Cybersecurity MSc - Deepfake Detection Researcher

Mohammed Abdul Rahman

************@*****.*** — +1-773-***-**** — LinkedIn

EDUCATION

Bradley University, Peoria, IL Aug 2024 – Present

Master of Science in Computer Information Systems (Cyber Security) GPA: 4.0

Relevant Coursework: Computer Networks and System Security, Database Management Systems, IT Infrastructure, IT Project Management, CIS Integration, Design and Analysis.

Jawaharlal Nehru University, Hyderabad, India Jun 2024 Bachelor of Science Engineering in Computer Science TECHNICAL SKILLS

Programming Languages: Python, SQL, Bash/Shell Scripting, PowerShell, JavaScript, C, C++, Java, Go (Basics), Rust (Basics) Cybersecurity & Networking: Kali Linux, Nmap, Metasploit, Wireshark, Tcpdump, Burp Suite, Linux Hardening, OSINT, Vulnerability Assessment, Penetration Testing, Firewall Configuration, NAT, VPN, SSH, Network Monitoring, Incident Response Machine Learning & AI: PyTorch, TensorFlow, CNNs, Deep Learning, Image Classification, Data Preprocessing, Model Eval- uation, Streamlit, NumPy, Pandas

Systems & Operating Systems: Linux (Ubuntu, Kali,Redhat Enterprise Linux), Windows Administration, Active Directory Basics, System Troubleshooting, Virtualization (VMware/VirtualBox) Databases: PostgreSQL, MySQL, DBMS, Query Optimization, Schema Design, Data Import/Export Cloud & DevOps: Git, GitHub, Docker (Basics), CI/CD (Basics) Tools & Platforms: Jupyter Notebook, Google Colab, VS Code, Streamlit, Git CLI, Command-Line Tools Core Skills: Problem Solving, Debugging, Documentation & Reporting, Technical Writing, Research Analysis, Communication EXPERIENCE

Research Assistant – Deepfake Detection & Digital Forensics Sep 2024 – Present Bradley University, Peoria, IL

• Developed a complete deepfake detection pipeline using CNN and EfficientNet-B0 architectures in PyTorch for image clas- sification.

• Processed and curated a 140K+ image dataset, implemented augmentation, and generated clean train/validation splits to improve model robustness.

• Applied digital forensic techniques including metadata analysis, compression artifact detection, and temporal inconsistency checks to classify manipulated images.

• Built custom evaluation tools to measure accuracy, F1-score, ROC curves, and training metrics using GPU acceleration

(Google Colab).

• Designed an interactive Streamlit dashboard for real-time prediction testing, visualization, and research experimentation.

• Utilized GitHub for version control, NumPy/Matplotlib for analytics, and maintained end-to-end documentation for publication support and reproducibility.

PROJECTS

Kernel-Level Firewall Design & Bypass Techniques Linux, Netfilter, iptables

• Built a kernel-level firewall using Linux Netfilter and iptables with stateful and stateless filtering.

• Configured NAT, connection tracking, and rate limiting for secure internal routing.

• Tested bypass techniques (SSH tunneling, SOCKS5, VPN) and analyzed packet behavior.

• Documented attack surfaces and improved rule-sets to reduce unauthorized bypass attempts. Virtual Mouse Using Computer Vision Python, OpenCV, MediaPipe

• Developed a real-time gesture-controlled virtual mouse using OpenCV and MediaPipe.

• Implemented gesture-based clicking and movement via PyAutoGUI with stable fingertip tracking.

• Improved accuracy using smoothing and adaptive thresholding techniques.

• Demonstrated use cases for VR/AR interfaces and accessibility tools. IT Infrastructure & Home Network Configuration Networking, Wireshark

• Configured a secure multi-device home network with proper segmentation and routing.

• Set up NAT, DHCP reservations, firewall rules, and guest/internal Wi-Fi separation.

• Used Wireshark/Tcpdump for packet analysis and troubleshooting. 1

Contact this candidate