Enabling Low-Cost Secure Computing on Untrusted In-Memory Architectures
Sahar Ghoflsaz Ghinani
34th USENIX Security Symposium (USENIX Security '25) · Day 1 · Embedded and Hardware Security
In an era where data processing demands are skyrocketing, **Processing-in-Memory (PIM)** architectures have emerged as a promising solution to overcome the traditional CPU-memory bottleneck. By integrating computational logic directly into memory modules, PIM systems offer significant performance enhancements, particularly for data-intensive applications like machine learning. However, this paradigm shift introduces a critical security challenge: how to perform computations over sensitive data when it resides in an untrusted memory environment. The talk "Enabling Low-Cost Secure Computing on Untrusted In-Memory Architectures" by Sahar Ghoflsaz Ghinani directly addresses this challenge, proposing a novel framework that combines **Trusted Execution Environments (TEEs)** with **Secure Multi-Party Computation (MPC)** to enable secure and efficient computation on PIM.
AI review
Solid systems security research from a PhD student tackling a real and underexplored problem: how do you run TEE-protected workloads when the compute lives in untrusted memory? The TEE+MPC hybrid with precomputation and garbled-circuit fallback for nonlinear ops is technically coherent, and crucially, it's validated on actual OPAM hardware rather than simulation — which puts it ahead of most academic PIM security work. Not revolutionary enough for a 5, but this is exactly the kind of deep, honest engineering paper USENIX Security should be platforming.