International Association
for Cryptologic Research

Multi-client Attribute-Based Encryption (ABE) is a generalization of key-policy ABE where attributes can be independently encrypted across several ciphertexts w.r.t. labels, and a joint decryption of these ciphertexts is possible if and only if (1) all ciphertexts share the same label, and (2) the combination of attributes satisfies the policy of the decryption key. All encryptors have their own secret key and security is preserved even if some of them are known to the adversary. Very recently, Pointcheval et al. (TCC 2024) presented a semi-generic construction of MC-ABE for restricted function classes, e.g., NC0 and constant-threshold policies. We identify an abstract criterion common to all their policy classes which suffices to present the construction in a fully black-box way and allows for a slight strengthening of the supported policy classes. The construction of Pointcheval et al. is based on pairings. We provide a new lattice-based instantiation from evasive LWE. Furthermore, we revisit existing constructions for policies that can be viewed as a conjunction of local policies (one per encryptor). Existing constructions from MDDH (Agrawal et al., CRYPTO 2023) and LWE (Francati et al., EUROCRYPT 2023) do not support encryption w.r.t. different labels. We show how this feature can be included at the cost of additionally relying on random oracles. Notably, the security model of Francati et al. additionally guarantees attribute-hiding but does not capture collusions. Our new construction is also attribute-hiding and provides resilience against any polynomially bounded number of collusions which must be fixed at the time of setup.

Dynamic Decentralized Functional Encryption (DDFE) is a generalization of Functional Encryption which allows multiple users to join the system dynamically without interaction and without relying on a trusted third party. Users can independently encrypt their inputs for a joint evaluation under functions embedded in functional decryption keys; and they keep control on these functions as they all have to contribute to the generation of the functional keys. In this work, we present new generic compilers which, when instantiated with existing schemes from the literature, improve over the state-of-the-art in terms of security, computational assumptions and functionality. Specifically, we obtain the first adaptively secure DDFE schemes for inner products in both the standard and the stronger function-hiding setting which guarantees privacy not only for messages but also for the evaluated functions. Furthermore, we present the first DDFE for inner products whose security can be proven under the LWE assumption in the standard model. Finally, we give the first construction of a DDFE for the attribute-weighted sums functionality with attribute-based access control (with some limitations). All prior constructions guarantee only selective security, rely on group-based assumptions on pairings, and cannot provide access control.

<p> Decentralized Multi-Client Functional Encryption (DMCFE) extends the basic functional encryption to multiple clients that do not trust each other. They can independently encrypt the multiple plaintext-inputs to be given for evaluation to the function embedded in the functional decryption key, defined by multiple parameter-inputs. And they keep control on these functions as they all have to contribute to the generation of the functional decryption keys. Tags can be used in the ciphertexts and the keys to specify which inputs can be combined together. As any encryption scheme, DMCFE provides privacy of the plaintexts. But the functions associated to the functional decryption keys might be sensitive too (e.g. a model in machine learning). The function-hiding property has thus been introduced to additionally protect the function evaluated during the decryption process.</p><p> In this paper, we provide new proof techniques to analyze a new concrete construction of function-hiding DMCFE for inner products, with strong security guarantees: the adversary can adaptively query multiple challenge ciphertexts and multiple challenge keys, with unbounded repetitions of the same tags in the ciphertext-queries and a fixed polynomially-large number of repetitions of the same tags in the key-queries. Previous constructions were proven secure in the selective setting only. </p>

Multi-input Attribute-Based Encryption (ABE) is a generalization of key-policy ABE where attributes can be independently encrypted across several ciphertexts, and a joint decryption of these ciphertexts is possible if and only if the combination of attributes satisfies the policy of the decryption key. We extend this model by introducing a new primitive that we call Multi-Client ABE (MC-ABE), which provides the usual enhancements of multi-client functional encryption over multi-input functional encryption. Specifically, we separate the secret keys that are used by the different encryptors and consider the case that some of them may be corrupted by the adversary. Furthermore, we tie each ciphertext to a label and enable a joint decryption of ciphertexts only if all ciphertexts share the same label. We provide constructions of MC-ABE for various policy classes based on SXDH. Notably, we can deal with policies that are not a conjunction of local policies, which has been a limitation of previous constructions from standard assumptions. Subsequently, we introduce the notion of Multi-Client Predicate Encryption (MC-PE) which, in contrast to MC-ABE, does not only guarantee message-hiding but also attribute-hiding. We present a new compiler that turns any constant-arity MC-ABE into an MC-PE for the same arity and policy class. Security is proven under the LWE assumption.

When multiple users have power or rights, there is always the risk of corruption or abuse. Whereas there is no solution to avoid those malicious behaviors, from the users themselves or from external adversaries, one can strongly deter them with tracing capabilities that will later help to revoke the rights or negatively impact the reputation. On the other hand, privacy is an important issue in many applications, which seems in contradiction with traceability. In this paper, we first extend usual tracing techniques based on codes so that not just one contributor can be traced but the full collusion. In a second step, we embed suitable codes into a set~$\mathcal V$ of vectors in such a way that, given a vector~$\mathbf U \in \mathsf{span}(\mathcal V)$, the underlying code can be used to efficiently find a minimal subset~$\mathcal X \subseteq \mathcal V$ such that~$\mathbf U \in \mathsf{span}(\mathcal X)$. To meet privacy requirements, we then make the vectors of~$\mathsf{span}(\cV)$ anonymous while keeping the efficient tracing mechanism. As an interesting application, we formally define the notion of linearly-homomorphic group signatures and propose a construction from our codes: multiple signatures can be combined to sign any linear subspace in an anonymous way, but a tracing authority is able to trace back all the contributors involved in the signatures of that subspace.