Compact FE for Unbounded Attribute-Weighted Sums for Logspace from SXDH 📺
Thispaperpresentsthefirstfunctionalencryption(FE)scheme for the attribute-weighted sum (AWS) functionality that supports the uniform model of computation. In such an FE scheme, encryption takes as input a pair of attributes (x, z) where the attribute x is public while the attribute z is private. A secret key corresponds to some weight function f, and decryption recovers the weighted sum f(x)z. This is an important functionality with a wide range of potential real-life applications, many of which require the attribute lengths to be flexible rather than being fixed at system setup. In the proposed scheme, the public attributes are considered as binary strings while the private attributes are considered as vectors over some finite field, both having arbitrary polynomial lengths that are not fixed at system setup. The weight functions are modelled as Logspace Turing machines. Prior schemes [Abdalla, Gong, and Wee, CRYPTO 2020 and Datta and Pal, ASIACRYPT 2021] could only support non-uniform Logspace. The proposed scheme is built in asymmetric prime-order bilinear groups and is proven adaptively simulation secure under the well-studied symmetric external Diffie-Hellman (SXDH) assumption against an arbitrary polynomial number of secret key queries both before and after the challenge ciphertext. This is the best possible level of security for FE as noted in the literature. As a special case of the proposed FE scheme, we also obtain the first adaptively simulation secure inner-product FE (IPFE) for vectors of arbitrary length that is not fixed at system setup. On the technical side, our contributions lie in extending the techniques of Lin and Luo [EUROCRYPT 2020] devised for payload hiding attribute-based encryption (ABE) for uniform Logspace access policies avoiding the so-called “one-use” restriction in the indistinguishability-based security model as well as the “three-slot reduction” technique for simulation- secure attribute-hiding FE for non-uniform Logspace devised by Datta and Pal [ASIACRYPT 2021] to the context of simulation-secure attribute- hiding FE for uniform Logspace.
Efficient Attribute-Based Signatures for Unbounded Arithmetic Branching Programs
This paper presents the first attribute-based signature (ABS) scheme in which the correspondence between signers and signatures is captured in an arithmetic model of computation. Specifically, we design a fully secure, i.e., adaptively unforgeable and perfectly signer-private ABS scheme for signing policies realizable by arithmetic branching programs (ABP), which are a quite expressive model of arithmetic computations. On a more positive note, the proposed scheme places no bound on the size and input length of the supported signing policy ABP’s, and at the same time, supports the use of an input attribute for an arbitrary number of times inside a signing policy ABP, i.e., the so called unbounded multi-use of attributes. The size of our public parameters is constant with respect to the sizes of the signing attribute vectors and signing policies available in the system. The construction is built in (asymmetric) bilinear groups of prime order, and its unforgeability is derived in the standard model under (asymmetric version of) the well-studied decisional linear (DLIN) assumption coupled with the existence of standard collision resistant hash functions. Due to the use of the arithmetic model as opposed to the boolean one, our ABS scheme not only excels significantly over the existing state-of-the-art constructions in terms of concrete efficiency, but also achieves improved applicability in various practical scenarios. Our principal technical contributions are (a) extending and refining the techniques of Okamoto and Takashima [PKC 2011, PKC 2013], which were originally developed in the context of boolean span programs, to the arithmetic setting; and (b) innovating new ideas to allow unbounded multi-use of attributes inside ABP’s, which themselves are of unbounded size and input length.
Fully Secure Functional Encryption with a Large Class of Relations from the Decisional Linear Assumption
This paper presents a fully secure (adaptively secure) practical functional encryption scheme for a large class of relations, that are specified by non-monotone access structures combined with inner-product relations. The security is proven under a standard assumption, the decisional linear assumption, in the standard model. Our scheme is constructed on the concept of dual pairing vector spaces and a hierarchical reduction technique on this concept is employed for the security proof. The proposed functional encryption scheme covers, as special cases, (1) key-policy, ciphertext-policy and unified-policy attribute-based encryption with non-monotone access structures, (2) (hierarchical) attribute-hiding functional encryption with inner-product relations and functional encryption with nonzero inner-product relations and (3) spatial encryption and a more general class of encryption than spatial encryption.
Unbounded Inner Product Functional Encryption from Bilinear Maps
Inner product functional encryption (IPFE), introduced by Abdalla et al. (PKC2015), is a kind of functional encryption supporting only inner product functionality. All previous IPFE schemes are bounded schemes, meaning that the vector length that can be handled in the scheme is fixed in the setup phase. In this paper, we propose the first unbounded IPFE schemes, in which we do not have to fix the lengths of vectors in the setup phase and can handle (a priori) unbounded polynomial lengths of vectors. Our first scheme is private-key based and fully function hiding. That is, secret keys hide the information of the associated function. Our second scheme is public-key based and provides adaptive security in the indistinguishability based security definition. Both our schemes are based on SXDH, which is a well-studied standard assumption, and secure in the standard model. Furthermore, our schemes are quite efficient, incurring an efficiency loss by only a small constant factor from previous bounded function hiding schemes.
Adaptively Simulation-Secure Attribute-Hiding Predicate Encryption
This paper demonstrates how to achieve simulation-based strong attribute hiding against adaptive adversaries for predicate encryption (PE) schemes supporting expressive predicate families under standard computational assumptions in bilinear groups. Our main result is a simulation-based adaptively strongly partially-hidingPE (PHPE) scheme for predicates computing arithmetic branching programs (ABP) on public attributes, followed by an inner-product predicate on private attributes. This simultaneously generalizes attribute-based encryption (ABE) for boolean formulas and ABP’s as well as strongly attribute-hiding PE schemes for inner products. The proposed scheme is proven secure for any a priori bounded number of ciphertexts and an unbounded (polynomial) number of decryption keys, which is the best possible in the simulation-based adaptive security framework. This directly implies that our construction also achieves indistinguishability-based strongly partially-hiding security against adversaries requesting an unbounded (polynomial) number of ciphertexts and decryption keys. The security of the proposed scheme is derived under (asymmetric version of) the well-studied decisional linear (DLIN) assumption. Our work resolves an open problem posed by Wee in TCC 2017, where his result was limited to the semi-adaptive setting. Moreover, our result advances the current state of the art in both the fields of simulation-based and indistinguishability-based strongly attribute-hiding PE schemes. Our main technical contribution lies in extending the strong attribute hiding methodology of Okamoto and Takashima [EUROCRYPT 2012, ASIACRYPT 2012] to the framework of simulation-based security and beyond inner products.