Can Intel’s Trusted Domain Extensions (TDX) support secure and reliable replication of academic papers in confidential cloud environments?

Academic replication packages often fail to run reliably across different computing environments due to software dependencies and documentation issues. This project evaluates whether Intel’s Trusted Domain Extensions (TDX) can support secure and reliable replication of academic papers in confidential cloud environments. Two recent Management Science studies from 2022 were tested using TDX-enabled virtual machines on Google Cloud. One package failed due to a missing dataset (Hotels_MW.dta) and reliance on Stata-only commands. No response was received from the authors. The other package was written in MATLAB and had to be converted to Octave. The code broke repeatedly due to nested functions and dimension mismatches. After rewriting key functions and adjusting test scripts, the model ran to completion inside the TDX VM. It used 184 GB of memory, ran for about 20 minutes, and cost under $5. Results matched those reported in the paper. This shows that TDX can be used for secure replication when code is self-contained, but packages that rely on closed data or platform-specific tools still remain a challenge.