Cloud services have turned remote computation into a commodity and enable convenient online collaboration. However, they require that clients fully trust the service provider in terms of confidentiality, integrity, and availability. Towards reducing this dependency, this paper introduces a protocol for verification of integrity and consistency for cloud object storage (VICOS), which enables a group of mutually trusting clients to detect data-integrity and consistency violations for a cloud object-storage service. It aims at services where multiple clients cooperate on data stored remotely on a potentially misbehaving service. VICOS enforces the consistency notion of fork-linearizability, supports wait-free client semantics for most operations, and reduces the computation and communication overhead compared to previous protocols. VICOS is based in a generic way on any authenticated data structure. Moreover, its operations cover the hierarchical name space of a cloud object store, supporting a real-world interface and not only a simplistic abstraction. A prototype of VICOS that works with the key-value store interface of commodity cloud storage services has been implemented, and an evaluation demonstrates its advantage compared to existing systems.
In CloudProof @cite_14 , an object-storage protection system with accountable and proof-based data integrity and consistency support, clients may verify the freshness of returned objects with the help of the data owner. Its auditing operation works in epochs and verifies operations on one object only with a certain probability and only at the end of an epoch. Moreover, the clients need to communicate directly with the owner of an object for establishing integrity and consistency.
@cite_14
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Several cloud storage systems exist today, but none of them provide security guarantees in their Service Level Agreements (SLAs). This lack of security support has been a major hurdle for the adoption of cloud services, especially for enterprises and cautious consumers. To fix this issue, we present CloudProof, a secure storage system specifically designed for the cloud. In CloudProof, customers can not only detect violations of integrity, write-serializability, and freshness, they can also prove the occurrence of these violations to a third party. This proof-based system is critical to enabling security guarantees in SLAs, wherein clients pay for a desired level of security and are assured they will receive a certain compensation in the event of cloud misbehavior. Furthermore, since CloudProof aims to scale to the size of large enterprises, we delegate as much work as possible to the cloud and use cryptographic tools to allow customers to detect and prove cloud misbehavior. Our evaluation of CloudProof indicates that its security mechanisms have a reasonable cost: they incur a latency overhead of only ∼15 on reads and writes, and reduce throughput by around 10 . We also achieve highly scalable access control, with membership management (addition and removal of members' permissions) for a large proprietary software with more than 5000 developers taking only a few seconds per month. To provide fault tolerance for cloud storage, recent studies propose to stripe data across multiple cloud vendors. However, if a cloud suffers from a permanent failure and loses all its data, then we need to repair the lost data from other surviving clouds to preserve data redundancy. We present a proxy-based system for multiple-cloud storage called NCCloud, which aims to achieve cost-effective repair for a permanent single-cloud failure. NCCloud is built on top of network-coding-based storage schemes called regenerating codes. Specifically, we propose an implementable design for the functional minimum-storage regenerating code (F-MSR), which maintains the same data redundancy level and same storage requirement as in traditional erasure codes (e.g., RAID-6), but uses less repair traffic. We implement a proof-of-concept prototype of NCCloud and deploy it atop local and commercial clouds. We validate the cost effectiveness of FMSR in storage repair over RAID-6, and show that both schemes have comparable response time performance in normal cloud storage operations. It is currently impossible for an application to verify that the data it passes to the kernel for storage is actually submitted to an underlying device or that the data returned to an application by the kernel has actually originated from an underlying device. A compromised or malicious OS can silently discard data written by the application or return fabricated data during a read operation. This is a serious data integrity issue for use-cases where verifiable storage and retrieval of data is a necessary precondition for ensuring correct operation, for example with secure logging, APT monitoring and compliance. We outline a solution for verifiable data storage and retrieval by providing a trustworthy mechanism, based on Intel SGX, to authenticate and verify request data at both the application and storage device endpoints. Even in the presence of a malicious OS our design ensures the authenticity and integrity of data while performing disk I O and detects any data loss attributable to the untrusted OS fabricating or discarding read and write requests respectively. We provide a nascent prototype implementation for the core system together with an evaluation highlighting the temporal overheads imposed by this mechanism. Geo-replicated storage systems are at the core of current Internet services. The designers of the replication protocols used by these systems must choose between either supporting low-latency, eventually-consistent operations, or ensuring strong consistency to ease application correctness. We propose an alternative consistency model, Explicit Consistency, that strengthens eventual consistency with a guarantee to preserve specific invariants defined by the applications. Given these application-specific invariants, a system that supports Explicit Consistency identifies which operations would be unsafe under concurrent execution, and allows programmers to select either violation-avoidance or invariant-repair techniques. We show how to achieve the former, while allowing operations to complete locally in the common case, by relying on a reservation system that moves coordination off the critical path of operation execution. The latter, in turn, allows operations to execute without restriction, and restore invariants by applying a repair operation to the database state. We present the design and evaluation of Indigo, a middleware that provides Explicit Consistency on top of a causally-consistent data store. Indigo guarantees strong application invariants while providing similar latency to an eventually-consistent system in the common case.