Lachlan J. Gunn

Parsa Sadri Sinaki, Zainab Ahmad, Wentao Xie et al.

Hardware-secured remote attestation is essential to establishing trust in the integrity of confidential virtual machines (cVMs), but is difficult to use in practice because verifying attestation evidence requires the use of hardware-specific cryptographic logic. This increases both maintenance costs and the verifiers' trusted computing base. We introduce the concept of self-verifying remote attestation evidence. Each attestation bundle identifies its verification logic in the form of a WebAssembly component that is downloaded by the verifier and executed. This approach transforms evidence verification into a platform-agnostic functionality that is implemented once for all platforms: the verifier measures the verification logic and then executes it to validate the evidence. As a result, verifiers can validate attestation evidence without any platform-specific code; the verification logic is just another measurement whose reference value can be checked with existing mechanisms. We implement this concept as TrustMee, a platform-agnostic verification driver for the Trustee framework. We demonstrate its functionality with self-verifying evidence for AMD SEV-SNP, Intel TDX, and Intel SGX attestations, producing attestation claims in the standard Entity Attestation Token (EAT) format.

Prach Chantasantitam, Adam Ilyas Caulfield, Vasisht Duddu et al.

Machine learning property attestations allow provers (e.g., model providers or owners) to attest properties of their models/datasets to verifiers (e.g., regulators, customers), enabling accountability towards regulations and policies. But, current approaches do not support generative models or large datasets. We present PAL*M, a property attestation framework for large generative models, illustrated using large language models. PAL*M defines properties across training and inference, leverages confidential virtual machines with security-aware GPUs for coverage of CPU-GPU operations, and proposes using incremental multiset hashing over memory-mapped datasets to efficiently track their integrity. We implement PAL*M on Intel TDX+NVIDIA H100 and evaluate it using state-of-the-art models and datasets, showing PAL*M is efficient, incurring < 11% overhead for common operations. Finally, we use the Tamarin Prover symbolic verification tool to formally model PAL*M's property attestation protocol, confirming that its security guarantees are upheld under the defined threat model.

Tigist Abera, Ferdinand Brasser, Lachlan J. Gunn et al.

Autonomous collaborative networks of devices are rapidly emerging in numerous domains, such as self-driving cars, smart factories, critical infrastructure, and Internet of Things in general. Although autonomy and self-organization are highly desired properties, they increase vulnerability to attacks. Hence, autonomous networks need dependable mechanisms to detect malicious devices in order to prevent compromise of the entire network. However, current mechanisms to detect malicious devices either require a trusted central entity or scale poorly. In this paper, we present GrandDetAuto, the first scheme to identify malicious devices efficiently within large autonomous networks of collaborating entities. GrandDetAuto functions without relying on a central trusted entity, works reliably for very large networks of devices, and is adaptable to a wide range of application scenarios thanks to interchangeable components. Our scheme uses random elections to embed integrity validation schemes in distributed consensus, providing a solution supporting tens of thousands of devices. We implemented and evaluated a concrete instance of GrandDetAuto on a network of embedded devices and conducted large-scale network simulations with up to 100000 nodes. Our results show the effectiveness and efficiency of our scheme, revealing logarithmic growth in run-time and message complexity with increasing network size. Moreover, we provide an extensive evaluation of key parameters showing that GrandDetAuto is applicable to many scenarios with diverse requirements.

Lachlan J. Gunn, Jian Liu, Bruno Vavala et al.

Consensus mechanisms used by popular distributed ledgers are highly scalable but notoriously inefficient. Byzantine fault tolerance (BFT) protocols are efficient but far less scalable. Speculative BFT protocols such as Zyzzyva and Zyzzyva5 are efficient and scalable but require a trade-off: Zyzzyva requires only $3f + 1$ replicas to tolerate $f$ faults, but even a single slow replica will make Zyzzyva fall back to more expensive non-speculative operation. Zyzzyva5 does not require a non-speculative fallback, but requires $5f + 1$ replicas in order to tolerate $f$ faults. BFT variants using hardware-assisted trusted components can tolerate a greater proportion of faults, but require that every replica have this hardware. We present SACZyzzyva, addressing these concerns: resilience to slow replicas and requiring only $3f + 1$ replicas, with only one replica needing an active monotonic counter at any given time. We experimentally evaluate our protocols, demonstrating low latency and high scalability. We prove that SACZyzzyva is optimally robust and that trusted components cannot increase fault tolerance unless they are present in greater than two-thirds of replicas.

Hans Liljestrand, Thomas Nyman, Lachlan J. Gunn et al.

A popular run-time attack technique is to compromise the control-flow integrity of a program by modifying function return addresses on the stack. So far, shadow stacks have proven to be essential for comprehensively preventing return address manipulation. Shadow stacks record return addresses in integrity-protected memory secured with hardware-assistance or software access control. Software shadow stacks incur high overheads or trade off security for efficiency. Hardware-assisted shadow stacks are efficient and secure, but require the deployment of special-purpose hardware. We present authenticated call stack (ACS), an approach that uses chained message authentication codes (MACs). Our prototype, PACStack, uses the ARM general purpose hardware mechanism for pointer authentication (PA) to implement ACS. Via a rigorous security analysis, we show that PACStack achieves security comparable to hardware-assisted shadow stacks without requiring dedicated hardware. We demonstrate that PACStack's performance overhead is small (~3%).

Lachlan J. Gunn, Andrew Allison, Derek Abbott

Decentralized systems can be more resistant to operator mischief than centralized ones, but they are substantially harder to develop, deploy, and maintain. This cost is dramatically reduced if the decentralized part of the system can be made highly generic, and thus incorporated into many different applications. We show how existing anonymization systems can serve this purpose, securing a public database against equivocation by its operator without the need for cooperation by the database owner. We derive bounds on the probability of successful equivocation, and in doing so, we demonstrate that anonymization systems are not only important for user privacy, but that by providing privacy to machines they have a wider value within the internet infrastructure

Lachlan J. Gunn, Andrew Allison, Derek Abbott

The Kish key distribution system has been proposed as a class ical alternative to quantum key distribution. The idealized Kish scheme elegantly promise s secure key distribution by exploiting thermal noise in a transmission line. However, we demonstrate that it is vulnerable to nonidealities in its components, such as the finite resistance of the transmission line connecting its endpoints. We introduce a novel attack against this nonideality using directional wave measurements, and experimentally demonstrate its efficacy. Our attack is based on causality: in a spatially distributed system, propagation is needed for thermodynamic equilibration, and that leaks information.

Lachlan J. Gunn, James M. Chappell, Andrew Allison et al.

While information-theoretic security is often associated with the one-time pad and quantum key distribution, noisy transport media leave room for classical techniques and even covert operation. Transit times across the public internet exhibit a degree of randomness, and cannot be determined noiselessly by an eavesdropper. We demonstrate the use of these measurements for information-theoretically secure communication over the public internet.