Numerous searchable encryption (SE)-based solutions have been proposed to address the aforementioned issues [5]. SE utilizes the computational power of function sharing (FS) for \(k\) searches without compromising anonymity. However, in large-scale applications involving billions of files and millions of vehicles, the implementation of such a system may be impeded by practical challenges related to effective key management [6]. In practice, it is often necessary to use different encryption keys for various files to enable vehicles to share encrypted data with specific users. Nevertheless, the expenses of setting up trapdoors, carefully keeping keys, and distributing keys rise in tandem with the volume of shared files. Searchable encryption using a key aggregate (KSE) is commonly employed to address the aforementioned challenges [7]. In KSE, vehicles can produce an aggregate key from various classes containing the term \(dr\) by utilizing their secret keys. Although it is a single key, this aggregate key possesses the capability to search for ciphertexts across multiple classes. Moreover, without requiring all of the decryption keys, \(dr\) is authorized to decode vehicle data using the aggregate key, provided that patient consent has been obtained. Nevertheless, certain issues persist [7]. Firstly, existing key search encryption (KSE) methods do not consider the potential for automobiles to provide \(dr\) with \(k\) information. If the \(dr\) is unable to supply \(k\) information, vehicles cannot generate aggregate keys. Secondly, the Function Server (FS) may not be entirely reliable, which raises the possibility of data manipulation. A straightforward approach involves using the data generator (\(dg_{i}\)) to create a bilinear aggregated signature for encrypted text data and contracting with the FS to manage the signature, along with the \(k\) ciphertexts [8]. The FS then provides the matching aggregate signature, along with the corresponding ciphertexts, to the \(dr\). The aggregated signature can then be used by the \(dr\) to confirm the accuracy of the plaintext data that correspond to the encrypted data. Nevertheless, the verification algorithm uses bilinear pairing, which raises the cost considerably. Here, we propose a verified search technique for FB-IAV utilizing secure multiple-key aggregation (MKA). The MKA scheme aggregates keys and generates trapdoors for an authorized \(dr\) by employing key search encryption (KSE) and blockchain technologies [9; 10; 11]. Vehicles can securely collect keys from various categories that contain relevant \(ks\), even when they are unaware of the specific \(k\) details associated with the \(dr\). Additionally, it incorporates an enhanced oblivious method [12] to prevent vehicles from discerning the \(k\) details of the \(dr\). To ensure efficient verification of the search results, we develop a dual provable method that does not rely on bilinear pairings. The main contributions are described as follows. * We utilize smart contracts (\(SCs\)), oblivious search inquiries, and key search encryption (KSE) to develop a Multi-Key Access (MKA) scheme. The aggregation of secure keys and the generation of trapdoors for permitted data retrieval (denoted as \(dr\)) can be accomplished by integrating KSE with an \(SC\). The leakage of \(k\) information related to \(dr\) is effectively mitigated through the use of oblivious search requests. * A dual-verifiable technique is also developed by our team, which utilizes two homomorphic hash functions and their properties. This approach enables the effective verification of the overall search outcome. Additionally, this method notably decreases the communication and computational costs through collaborative confirmation. Additionally, bilinear pairing is not employed in the dual-verifiable algorithm. * We validate the suggested system and perform a thorough security study, showcasing its strong security features.