinf.2021EDL8022.

[7] N. Sugianti, Y. Galuh, S. Fatia, and K. F. H. Holle, “Deteksi Serangan Distributed Denia of Services (DDOS) Berbasis HTTP Menggunakan Metode Fuzzy Sugeno,” JISKA (Jurnal Informatika Sunan Kalijaga), vol. 4, no. 3, 2020, doi: 10.14421/jiska.2020.43-03.

[8] F. Nisa and S. Ramadona, “Sistem Pencegahan Serangan Distributed Denial Of Service Pada Jaringan SDN,” Jurnal Sistim Informasi dan Teknologi, vol. 5, no. 3, 2023.

[9] J. Hansen and T. Sutabri, “Mendesain Cyber Security Untuk Mencegah Serangan DDoS Pada Website Menggunakan Metode Captcha,” Digital Transformation Technology, vol. 3, no. 1, 2023.

[10] D. Firdaus, I. Sumardi, and G. Nugraha, “Peningkatan Keamanan Server GraphQL Terhadap Serangan DDOS Dengan Tipe Batch Attack Menggunakan Metode Rate Limiting,” Cyber Security dan Forensik Digital, vol. 7, no. 2, pp. 62–68, 2024, doi: 10.14421/csecurity.2024.7.2.4718.

[11] A. El Kamel, “A GNN-Based Rate Limiting Framework for DDoS Attack Mitigation in Multi-Controller SDN,” in Proceedings - IEEE Symposium on Computers and Communications, 2023. doi: 10.1109/ISCC58397.2023.10218204.

[12] M. T. A. Zaen, A. Tantoni, and M. Ashari, “DDoS Attack Mitigation With Intrusion Detection System (IDS) Using Telegram Bots,” JISA(Jurnal Informatika dan Sains), vol. 4, no. 2, 2021, doi: 10.31326/jisa.v4i2.1043.

[13] I. D. Wiradyaksa, D. H. Putri, R. M. Iqbal, N. H. Astari, N. Karna, and F. Dewanta, “Design and Implementation of Automated Web Application Firewall, Rate Limiting, and Intrusion Detection System for Cyber Defense,” in 2024 8th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE), IEEE, Aug. 2024, pp. 256–261. doi: 10.1109/ICITISEE63424.2024.10730693.

[14] Y. Arta, R. Wandri, A. Hanafiah, B. K. Pranoto, and M. R. Fadhilah, “Analisa Perbandingan Web Server Untuk Kebutuhan Open Journal System (OJS) Menggunakan Secure Tunnel,” CogITo Smart Journal, vol. 8, no. 2, 2022, doi: 10.31154/cogito.v8i2.407.537-548.

[15] G. Fanani and I. Riadi, “Analysis of Digital Evidence on Denial of Service (DoS) Attack Log Based,” Buletin Ilmiah Sarjana Teknik Elektro, vol. 2, no. 2, 2020, doi: 10.12928/biste.v2i2.1065.

[16] R. I. P. Siagian, F. A. Lubis, M. A. Syuja, and D. Kiswanto, “Analisis Performa Sistem Operasi Manjaro Linux Dalam Lingkungan Komputasi Desktop Virtual,” JATI (Jurnal Mahasiswa Teknik Informatika), vol. 9, no. 1, pp. 1266–1272, 2025, doi: 10.36040/jati.v9i1.12668.

[17] B. Jaya, Y. Yuhandri, and S. Sumijan, “Peningkatan Keamanan Router Mikrotik Terhadap Serangan Denial of Service (DoS),” Jurnal Sistim Informasi dan Teknologi, 2020, doi: 10.37034/jsisfotek.v2i4.32.

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Published

2025-04-21

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