Multi-input functional encryption is a primitive that allows for the evaluation of an \(\ell \) -ary function over multiple ciphertexts, without learning any information about the underlying plaintexts. This type of computation is useful in many cases where one has to compute over encrypted data, such as privacy-preserving cloud services, federated learning, or more generally delegation of computation from multiple clients. In this work we propose the first secret-key multi-input quadratic functional encryption scheme satisfying simulation security. On contrary, current constructions supporting quadratic functionalities, proposed by Agrawal et al. in CRYPTO ’21 and TCC ’22, only reach indistinguishibility-based security. Our proposed construction is generic, and for a concrete instantiation, we propose a new function-hiding inner-product functional encryption scheme proven simulation secure against one challenge ciphertext in the standard model, which is of independent interest.