Welcome to my Cybersecurity Portfolio — a curated collection of my hands-on projects, research, and learning milestones in cybersecurity, machine learning, and threat intelligence. These works were developed during the 3MTT Nigeria program, personal R&D, and my M.Sc in Computer Science.
Each project highlights a specific challenge in the cybersecurity landscape — from real-time detection of fake alerts to threat intelligence automation and ML-based attack prediction.
Explore practical challenges tackled during the 3MTT Cybersecurity Cohort, including demonstrations and thought-provoking insights.
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Packet Sniffing with Wireshark
Capturing and analyzing network traffic using Wireshark to detect suspicious activity.
Tools: Wireshark, TCP/IP protocols -
Fake Bank Alert Detection & Awareness
Investigating common mobile fraud schemes and demonstrating how to spot fake transaction alerts.
Tools: Social Engineering Analysis, Device Forensics -
Hackathon 2.0 Winner – Ekiti State
My team emerged as the grand prize winner, building a solution to a real-world cybersecurity problem within a limited time. -
OSINT & Dark Web Monitoring
Utilizing open-source tools to gather intelligence from public and dark web platforms. -
Career Growth & Personal Development
Reflections on building a cyber path and personal growth throughout the 3MTT journey.
This master's research focuses on detecting vampire attacks—a type of resource-draining attack—in wireless sensor networks. It uses Random Forest and XGBoost for predictive modeling.
- Preprocessed Dataset:
WSN-DS-Preprocessed.csv - Trained Models:
best_rf_model.pkl,best_xgb_model.pkl - Performance Metrics:
- Confusion Matrices
- ROC Curves (Per-Class + Combined)
- Classification Reports
Python, Scikit-learn, XGBoost, pandas, matplotlib, Jupyter Notebook
This project evaluates and compares CTI-sharing platforms such as AlienVault OTX and VirusTotal for their effectiveness in collaborative threat detection.
- Real-time and combined datasets (
cleaned_realtime.csv,cti_combined_dataset.csv) - Threat indicator expansion outputs
- Jupyter Notebook for threat similarity analysis
- Comparative insights into CTI data quality
- Similarity scoring and detection overlap evaluation
I’m open to collaborations, internships, or research opportunities in cybersecurity, machine learning, or digital forensics. Feel free to connect:
- 📞 Phone: +2348147966893
- 💬 WhatsApp: Chat Now
- 💼 LinkedIn: Samuel Ojeleke
- 💻 GitHub: PsalmTech
Note: Some project files (e.g., full source codes or detection tools) are available upon request for educational or collaborative purposes.