Outsourced computing is widely used today. However, current approaches for protecting client data in outsourced computing fall short: use of cryptographic techniques like fully-homomorphic encryption incurs substantial costs, whereas use of hardware-assisted trusted execution environments has been shown to be vulnerable to run-time attacks, and side-channel attacks.
We present Blinded Memory (BliMe), an architecture to realize efficient and secure outsourced computation. BliMe consists of a novel and minimal set of ISA extensions implementing a taint-tracking policy to ensure the confidentiality of client data even in the presence of server vulnerabilities. To secure outsourced computation, the BliMe extensions can be used together with an attestable, fixed-function hardware security module (HSM) and an encryption engine that provides atomic decrypt-and-taint and encrypt-and-untaint operations. Clients rely on remote attestation and key agreement with the HSM to ensure that their data can be transferred securely to and from the encryption engine and will always be protected by BliMe’s taint-tracking policy while at the server.
We provide a machine-checked security proof of BliMe extensions, and an RTL implementation BliMe-BOOM based on the BOOM RISC-V core. BliMe-BOOM incurs no reduction in clock frequency relative to unmodified BOOM, nor does it use significantly more power (<1.5%) or FPGA resources (≤9.0%). Various implementations of BliMe (on FPGA and the gem5 simulator) incur only moderate performance overhead (8-25%). We also provide a machine-checked security proof of a simplified model ISA with BliMe extensions.
Conference/journal paper publications
NDSS
BliMe: Verifiably Secure Outsourced Computation with Hardware-Enforced Taint Tracking
H ElAtali, L J Gunn, H Liljestrand, and 1 more author
In Network and Distributed Systems Symposium (NDSS), 2024
@inproceedings{blime24,title={BliMe: Verifiably Secure Outsourced Computation with Hardware-Enforced Taint Tracking},author={ElAtali, H and Gunn, L J and Liljestrand, H and Asokan, N},booktitle={Network and Distributed Systems Symposium (NDSS)},location={San Diego, CA, USA},year={2024},isbn={1-891562-93-2},doi={10.14722/ndss.2024.24105},}
HOST
Data-Oblivious ML Accelerators using Hardware Security Extensions
H ElAtali, J Z Jekel, L J Gunn, and 1 more author
In IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2024
@inproceedings{dolma24,title={Data-Oblivious ML Accelerators using Hardware Security Extensions},author={ElAtali, H and Jekel, J Z and Gunn, L J and Asokan, N},booktitle={IEEE International Symposium on Hardware Oriented Security and Trust (HOST)},location={Tysons Corner, VA, USA},year={2024},doi={10.1109/HOST55342.2024.10545398},}
SecDev
BliMe Linter
H ElAtali, X Duan, H Liljestrand, and 2 more authors
In IEEE Secure Development Conference (SecDev), 2024
@inproceedings{blimeLinter24,title={BliMe Linter},author={ElAtali, H and Duan, X and Liljestrand, H and Xu, M and Asokan, N},booktitle={IEEE Secure Development Conference (SecDev)},year={2024},doi={10.1109/SecDev61143.2024.00011},}
CCS
BLACKOUT: Data-Oblivious Computation with Blinded Capabilities
H ElAtali, M Gülmez, T Nyman, and 1 more author
In ACM Conference on Computer and Communications Security (CCS), 2025
@inproceedings{blackout25,title={BLACKOUT: Data-Oblivious Computation with Blinded Capabilities},author={ElAtali, H and Gülmez, M and Nyman, T and Asokan, N},booktitle={ACM Conference on Computer and Communications Security (CCS)},year={2025},doi={10.1145/3719027.3765169},}
HASP
MAGNET: Memory Tagging with Efficient Tag Prediction
P Makkar, H ElAtali, A Caulfield, and 1 more author
In International Workshop on Hardware and Architectural Support for Security and Privacy, 2025
@inproceedings{magnet25,title={MAGNET: Memory Tagging with Efficient Tag Prediction},author={Makkar, P and ElAtali, H and Caulfield, A and Asokan, N},booktitle={International Workshop on Hardware and Architectural Support for Security and Privacy},year={2025},isbn={9798400721984},publisher={Association for Computing Machinery},doi={10.1145/3768725.3768728},}