Final-year BS Cybersecurity & Digital Forensics student (CGPA 3.50) with hands-on experience in threat detection, blockchain security, AI anomaly detection, and digital forensics. Published researcher • IEEE event host • Real-world security builder.
I am Eman Fatima, a dedicated final-year BS Cybersecurity & Digital Forensics student at The Islamia University of Bahawalpur (CGPA 3.50). Based in Rahim Yar Khan, Pakistan, I specialize in fortifying digital infrastructures and uncovering insights hidden in complex data.
My research has been accepted at ICACNC 2025 and submitted to JAIR, focusing on blockchain-AI integration for healthcare security. I've hosted IEEE cybersecurity events, led lab teams, and completed internships in both forensics and AI.
Whether it's deploying phishing detection platforms, crafting steganography utilities, or building audio forensics tools — I thrive on solving intricate technical challenges. Let's collaborate to build something secure and impactful.
Ethical hacking, digital tampering detection, memory forensics, and network security with industry tools.
Integrating LLMs, Whisper, and ML models into security protocols for anomaly detection and threat intelligence.
Ethereum smart contracts, IPFS decentralized storage, and role-based access control for healthcare systems.
Continuously expanding knowledge through industry-recognized programs.
Google / Coursera • Aug 2024
Google / Coursera
Google / Coursera
Boot Camp • May 2025
In Progress
Microsoft / Online
Secure hospital management system using Ethereum smart contracts for role-based access, IPFS for decentralized storage, and Random Forest AI for anomaly detection. Live at healerplus.live
Web platform detecting digital tampering in audio files using Whisper for transcription and DistilBERT for NLP-based authenticity analysis.
Full-stack platform detecting phishing URLs, emails, and web content in real-time with NLP, WHOIS/DNS lookups and risk scoring.
Deep learning model trained on German Traffic Sign dataset (GTSRB) to detect and classify traffic signs with 98.2% confidence using computer vision.
Records audio to evaluate Quranic pronunciation accuracy with phoneme-level analysis using Whisper and Wav2Vec2.
CNN-based classifier with 85%+ confidence threshold for Cat vs Dog categorization with per-class confidence scores and Streamlit UI.
Audits password strength, enforces policy requirements, and verifies credentials against known breached password databases for robust account security.
Lightweight multi-threaded network port scanner for rapid discovery of open ports, live hosts, and active services during security reconnaissance.
Extracts hidden metadata from documents and images, exposing EXIF data, authors, GPS coordinates, and creation timelines for forensic investigations.
I'm actively looking for cybersecurity roles, research collaborations, and internships where I can apply my skills in threat detection, forensics, and AI-powered security solutions.
Online · Ask me about Eman!