Nicolas Dutly

Andrin Bertschi, Supraja Sridhara, Mark Kuhne et al.

Modern confidential computing executes sensitive computation in an abstraction called confidential VMs and protects from the hypervisor, host OS, and other co-resident VMs. It has been shown that an attacker can inject malicious interrupts to break the confidentiality and integrity of confidential VMs. We present Devlore, a device interrupt isolation mechanism that protects confidential VMs from interrupt manipulation attacks. Our design employs a delegate-but-check strategy by offloading interrupt management to the hypervisor, but adds correctness checks in the trusted software. We prototype our design on Arm Confidential Computing Architecture (CCA). We evaluate it on Arm FVP to demonstrate four diverse devices attached to confidential VMs and report costs on a Rock5b board. Our case studies show the feasibility of real-world use cases and that Devlore incurs minimal overheads of 0.06% for typical integrated GPU applications.

Yoshimichi Nakatsuka, Nicolas Dutly, Kari Kostiainen et al.

Private Membership Testing (PMT) protocols enable clients to verify whether a certain data item is included in a database without revealing the item to the database operator or other external parties. This paper examines Source-assisted PMT (SPMT), in which clients leverage compact data source-provided information issued when the data item is first submitted to the database. SPMT is relevant in applications such as certificate transparency and supply-chain auditing; yet, designing an approach that is efficient, scalable, and privacy-preserving remains a challenge. This work presents Gyokuro, which takes a different approach to conventional membership testing schemes. Instead of requesting the server to produce a proof attesting that a certain data item exists in the database, we leverage Trusted Execution Environments (TEEs) to produce proofs demonstrating that the server has made enough progress to add the data item to the database. With the help of existing monitoring services, clients can infer that no items have been removed from the database. This allows Gyokuro to provide strong privacy guaranties and achieve high efficiency, as a client's membership testing query does not include any information regarding their interests, and eliminates the need for complex and inefficient protection mechanisms. Additionally, this approach enables membership testing on large-scale databases, since the communication and computation required are independent of the database size. Our evaluations show practical feasibility, achieving 7 ms membership testing latency and throughput of around 1400 requests/sec/core.