After years of research, development, experimentation, and validation, I’m proud to publicly introduce the AnubisX Framework.
AnubisX is a scientific behavioral attribution framework that investigates one fundamental question:
Can human digital behavior itself become a reliable identifier?
Rather than relying on usernames, IP addresses, devices, or traditional digital artifacts, AnubisX focuses on extracting and analyzing behavioral fingerprints from digital activities using artificial intelligence, mathematical modeling, stylometry, graph analysis, and behavioral analytics.
The framework currently includes:
✅ 31 Formal Scientific Axioms ✅ 37+ Algorithm Specifications ✅ 292 Mathematical Definitions ✅ 50 Mathematical Equations ✅ 38 Experimental Designs ✅ 24 Benchmark Suites ✅ Multiple Real-World Case Studies ✅ AI-powered Behavioral Fingerprinting Architecture
This is not simply another OSINT tool.
It is a proposed scientific methodology for Behavioral Digital Attribution — designed to support research in:
• Cyber Threat Intelligence • Digital Forensics • Attribution Research • Counter Cybercrime • Online Identity Analysis • Behavioral Biometrics • Artificial Intelligence for Cybersecurity
The project is currently attracting significant attention, including ongoing discussions with Egyptian governmental stakeholders regarding potential applications of the framework in national cybersecurity and digital investigations.
For anyone interested in reviewing the work, all public research resources are available below.
📖 Book You Can Hide Your Name… Not Your Mind https://www.amazon.com/dp/B0H8LCTTWW
📚 Research Paper (Zenodo) https://doi.org/10.5281/zenodo.21393392
👨🔬 ORCID https://orcid.org/0009-0005-0654-3393
📄 ResearchGate https://www.researchgate.net/profile/Ahmed-Awad-118
📝 SSRN (Under Review)
💻 GitHub Repository https://github.com/NullC0d30/AnubisXFramework
I welcome constructive scientific discussion, peer review, collaboration opportunities, and independent validation of the framework.
If behavioral attribution can be formalized as a scientific discipline, it could reshape how we investigate digital identities in the years ahead.
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