Biblio

Using dynamic Searchable Symmetric Encryption, a user with limited storage resources can securely outsource a database to an untrusted server, in such a way that the database can still be searched and updated efficiently. For these schemes, it would be desirable that updates do not reveal any information a priori about the modifications they carry out, and that deleted results remain inaccessible to the server a posteriori. If the first property, called forward privacy, has been the main motivation of recent works, the second one, backward privacy, has been overlooked. In this paper, we study for the first time the notion of backward privacy for searchable encryption. After giving formal definitions for different flavors of backward privacy, we present several schemes achieving both forward and backward privacy, with various efficiency trade-offs. Our constructions crucially rely on primitives such as constrained pseudo-random functions and puncturable encryption schemes. Using these advanced cryptographic primitives allows for a fine-grained control of the power of the adversary, preventing her from evaluating functions on selected inputs, or decrypting specific ciphertexts. In turn, this high degree of control allows our SSE constructions to achieve the stronger forms of privacy outlined above. As an example, we present a framework to construct forward-private schemes from range-constrained pseudo-random functions. Finally, we provide experimental results for implementations of our schemes, and study their practical efficiency.

Proof systems for verifiable computation (VC) have the potential to make cloud outsourcing more trustworthy. Recent schemes enable a verifier with limited resources to delegate large computations and verify their outcome based on succinct arguments: verification complexity is linear in the size of the inputs and outputs (not the size of the computation). However, cloud computing also often involves large amounts of data, which may exceed the local storage and I/O capabilities of the verifier, and thus limit the use of VC. In this paper, we investigate multi-relation hash & prove schemes for verifiable computations that operate on succinct data hashes. Hence, the verifier delegates both storage and computation to an untrusted worker. She uploads data and keeps hashes; exchanges hashes with other parties; verifies arguments that consume and produce hashes; and selectively downloads the actual data she needs to access. Existing instantiations that fit our definition either target restricted classes of computations or employ relatively inefficient techniques. Instead, we propose efficient constructions that lift classes of existing arguments schemes for fixed relations to multi-relation hash & prove schemes. Our schemes (1) rely on hash algorithms that run linearly in the size of the input; (2) enable constant-time verification of arguments on hashed inputs; (3) incur minimal overhead for the prover. Their main benefit is to amortize the linear cost for the verifier across all relations with shared I/O. Concretely, compared to solutions that can be obtained from prior work, our new hash & prove constructions yield a 1,400x speed-up for provers. We also explain how to further reduce the linear verification costs by partially outsourcing the hash computation itself, obtaining a 480x speed-up when applied to existing VC schemes, even on single-relation executions.