2,650 research outputs found
LNCS
HMAC and its variant NMAC are the most popular approaches to deriving a MAC (and more generally, a PRF) from a cryptographic hash function. Despite nearly two decades of research, their exact security still remains far from understood in many different contexts. Indeed, recent works have re-surfaced interest for {\em generic} attacks, i.e., attacks that treat the compression function of the underlying hash function as a black box.
Generic security can be proved in a model where the underlying compression function is modeled as a random function -- yet, to date, the question of proving tight, non-trivial bounds on the generic security of HMAC/NMAC even as a PRF remains a challenging open question.
In this paper, we ask the question of whether a small modification to HMAC and NMAC can allow us to exactly characterize the security of the resulting constructions, while only incurring little penalty with respect to efficiency. To this end, we present simple variants of NMAC and HMAC, for which we prove tight bounds on the generic PRF security, expressed in terms of numbers of construction and compression function queries necessary to break the construction. All of our constructions are obtained via a (near) {\em black-box} modification of NMAC and HMAC, which can be interpreted as an initial step of key-dependent message pre-processing.
While our focus is on PRF security, a further attractive feature of our new constructions is that they clearly defeat all recent generic attacks against properties such as state recovery and universal forgery. These exploit properties of the so-called ``functional graph'' which are not directly accessible in our new constructions
Order-Revealing Encryption and the Hardness of Private Learning
An order-revealing encryption scheme gives a public procedure by which two
ciphertexts can be compared to reveal the ordering of their underlying
plaintexts. We show how to use order-revealing encryption to separate
computationally efficient PAC learning from efficient -differentially private PAC learning. That is, we construct a concept
class that is efficiently PAC learnable, but for which every efficient learner
fails to be differentially private. This answers a question of Kasiviswanathan
et al. (FOCS '08, SIAM J. Comput. '11).
To prove our result, we give a generic transformation from an order-revealing
encryption scheme into one with strongly correct comparison, which enables the
consistent comparison of ciphertexts that are not obtained as the valid
encryption of any message. We believe this construction may be of independent
interest.Comment: 28 page
More Discriminants with the Brezing-Weng Method
The Brezing-Weng method is a general framework to generate families of
pairing-friendly elliptic curves. Here, we introduce an improvement which can
be used to generate more curves with larger discriminants. Apart from the
number of curves this yields, it provides an easy way to avoid endomorphism
rings with small class number
Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data
We provide formal definitions and efficient secure techniques for
- turning noisy information into keys usable for any cryptographic
application, and, in particular,
- reliably and securely authenticating biometric data.
Our techniques apply not just to biometric information, but to any keying
material that, unlike traditional cryptographic keys, is (1) not reproducible
precisely and (2) not distributed uniformly. We propose two primitives: a
"fuzzy extractor" reliably extracts nearly uniform randomness R from its input;
the extraction is error-tolerant in the sense that R will be the same even if
the input changes, as long as it remains reasonably close to the original.
Thus, R can be used as a key in a cryptographic application. A "secure sketch"
produces public information about its input w that does not reveal w, and yet
allows exact recovery of w given another value that is close to w. Thus, it can
be used to reliably reproduce error-prone biometric inputs without incurring
the security risk inherent in storing them.
We define the primitives to be both formally secure and versatile,
generalizing much prior work. In addition, we provide nearly optimal
constructions of both primitives for various measures of ``closeness'' of input
data, such as Hamming distance, edit distance, and set difference.Comment: 47 pp., 3 figures. Prelim. version in Eurocrypt 2004, Springer LNCS
3027, pp. 523-540. Differences from version 3: minor edits for grammar,
clarity, and typo
On the Cryptographic Hardness of Local Search
We show new hardness results for the class of Polynomial Local Search problems (PLS):
- Hardness of PLS based on a falsifiable assumption on bilinear groups introduced by Kalai, Paneth, and Yang (STOC 2019), and the Exponential Time Hypothesis for randomized algorithms. Previous standard model constructions relied on non-falsifiable and non-standard assumptions.
- Hardness of PLS relative to random oracles. The construction is essentially different than previous constructions, and in particular is unconditionally secure. The construction also demonstrates the hardness of parallelizing local search.
The core observation behind the results is that the unique proofs property of incrementally-verifiable computations previously used to demonstrate hardness in PLS can be traded with a simple incremental completeness property
EsPRESSo: Efficient Privacy-Preserving Evaluation of Sample Set Similarity
Electronic information is increasingly often shared among entities without
complete mutual trust. To address related security and privacy issues, a few
cryptographic techniques have emerged that support privacy-preserving
information sharing and retrieval. One interesting open problem in this context
involves two parties that need to assess the similarity of their datasets, but
are reluctant to disclose their actual content. This paper presents an
efficient and provably-secure construction supporting the privacy-preserving
evaluation of sample set similarity, where similarity is measured as the
Jaccard index. We present two protocols: the first securely computes the
(Jaccard) similarity of two sets, and the second approximates it, using MinHash
techniques, with lower complexities. We show that our novel protocols are
attractive in many compelling applications, including document/multimedia
similarity, biometric authentication, and genetic tests. In the process, we
demonstrate that our constructions are appreciably more efficient than prior
work.Comment: A preliminary version of this paper was published in the Proceedings
of the 7th ESORICS International Workshop on Digital Privacy Management (DPM
2012). This is the full version, appearing in the Journal of Computer
Securit
Families of fast elliptic curves from Q-curves
We construct new families of elliptic curves over \FF_{p^2} with
efficiently computable endomorphisms, which can be used to accelerate elliptic
curve-based cryptosystems in the same way as Gallant-Lambert-Vanstone (GLV) and
Galbraith-Lin-Scott (GLS) endomorphisms. Our construction is based on reducing
\QQ-curves-curves over quadratic number fields without complex
multiplication, but with isogenies to their Galois conjugates-modulo inert
primes. As a first application of the general theory we construct, for every
, two one-parameter families of elliptic curves over \FF_{p^2}
equipped with endomorphisms that are faster than doubling. Like GLS (which
appears as a degenerate case of our construction), we offer the advantage over
GLV of selecting from a much wider range of curves, and thus finding secure
group orders when is fixed. Unlike GLS, we also offer the possibility of
constructing twist-secure curves. Among our examples are prime-order curves
equipped with fast endomorphisms, with almost-prime-order twists, over
\FF_{p^2} for and
Towards an Information Theoretic Analysis of Searchable Encryption (Extended Version)
Searchable encryption is a technique that allows a client to store
data in encrypted form on a curious server, such that data can be
retrieved while leaking a minimal amount of information to the
server. Many searchable encryption schemes have been proposed and
proved secure in their own computational model. In this paper we
propose a generic model for the analysis of searchable
encryptions. We then identify the security parameters of
searchable encryption schemes and prove information theoretical
bounds on the security of the parameters. We argue that perfectly
secure searchable encryption schemes cannot be efficient. We
classify the seminal schemes in two categories: the schemes that
leak information upfront during the storage phase, and schemes
that leak some information at every search. This helps designers
to choose the right scheme for an application
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