Authors : Brent Warren M. Morta; Carl Christian Jarque; Rafael Nickolai Pugay; Jan Tristan Buenviaje; Robert Perido; Paolo Roberto Lozada

Volume/Issue : Volume 11 - 2026, Issue 5 - May

---

Google Scholar : https://tinyurl.com/2jumtwut

Scribd : https://tinyurl.com/46tvuf6m

DOI : https://doi.org/10.38124/ijisrt/26May1577

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

---

Abstract : Phishing attacks constitute a persistent and escalating cybersecurity threat, disproportionately affecting households and small businesses in the Philippines due to limited access to affordable protective infrastructure. This study developed the PhiNex an Advanced RISC Machine and Field-Programmable Gate Array (ARM-FPGA) Hybrid Security Gateway for Real-Time Phishing Detection and Domain Name System (DNS)-Level Threat Mitigation using the PYNQ-Z2 development board. The system integrates hardware-accelerated threat pre-filtering through reprogrammable FPGA logic with XGBoost-based machine learning classification on an ARM Cortex-A9 processor, enabling real-time phishing detection across multiple networked devices simultaneously.

Keywords : Phishing Detection; ARM-FPGA; DNS-Level Security; Hardware Acceleration; Real-Time Threat Detection; Machine Learning.

References :

1. National University, “101 Cybersecurity Statistics and Trends for 2024,” Jan. 2025. [Online]. Available: https://www.nu.edu/blog/cybersecurity-statistics/
2. Federal Trade Commission, “Consumer Sentinel Network Data Book 2022,” FTC, 2023.
3. C8 Secure, “Cybersecurity Issue: More than 5 Billion Cyber Attacks,” Sep. 2024. [Online]. Available: https://www.c8secure.com/
4. Rappler, “NBI arrests 29 individuals from scam hub in Kawit, Cavite,” 2024.
5. PSA Intelligence, “Crackdown on recent scam hubs lead to multiple arrests in the Philippines,” Jan. 2025.
6. J.-C. Owens, “PYNQ-THNK SeCuRiTy,” Hackster.io, 2020.
7. George Mason University CERG, “FOBOS³ Introduction,” [Online]. Available: https://cryptography.gmu.edu/
8. D.-M. Ngo, D. Lightbody, A. Temko, and E. Popovici, “HH-NIDS: Heterogeneous Hardware-Based Network Intrusion Detection Framework for IoT Security,” Future Internet, vol. 15, no. 1, p. 9, 2022.
9. C. Pham-Quoc, T. H. Q. Bao, and T. N. Thinh, “FPGA/AI-powered architecture for anomaly network intrusion detection systems,” Electronics, vol. 12, no. 3, p. 668, 2023.
10. D. Kourfalas, A. Roy, and M. Payer, “MaliGNNoma: GNN-Based Malicious Circuit Classifier for Secure Cloud FPGAs,” arXiv: 2403.01860, 2024.
11. S. Park et al., “5G Security Threat Assessment in Real Networks,” Sensors, vol. 21, no. 16, p. 5524, 2021.
12. E. Torreno, “FPGA Resource Optimization for Embedded Security Systems,” B.S. thesis, 2020.
13. R. A. Maranan et al., “FPGA-based encryption and decryption system using IDEA cryptography,” B.S. thesis, De La Salle University, Manila, 2010.
14. R. Zieni et al., “Phishing or Not Phishing? A Survey on the Detection of Phishing Websites,” IEEE Access, vol. 11, pp. 112261–112286, 2023.
15. Lumify Work Philippines, “2024–2025 Budget: Cyber Security Meets Philippine Skills Framework,” 2024.
16. AAG IT Support, “The Latest Cyber Crime Statistics,” Jun. 2024.