As traditional computing and cloud computing integrate, the Internet of Things (IoT) has evolved into a layered and cloud-network-edge-end architecture. However, most searchable encryption models still use triples, in which hierarchical structures are neglected, and insecure intermediate nodes are exposed to external environment. Meanwhile, mainstream schemes adopting accurate retrieval are incompatible with IoT end users' features of differentiation. To address these issues, we innovatively design an efficient and credible search model with an accurate multikeyword fuzzy ciphertext retrieval scheme in the context of IoT. First, based on network coding and key sharing, data are grouped, encoded, and transmitted in parallel to the receiver node through middle-layer nodes, with high efficiency and reliability. Second, to realize fuzzy retrieval of IoT, edit distance is selected as the standard of difference between keywords, and then document index vector and query vector are created based on locality sensitive hashing (LSH) and Bloom Filter. Furthermore, to improve the traditional scheme, query keywords are split into multiple single-word forms, inner products between each trapdoor of single word and encryption index vector are calculated, respectively, for the sum of each inner product and thus $$\mathrm{top}$$-$$k$$ sorting search. Ultimately, feasibility, safety, and efficiency of our improved scheme are verified by security analysis, while simulation results support that our scheme has better accuracy and efficiency.