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Cloud infrastructure is experiencing a shift towards disaggregated setups, especially with the introduction of the Compute Express Link (CXL) technology, where byte-addressable ersistent memory (PM) is becoming prominent. To fully utilize the potential of such devices, it is a necessity to access them through network stacks with equivalently high levels of performance (e.g., kernel-bypass, RDMA). While, these advancements are enabling the development of high-performance data management systems, their deployment on untrusted cloud environments also increases the security threats. To this end, we present Anchor, a library for building secure PM systems. Anchor provides strong hardware-assisted security properties, while ensuring crash consistency. Anchor exposes APIs for secure data management within the realms of the established PM programming model, targeting byte-addressable storage devices. Anchor leverages trusted execution environments (TEE) and extends their security properties on PM. While TEE's protected memory region provides a strong foundation for building secure systems, the key challenge is that: TEEs are fundamentally incompatible with PM and kernel-bypass networking approaches-in particular, TEEs are neither designed to protect untrusted non-volatile PM, nor the protected region can be accessed via an untrusted DMA connection. To overcome this challenge, we design a PM engine that ensures strong security properties for the PM data, using confidential and authenticated PM data structures, while preserving crash consistency through a secure logging protocol. We further extend the PM engine to provide remote PM data operations via a secure network stack and a formally verified remote attestation protocol to form an end-to-end system. Our evaluation shows that Anchor incurs reasonable overheads, while providing strong security properties.
Cloud infrastructure is experiencing a shift towards disaggregated setups, especially with the introduction of the Compute Express Link (CXL) technology, where byte-addressable ersistent memory (PM) is becoming prominent. To fully utilize the potential of such devices, it is a necessity to access them through network stacks with equivalently high levels of performance (e.g., kernel-bypass, RDMA). While, these advancements are enabling the development of high-performance data management systems, their deployment on untrusted cloud environments also increases the security threats. To this end, we present Anchor, a library for building secure PM systems. Anchor provides strong hardware-assisted security properties, while ensuring crash consistency. Anchor exposes APIs for secure data management within the realms of the established PM programming model, targeting byte-addressable storage devices. Anchor leverages trusted execution environments (TEE) and extends their security properties on PM. While TEE's protected memory region provides a strong foundation for building secure systems, the key challenge is that: TEEs are fundamentally incompatible with PM and kernel-bypass networking approaches-in particular, TEEs are neither designed to protect untrusted non-volatile PM, nor the protected region can be accessed via an untrusted DMA connection. To overcome this challenge, we design a PM engine that ensures strong security properties for the PM data, using confidential and authenticated PM data structures, while preserving crash consistency through a secure logging protocol. We further extend the PM engine to provide remote PM data operations via a secure network stack and a formally verified remote attestation protocol to form an end-to-end system. Our evaluation shows that Anchor incurs reasonable overheads, while providing strong security properties.
Confidentiality, integrity protection, and high availability, abbreviated to CIA, are essential properties for trustworthy data systems. The rise of cloud computing and the growing demand for multiparty applications however means that building modern CIA systems is more challenging than ever. In response, we present the Confidential Consortium Framework (CCF), a general-purpose foundation for developing secure stateful CIA applications. CCF combines centralized compute with decentralized trust, supporting deployment on untrusted cloud infrastructure and transparent governance by mutually untrusted parties. CCF leverages hardware-based trusted execution environments for remotely verifiable confidentiality and code integrity. This is coupled with state machine replication backed by an auditable immutable ledger for data integrity and high availability. CCF enables each service to bring its own application logic, custom multiparty governance model, and deployment scenario, decoupling the operators of nodes from the consortium that governs them. CCF is open-source and available now at https://github.com/microsoft/CCF.
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