The rapid growth in the NFT (Non-fungible token) market has offered a wide variety of opportunities for scammers, fraudsters, wash tradings, and so on. One of the most urgent security issues is how to efficiently authorize and validate the ownership to make the NFT ecosystem avoid infringement and counterfeiting. By exploiting linear homomorphic tagging and robust digital watermarking technologies, this article proposes a generic framework for ownership authorization and batch validation of NFTs. Within this framework, the digital artwork creators can authorize the ownership to a buyer before the NFT is minted in the public blockchain. Anytime in the future who questions the ownership of a claimant can initiate a validation procedure to get an auditing report by running a Challenge-Response protocol that supports efficient batch verification. The completeness and soundness of the proposed framework have been proven by assuming a secure homomorphic tag scheme and a robust watermarking scheme. We also present instantiations of the generic construction, especially with$\Pi _{Pub}$, one can outsource the validation procedure to the public blockchain to release local computation burden. A series of elaborated experiments have shown our proposed framework is practical and efficient.

Crowdsourcing for healthcare, which is an application of crowd intelligence, has become a novel and important auxiliary way for traditional healthcare, showing a huge application perspective. In a crowdsourcing platform for healthcare, patients can act as requesters who recruit workers, such as doctors, to provide professional advice by posting a task. However, privacy concerns pose a significant obstacle for patients willing to participate in crowdsourcing, as task data often contain sensitive personal information. To address this issue, we propose a novel attribute-based, lightweight, and dynamic fine-grained worker selection scheme, called ABCrowdMed, with privacy-preserving features. With this scheme, requesters can select workers in a non-interactive way by using a novel CP-ABE scheme that incorporates online/offline encryption, verifiable outsourcing decryption, revocation, and hidden policy properties. Additionally, requesters can revoke and update their tasks by withdrawing some workers’ decryption privileges. Participants can also release the computation burden with the aid of a third-party server. The proposed scheme’s security has been proven to be selectively secure under the decisional$ (q-1)$assumption and satisfies forward/backward security. The performance of ABCrowdMed has been evaluated and compared with state-of-art schemes, with the results demonstrating that our scheme achieves the lowest computation and is suitable for resource-constrained settings.