Journals / Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi / 2026 / Sayı: 10

Development of an Open-Source Firewall System Based on NanoPi R5S

NanoPi R5S Tabanlı Açık Kaynak Kodlu Bir Güvenlik Duvarı Sisteminin Geliştirilmesi

Ömer Aslan(BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ)0000-0003-0737-1966
Cihan Işik(MİLLİ SAVUNMA ÜNİVERSİTESİ, KARA ASTSUBAY MESLEK YÜKSEKOKULU, MÜDÜRLÜK)0000-0000-0000-0000
Pages
—
Publication Date
2026-07-07
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally, the study explores the potential benefits of this solution for individual users, small businesses, and educational institutions, concluding with practical recommendations for network security researchers and system administrators.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In recent years, the increasing prevalence of cyber threats has driven both individual and institutional users to seek more robust and flexible security solutions.
📊
Key Findings & Data:Within this landscape, solutions based on Mini PCs have gained significant traction among small and medium-sized enterprises and home users, owing to their compact form factor and adequate processing power.
💡
Conclusion & Impact:Finally, the study explores the potential benefits of this solution for individual users, small businesses, and educational institutions, concluding with practical recommendations for network security researchers and system administrators.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Açık Kaynak Kodlu Güvenlik Duvarı · NanoPi R5S · Ağ Güvenliği

Abstract

In recent years, the increasing prevalence of cyber threats has driven both individual and institutional users to seek more robust and flexible security solutions. Offering a compelling combination of flexibility and cost-effectiveness, open-source software presents a viable alternative to commercial firewall systems. Within this landscape, solutions based on Mini PCs have gained significant traction among small and medium-sized enterprises and home users, owing to their compact form factor and adequate processing power. This paper details the design and implementation of an open-source firewall system built on the NanoPi R5S platform. The system was configured using a suite of open-source tools to deliver secure internet access, filter malicious content, and perform network traffic analysis. Its performance was rigorously evaluated under various operational scenarios to analyze the efficiency of the NanoPi R5S hardware in a network security context. The NanoPi R5S architecture sustained robust security operations with minimal 7–12% CPU utilization. Compared to x86 alternatives, it achieved a 60–70% improvement in energy efficiency and 50% lower DNS latency. These findings proved that containerized security on low-power hardware offers high performance without the overhead or thermal footprint of traditional appliances. Finally, the study explores the potential benefits of this solution for individual users, small businesses, and educational institutions, concluding with practical recommendations for network security researchers and system administrators.

Özet

Son yıllarda siber tehditlerin artan yaygınlığı hem bireysel hem de kurumsal kullanıcıları daha sağlam ve esnek güvenlik çözümleri aramaya yöneltmiştir. Esneklik ve maliyet etkinliğini bir arada sunan açık kaynak kodlu yazılımlar, ticari güvenlik duvarı sistemlerine uygulanabilir bir alternatif oluşturmaktadır. Bu bağlamda, Mini PC tabanlı çözümler, kompakt form faktörleri ve yeterli işlem güçleri sayesinde küçük ve orta ölçekli işletmeler ile ev kullanıcıları arasında önemli bir ivme kazanmıştır. Bu makale, NanoPi R5S platformu üzerine inşa edilmiş açık kaynak kodlu bir güvenlik duvarı sisteminin tasarımını ve uygulamasını göstermektedir. Sistem, güvenli internet erişimi sağlamak, kötü amaçlı içerikleri filtrelemek ve ağ trafiği analizi gerçekleştirmek için bir dizi açık kaynak araç kullanılarak yapılandırılmıştır. NanoPi R5S donanımının bir ağ güvenliği bağlamındaki verimliliğini analiz etmek amacıyla sistemin performansı, çeşitli operasyonel senaryolar altında titizlikle değerlendirilmiştir. NanoPi R5S mimarisi, yalnızca %7–12 oranında minimum düzeyde CPU kullanımıyla güçlü güvenlik operasyonlarını sergilemiştir. X86 alternatifleriyle karşılaştırıldığında, enerji verimliliğinde %60–70 oranında iyileşme ve %50 daha düşük DNS gecikmesi sağlamıştır. Bu bulgular, düşük güçlü donanım üzerinde konteynerize edilmiş güvenliğin, geleneksel cihazların getirdiği yük veya termal ayak izi olmadan yüksek performans sunduğunu kanıtlamıştır. Son olarak çalışma, bu çözümün bireysel kullanıcılar, küçük işletmeler ve eğitim kurumları için potansiyel faydalarını incelemekte ve ağ güvenliği araştırmacıları ile sistem yöneticileri için pratik öneriler sunmaktadır.

🔖

Cite This Article

Aslan, Ö., Işik, C. (2026). Development of an Open-Source Firewall System Based on NanoPi R5S. Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi, Sayı: 10. https://doi.org/10.33461/uybisbbd.1912322

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (25)

  1. AdGuard. (2024). AdGuard Home Documentation. https://github.com/AdguardTeam/AdGuardHome
  2. Ahmad, I., Basheri, M., Iqbal, M. J., & Rahim, A. (2018). Performance comparison of support vector machine, random forest, and extreme learning machine for intrusion detection. IEEE access, 6, 33789-33795. https://doi.org/10.1109/ACCESS.2018.2841987
  3. Combs, G. (2021). Wireshark Network Analysis: The Official Wireshark Certified Network Analyst Study Guide. Protocol Analysis Institute. Google Scholar
  4. Conti, M., Dehghantanha, A., Franke, K., & Watson, S. (2018). Internet of Things security and forensics: Challenges and opportunities. Future Generation Computer Systems, 78, 544–546. https://doi.org/10.1016/j.future.2017.07.060
  5. Deeka, T., Deeka, B., & On-rit, S. (2025, November). Dockerized Microservices for Routing and Traffic Engineering in Complex Networks. In 2025 29th International Computer Science and Engineering Conference (ICSEC) (pp. 119-122). IEEE. https://doi.org/10.1109/ICSEC67360.2025.11298007
  6. Fernández Hansen, Y. (2019). The Hacker's Hardware Toolkit: best gadgets for Red Team hackers. Amazon
  7. FriendlyARM. (2024). NanoPi R5S
  8. Wiki. https://wiki.friendlyelec.com/wiki/index.php/NanoPi_R5S
  9. FriendlyWRT. (2024). FriendlyWRT Documentation for NanoPi
  10. R5S. https://wiki.friendlyelec.com/wiki/index.php/FriendlyWRT
  11. Gosálvez-White, I., Rodríguez-Martín, N., Barajas-García, N., Mena-Gallardo, C., & García- Teodoro, P. (2025). MEDIotWAL: Securing Smart Healthcare Environments Through IoT Firewalls. Sensors, 25(19), 6235. https://doi.org/10.3390/s25196235
  12. Huang, S., Cao, J., Chen, Z., Zhong, Q., & Zhang, M. (2025). Online Traffic Obfuscation Experimental Framework for the Smart Home Privacy Protection. Electronics, 14(16), 3294.https://doi.org/10.3390/electronics14163294
  13. Iadicicco, G. (2025). Development and Optimization of a Firmware for Real-Time Monitoring of Network Traffic and Threat Detection (Doctoral dissertation, Politecnico di Torino). Google Scholar
  14. Işık, C. (2025). NanoPi yapılandırma test ve gözlem notları. Kişisel proje dokümantasyonu, Bandırma Onyedi Eylül Üniversitesi, Yazılım Mühendisliği ABD.
  15. Lee, W., Stolfo, S. J., & Mok, K. W. (2000). Adaptive intrusion detection: A data mining approach. Artificial Intelligence Review, 14(6), 533–567. Google Scholar
  16. Nakra, T. (2025). Empowering Household Sovereignty: Privacy and Security with OpenWrt Firewall. Google Scholar
  17. Nodogsplash. (2024). Nodogsplash Captive Portal. https://github.com/nodogsplash/nodogsplash
  18. Olivera-Ruiz, G., Solsol-Isminio, J., & Bermúdez-Pino, W. (2024, October). Next-Generation Firewall Open-Source and LAN Performance. In 2024 43rd International Conference of the Chilean Computer Science Society (SCCC) (pp. 1-7). IEEE. https://doi.org/10.1109/SCCC63879.2024.10767614
  19. Ozkan-Okay, M., Samet, R., Aslan, Ö., & Gupta, D. (2021). A comprehensive systematic literature review on intrusion detection systems. IEEE Access, 9, 157727-157760. https://doi.org/10.1109/ACCESS.2021.3129336
  20. Ozkan-Okay, M., Samet, R., Aslan, Ö., Kosunalp, S., Iliev, T., & Stoyanov, I. (2023). A novel feature selection approach to classify intrusion attacks in network communications. Applied Sciences, 13(19), 11067. https://doi.org/10.3390/app131911067
  21. Repetto, M., & Carrega, A. (2022). Monitoring network flows in containerized environments. In Cybersecurity of Digital Service Chains: Challenges, Methodologies, and Tools (pp. 32-55). Cham: Springer International Publishing. Google Scholar
  22. Scarfone, K., & Mell, P. (2007). Guide to Intrusion Detection and Prevention Systems (IDPS) (NIST Special Publication 800-94). National Institute of Standards and Technology. https://csrc.nist.gov/publications/detail/sp/800-94. Google Scholar
  23. Shiravi, A., Shiravi, H., Tavallaee, M., & Ghorbani, A. A. (2012). Toward developing a systematic approach to generate benchmark datasets for intrusion detection. Computers & Security, 31(3), 357–374. https://doi.org/10.1016/j.cose.2011.12.012
  24. Suricata IDS. (2024). Suricata Documentation. https://docs.suricata.io/
  25. The OpenWRT Project. (2024). OpenWRT Documentation. https://openwrt.org https://wiki.friendlyelec.com/wiki/index.php/NanoPi_R5S