Private-keyless access, serving as an implementation mechanism within policy-based data custody, enables control and authorization based on predefined policies without requiring users to possess a private key. The unforgeability of both user identity and authorization decisions is ensured by the cryptosystem in private-keyless data custody. Hereby, we introduce a novel Cryptographic Resource Enabled Framework (CREF) to simplify key management, enhance security, and increase flexibility of access authorization. Firstly, in the data custody phase, data resource and its session key are uploaded in ciphertext form to CREF, and the access authorization complies with multiple policies designated by the provider. Secondly, in the dynamic authorization phase, traditional keys or keycards are replaced with adequate one-time attribute credentials issued by multiple authorities. CREF makes dynamically cryptographic policy decision according to the credentials and the cryptographic policy (cryptopolicy). Technically, we design the Credentials-Driven Cryptosystem (CDC) over ideal lattice to build anti-quantum confidence for CREF. In CDC, preimage Gaussian sampler is adopted to sample short vector as real-time attribute credential instead of user's private key. Small policy matrix is implemented to convert monotone policies into optimized cryptopolicies in order to reduce accumulated error. The security analysis confirms that both credentials and cryptopolicies are existentially unforgeable, ensuring the semantic security of the whole CREF. Experimental results indicate CREF has lower storage and computational costs than existing schemes. Meanwhile, with policies' continuous improvements as system evolves, CREF only need to select a suitable policy among multiple candidates to make authorization decisions without having to reencrypt data.

Abstract Fuzzy extractors allow for the extraction and reproduction of a nearly uniform string from a noisy and non-uniform source. Reusable and robust fuzzy extractors further require that the output string should remain pseudorandom under multiple extractions and any modification of public value should be detectable. Existing constructions of reusable and robust fuzzy extractors are all designed in the Common Reference String (CRS) model and work only for CRS-independent sources. In this work, we introduce a construction of reusable and robust fuzzy extractor for CRS-dependent sources. Our construction is built upon some well-studied cryptography, including a collision resistant hash function, a symmetric key encryption that keeps secure with respect to auxiliary input, a public key encryption and simulation-sound non-interactive zero-knowledge argument. We also present some instantiations of these primitives from Learning with Parity Noise (LPN) assumption and Short Integer Solution (SIS) assumption. These instantiations result in the first reusable and robust fuzzy extractor for CRS-dependent sources that can tolerate linear errors.

Abstract The group fuzzy extractor allows group users to extract and reproduce group cryptographic keys from their individual non-uniform random sources. It can be easily used in group-oriented cryptographic applications. However, current group fuzzy extractors are not dynamic, i.e. they spend a large cost when dealing with user revocation. In this work, we propose the formal definition and construction of dynamic group fuzzy extractor (DGFE) to address this issue. For the revocation, DGFE allows unrevoked group users to reproduce updated group keys from the existing group help data. Meanwhile, it prevents any revoked group user from generating new group keys using the previously authorized individual help data. We propose a DGFE construction based on the revocable group signature. Furthermore, we give formal proofs of reusability, anonymity and traceability of our construction.

Abstract In this paper, we propose a novel cryptographic primitive named reusable group fuzzy extractor (RGFE) allowing any member of a group to extract and reproduce random strings from a fuzzy and non-uniform source of high entropy (called fingerprint). Any group member can anonymously generate a random string for the group using his fingerprint and can be traced when needed, whereas other members can reproduce the string using their own fingerprints. Moreover, a fingerprint can be repeatedly used to generate multiple random strings. Basing on RGFE, we present group-shared Bitcoin wallet, which can be used by a group of users to receive or spend coins via biometrics in a traceable way.

Timed-release CP-ABE can provide fine-grained and timed-release access control while ensuring data confidentiality. Existing schemes usually rely on a trusted third-party called time server. This paper proposes a novel timed-release CP-ABE scheme named ciphertext-policy attribute-based delay encryption (CP-ABDE), which does not require a time server. Specifically, we formalise the notion of CP-ABDE and its system model and security model. Furthermore, we provide a formal construction that is secure under the decisional bilinear Diffie-Hellman assumption and repeated squaring assumption. Finally, performance analysis shows that the scheme performs well while achieving timed-release access control.

In this article, we address the problem of data privacy in multisource data mining. To do it, we present a new multiparty fully homomorphic encryption (MP-FHE) scheme, in which all participants are completely fair to perform the same computation. At first, the proposed MP-FHE scheme is divided into five stages (i.e., calculation, configuration, recombination, resharing, and reconstruction stage) to achieve the unified computation form of addition and multiplication. Meanwhile, random bivariate polynomials and commutative encryption are used to achieve the degree reduction of polynomials and the continuity of computation. Moreover, we prove that the scheme meets result consistency and program termination under the fail-stop adversary model. Especially, three kinds of error detection criteria are presented to find errors in three different stages (i.e., recombination, resharing, and reconstruction stage), which provides the monitor basis for the fail-stop adversary model. In addition, the MP-FHE scheme is applied into privacy preserving k-means clustering algorithm. Finally, we evaluate the computation and communication performance of our scheme from both theoretical and experimental aspects, and the evaluation results show that the scheme is efficient enough for multisource data mining.

Closest point determination is a fundamental problem that arises in location-based services. In this paper, we study privacy-preserving closest point determination problem involving at least three parties, which focuses on determining the closest point without revealing location information. First, we present a three-party integer comparison protocol using homomorphic encryption systems in order to achieve the ciphertext comparison. Second, we propose a three-party and a multi-party protocol based on the integer comparison protocol to determine the closest point and prove that they are secure against semi-honest adversaries in the standard model. The proposed protocols are built on partially homomorphic encryption systems and can keep location and distance confidential. Finally, we confirm that our protocols reach a better balance between complexity and security. And experimental results demonstrate that our protocol is feasible and effective.

Secure integer comparison enables two parties to compare their inputs without revealing the exact value of those inputs. In this paper, we highlight three-party integer comparison (TPIC), where a judge, with no private input, wants to know the comparison result, while two competitors hold secret integers to do privacy-preserving comparison. A TPIC protocol enables the judge to actively obtain the result rather than passively learning it from one of the competitors. We give two TPIC constructions considering mixed adversaries, who have different capabilities. One is secure against semi-honest competitors with low computation and communication cost, while the other is secure against malicious competitors. In both, the judge is semi-honest. As applications of TPIC, we present a joint bidding scheme and a practical auction with brief security proofs and analysis. In comparison, our auction scheme is more efficient with lower cost, making it feasible in practice rather than a theoretical design. The proposed TPIC protocols and application schemes run on top of blockchain requiring a constant number of rounds.

Blockchains are confronted with challenges to store private files and grant access, especially for biometric-based schemes. We propose BSA, a biometric-based scheme for file storage and access authorization on blockchains. File storing, access request and response are performed on blockchains. Biometrics is the only secret information for storage and authorization, and can be repeatedly used with no privacy leakage. Such a scheme does not require a file owner to store any information locally, so it can be used on resource-constrained devices.

The interval discrete logarithm problem(IDLP) is to find a solution n such that g n = h in a finite cyclic group G = 〈 g〉, where h ∈ G and n belongs to a given interval. To accelerate solving IDLP, a restricted jump method is given to speed up Pollard’s kangaroo algorithm in this paper. Since the Pollard’ kangaroo-like method need to compute the intermediate value during every iteration, the restricted jump method gives another way to reuse the intermediate value so that each iteration is speeded up at least 10 times. Actually, there are some variants of kangaroo method pre-compute the intermediate value and reuse the pre-computed value in each iteration. Different from the pre-compute method that reuse the pre-computed value, the restricted jump method reuse the value naturally arised in pervious iteration, so that the improved algorithm not only avoids precomputation, but also speeds up the efficiency of each iteration. So only two or three large integer multiplications are needed in each iteration of the restricted jump method. And the average large integer multiplication times is (1:633 + o(1))[Formula: see text] in restricted jump method, which is verified in the experiment.