About Me

Hello! I am a mathematician into Cybersecurity. It is nice to see network defense as a large-scale modeling problem, where algebra, graph theory, and automation meet to solve real-world security challenges.

Numerical Analysis & Image Processing

My research focused on Numerical Analysis and Image Processing, specifically investigating the reconstruction of surfaces featuring jump discontinuities through interpolation. I employed piecewise monotone-preserving interpolants, which remain a powerful tool for balancing high-order accuracy with monotonicity. My work centered on constructing interpolants using custom non-linear means to recover 2D properties that are typically only guaranteed in the univariate case.

Graph Theory & Anomaly Detection

I have a strong interest in Graph Theory, and modeling through graphs. particularly in planarity problems. In the cyber world, I relate this to Network Topology Analysis:

• Graph-based Detection: Instead of simple logs, I see network traffic as a dynamic graph.
• Structural Anomalies: I’m exploring how changes in graph centralities or the appearance of unexpected edges can signal lateral movement or C2 activities.

🛡️ Microsoft Azure & Sentinel Operations

I am currently blue teaming as a SOC Analyst, and my dayly key-words are:

• KQL (Kusto Query Language) 💎: My primary tool for querying and correlating security telemetries across EDR (Endpoint Detection and Response), firewalls, and identity providers. I use it to build complex hunting logic that connects disparate data points into a coherent attack narrative.
• Workbooks 📊: I develop these to transform fragmented logs into centralized, interactive dashboards. They are essential for visualizing the “blast radius” of an incident and providing a clear, quantitative view of the infrastructure’s security posture.
• Playbooks ⚙️: Leveraging Logic Apps to automate repetitive triage tasks. These orchestrations integrate with OSINT 🔍 sources to automatically enrich alerts with external threat intelligence, significantly reducing the Mean Time to Respond (MTTR).

🔭 Learning Goals

• Getting in Anomaly Detection: I like to deduce hacker behavior through analytics. I aim to design and implement Anomaly Detection pipelines. 🚀

• Implementing MLOps orchestration, mastering Docker.