Kerem Arikan (Binghamton University), Abraham Farrell (Binghamton University), Williams Zhang Cen (Binghamton University), Jack McMahon (Binghamton University), Barry Williams (Binghamton University), Yu David Liu (Binghamton University), Nael Abu-Ghazaleh (University of California, Riverside), Dmitry Ponomarev (Binghamton University)

Protection of cache hierarchies from side-channel attacks is critical for building secure systems, particularly the ones using Trusted Execution Environments (TEEs). In this paper, we consider the problem of efficient and secure fine-grained partitioning of cache hierarchies and propose a framework, called Secure Hierarchies for TEEs (TEE-SHirT). In the context of a three-level cache system, TEE-SHirT consists of partitioned shared last-level cache, partitioned private L2 caches, and non-partitioned L1 caches that are flushed on context switches and system calls. Efficient and correct partitioning requires careful design. Towards this goal, TEE-SHirT makes three contributions: 1) we demonstrate how the hardware structures used for holding cache partitioning metadata can be effectively virtualized to avoid flushing of cache partition content on context switches and system calls; 2) we show how to support multi-threaded enclaves in TEE-SHirT, addressing the issues of coherency and consistency that arise with both intra-core and inter-core data sharing; 3) we develop a formal security model for TEE-SHirT to rigorously reason about the security of our design.

View More Papers

WIP: A First Look At Employing Large Multimodal Models...

Mohammed Aldeen, Pedram MohajerAnsari, Jin Ma, Mashrur Chowdhury, Long Cheng, Mert D. Pesé (Clemson University)

Read More

Strengthening Privacy in Robust Federated Learning through Secure Aggregation

Tianyue Chu, Devriş İşler (IMDEA Networks Institute & Universidad Carlos III de Madrid), Nikolaos Laoutaris (IMDEA Networks Institute)

Read More

A Comparison of Three Approaches to Assist Users in...

Michael Clark (Brigham Young University), Scott Ruoti (The University of Tennessee), Michael Mendoza (Imperial College London), Kent Seamons (Brigham Young University)

Read More

WIP: Threat Modeling Laser-Induced Acoustic Interference in Computer Vision-Assisted...

Nina Shamsi (Northeastern University), Kaeshav Chandrasekar, Yan Long, Christopher Limbach (University of Michigan), Keith Rebello (Boeing), Kevin Fu (Northeastern University)

Read More