Generic Efficient Dynamic Proofs of Retrievability

Together with its great advantages, cloud storage brought many interesting security issues to our attention. Since 2007, with the first efficient storage integrity protocols Proofs of Retrievability (PoR) of Juels and Kaliski, and Provable Data Possession (PDP) of Ateniese et al., many researchers worked on such protocols. The first proposals worked for static or limited dynamic data, whereas later proposals enabled fully dynamic data integrity and retrievability. Since the beginning, the difference between PDP and PoR models were greatly debated. Most notably, it was thought that dynamic PoR (DPoR) is harder than dynamic PDP (DPDP). Historically this was true: The first DPDP scheme was shown by Erway et al. in 2009, whereas the first DPoR scheme was created by Cash et al. in 2013. We show how to obtain DPoR from DPDP and PDP, together with erasure codes, making us realize that even though we did not know it, in 2009 we already could have had a DPoR solution. We propose a general framework for constructing DPoR schemes. Our framework encapsulates all known DPoR schemes as its special cases. We further show practical and interesting optimizations that enable even better performance than Chandran et al. and Shi et al. constructions. For the first time, we show how to obtain audit bandwidth for DPoR that is independent of the data size, and how the client can greatly speed up updates with O(λ√n) local storage (where n is the number of blocks, and λ is the security parameter), which corresponds to less than 3 MB for 10 GB outsourced data, and can easily be obtained in today’s smart phones, let alone computers

Foundations of Data Availability Sampling

Towards building more scalable blockchains, an approach known as data availability sampling (DAS) has emerged over the past few years. Even large blockchains like Ethereum are planning to eventually deploy DAS to improve their scalability. In a nutshell, DAS allows the participants of a network to ensure the full availability of some data without any one participant downloading it entirely. Despite the significant practical interest that DAS has received, there are currently no formal definitions for this primitive, no security notions, and no security proofs for any candidate constructions. For a cryptographic primitive that may end up being widely deployed in large real-world systems, this is a rather unsatisfactory state of affairs. In this work, we initiate a cryptographic study of data availability sampling. To this end, we define data availability sampling precisely as a clean cryptographic primitive. Then, we show how data availability sampling relates to erasure codes. We do so by defining a new type of commitment schemes which naturally generalizes vector commitments and polynomial commitments. Using our framework, we analyze existing constructions and prove them secure. In addition, we give new constructions which are based on weaker assumptions, computationally more efficient, and do not rely on a trusted setup, at the cost of slightly larger communication complexity. Finally, we evaluate the trade-offs of the different constructions

Generic constructions of PoRs from codes and instantiations

International audienceIn this paper, we show how to construct, from any linear code, a Proof of Retrievability (PoR) which features very low computation complexity on both the client (Verifier) and server (Prover) side, as well as small client storage (typically 512 bits). We adapt the security model initiated by Juels and Kaliski [JK07] to fit into the framework of Paterson et al. [PSU13], from which our construction evolves. We thus provide a rigorous treatment of the security of our generic design; more precisely, we sharply bound the extraction failure of our protocol according to this security model. Next, we instantiate our formal construction with codes built from tensor-products as well as with Reed-Muller codes and lifted codes [GKS13], yielding PoRs with moderate communication complexity and (server) storage overhead, in addition to the aforementioned features