Paper 2025/423

Multi-Client Attribute-Based Unbounded Inner Product Functional Encryption, and More

Abstract

This paper presents the concept of a multi-client functional encryption (MC-FE) scheme for attribute-based inner product functions (AB-IP), initially proposed by Abdalla et al. [ASIACRYPT’20], in an unbounded setting. In such a setting, the setup is independent of vector length constraints, allowing secret keys to support functions of arbitrary lengths, and clients can dynamically choose vector lengths during encryption. The functionality outputs the sum of inner products if vector lengths and indices meet a specific relation, and all clients’ attributes satisfy the key’s policy. We propose the following constructions based on the matrix decisional Diffie-Hellman assumption in a natural permissive setting of unboundedness: – the first multi-client attribute-based unbounded IPFE (MC-AB-UIPFE) scheme secure in the standard model, overcoming previous limitations where clients could only encrypt fixed-length data; – the first multi-input AB-UIPFE (MI-AB-UIPFE) in the public key setting; improving upon prior bounded constructions under the same assumption; – the first dynamic decentralized UIPFE (DD-UIPFE); enhancing the dynamism property of prior works. Technically, we follow the blueprint of Agrawal et al. [CRYPTO’23] but begin with a new unbounded FE called extended slotted unbounded IPFE. We first construct a single-input AB-UIPFE in the standard model and then extend it to multi-input settings. In a nutshell, our work demonstrates the applicability of function-hiding security of IPFE in realizing variants of multi-input FE capable of encoding unbounded length vectors both at the time of key generation and encryption.