Fast Reed-Solomon Interactive Oracle Proofs of Proximity

Ben–Sasson, Eli; Bentov, Iddo; Horesh, Yinon; Riabzev, Michael

doi:10.4230/lipics.icalp.2018.14

Cited by 19 publications

(3 citation statements)

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“…even with degrees as small as 20), and thus denote this exhaustion by MT (memory thrashing). Finally, we mention if the protocol is feasibly post-quantum (P-Q) secure in the 'P-Q' column ( [8,12] are P-Q-secure, [14] do not mention it but seems P-Q-secure, all the others, including us, use bilinear pairings). In Appendix E, we abstract the requirements of our protocols to see if they could be modified to use only postquantum secure routines.…”

Section: Protocolmentioning

confidence: 99%

“…Correctness. First, (8) gives the correctness of Read. For Update, (9) provides the correctness of the hash tree.…”

Section: Server Communications Clientmentioning

confidence: 99%

“…Typically, the polynomial will be stored under a fully-or partiallyhomomorphic encryption scheme, in such a way that the Server can still compute the (necessarily encrypted) evaluation and certificate for verification. This setting has been extensively studied in the literature, with both general-purpose protocols as well as some specific ones for verified polynomial evaluation; see, e.g., [8,12,14,19,31,32,38,47,50,57]. ‚ Dynamic updates.…”

Section: Introductionmentioning

confidence: 99%

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VESPo: Verified Evaluation of Secret Polynomials (with application to dynamic proofs of retrievability)

Dumas

Maignan

Pernet

et al. 2023

PoPETs

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Proofs of Retrievability are protocols which allow a Client to store data remotely and to efficiently ensure, via audits, that the entirety of that data is still intact. Dynamic Proofs of Retrievability (DPoR) also support efficient retrieval and update of any small portion of the data. We propose a novel protocol for arbitrary outsourced data storage that achieves both low remote storage size and audit complexity. A key ingredient, that can be also of intrinsic interest, reduces to efficiently evaluating a secret polynomial at given public points, when the (encrypted) polynomial is stored on an untrusted Server. The Server performs the evaluations and also returns associated certificates. A Client can check that the evaluations are correct using the certificates and some pre-computed keys, more efficiently than re-evaluating the polynomial. Our protocols support two important features: the polynomial itself can be encrypted on the Server, and it can be dynamically updated by changing individual coefficients cheaply without redoing the entire setup. Our methods rely on linearly homomorphic encryption and pairings, and our implementation shows good performance for polynomial evaluations with millions of coefficients, and efficient DPoR with terabytes of data. For instance, for a 1TB database, compared to the state of art, we can reduce the Client storage by 5000x, communication size by 20x, and client-side audit time by 2x, at the cost of one order of magnitude increase in server-side audit time.

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Section: Protocolmentioning

confidence: 99%

“…Correctness. First, (8) gives the correctness of Read. For Update, (9) provides the correctness of the hash tree.…”

Section: Server Communications Clientmentioning

confidence: 99%