DNS Security • Machine Learning • Network Intelligence • Predictive Systems
I'm an engineer specializing in AI-driven cybersecurity, with a strong research background in DNS security, anomaly detection, and intelligent network defense systems.
My work focuses on bridging applied AI with real-world network protection, leveraging scalable architectures, automation, and data-driven intelligence.
- 🎓 Graduated from ESPRIT, Tunisia (2025)
- 🌍 Research collaboration with Landshut University (Germany) and Dräxlmaier
- 🧩 Expertise: DNS Security, AI Threat Detection, Distributed Protocols, Predictive Maintenance
- ⚙️ Passion: Converting research into deployable, high-impact cybersecurity systems
| Category | Technologies |
|---|---|
| Languages | Python, C/C++, Java |
| AI & ML | TensorFlow, PyTorch, Scikit-learn |
| Security / Networking | Scapy, Wireshark, BIND9, DNSSEC |
| DevOps & Tools | Docker, Kubernetes, Git/GitHub, Linux |
| Data & Automation | Pandas, NumPy, n8n, REST APIs |
🔹 DNS Anomaly Detection System
Machine learning–based system to detect DNS tunneling, cache poisoning, and resolver abuse.
🔹 BIND9 Security Analysis
Reverse engineering, vulnerability analysis, and proposal of a custom DNS security protocol for enhanced integrity.
🔹 Predictive Maintenance Platform
Deployed ML pipelines for real-time failure prediction using streaming sensor data.
🔹 Paper2Attack Framework
Automated research-to-simulation pipeline: parses academic papers to extract DNS attack parameters and simulate them via Scapy.
📂 Explore more at github.com/Dhiaelhak-Rached
© 2025 Dhia el Hak Rached — Focused on AI, Security, and Scalable Intelligence Systems.