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.

Smart grids integrate modern Internet of Things technologies with the traditional grid systems, aiming to achieve effective and reliable electricity distribution as well as promote clean energy development. Nowadays, it is an indispensable infrastructure for smart homes, wisdom medical, intelligent transportation, and various other services. However, when smart meters transmit users’ power consumption data to the control center, sensitive information may be leaked or tampered. Moreover, distributed architecture, fine-grained access control, and user anonymity are also desirable in real-world applications. In this paper, we propose a privacy-preserving data aggregation scheme for a smart grid with user anonymity and designated recipients. Smart meters collect users’ power consumption data, encrypt it using homomorphic re-encryption, and then transmit the ciphertexts anonymously. Afterward, proxies re-encrypt the aggregated data in a distributed fashion so that only the designated recipients can decrypt it. Therefore, our proposed scheme provides a more secure and flexible solution for privacy-preserving data aggregation in smart grids. Security analyses prove that our scheme achieves all the above-mentioned security requirements, and efficiency analyses demonstrate that it is efficient and suitable for real-world applications.

For electronic voting (e-voting) with a trusted authority, the ballots may be discarded or tampered, so it is attractive to eliminate the dependence on the trusted party. An e-voting protocol, where the final voting result can be calculated by any entity, is known as self-tallying e-voting protocol. To the best of our knowledge, addressing both abortive issue and adaptive issue simultaneously is still an open problem in self-tallying e-voting protocols. Combining Ethereum blockchain with cryptographic technologies, we present a decentralized self-tallying e-voting protocol. We solve the above problem efficiently by utilizing optimized Group Encryption Scheme and standard Exponential ElGamal Cryptosystem. We use zero-knowledge proof and homomorphic encryption to protect votes' secrecy and achieve self-tallying. All ballots can be verified by anyone and the final voting result can be calculated by any entity. In addition, using the paradigm of score voting and “1-out-of- $k$ ” proof, our e-voting system is suitable for a wide range of application scenarios. Experiments show that our protocol is more competitive and more suitable for large-scale voting.

Keyword-based auditing (KA) provides a means for users to verify the integrity of only the outsourced data they are interested in. Existing KA schemes employ relation authentication labels to conduct targeted audits with keywords, which significantly improves the cost-effectiveness. However, such schemes typically support only a single-challenge scenario, which may not always be practical. To overcome this constraint, we introduce a hierarchical challenge mechanism grounded in user attributes. This mechanism leverages inequality and affiliation relationships to comply with a predefined tree structure for access policies. Incorporated during the challenge-response phase of the auditing model, it permits users to initiate cross-challenges. Expanding upon this hierarchical mechanism, we propose an attribute-based hierarchical keyword auditing scheme, abbreviated as ${\mathcal{AHKA}}$x . ${\mathcal{AHKA}}$x combines searchable encryption to conduct cross-targeted audits and benefits from the hash collision mapping of Bloom filters to safeguard against keyword guessing attacks. Moreover, we design a fault localization algorithm based on a variant of the binary search technique. It locates in batch the faulty cloud servers and damaged data blocks after an audit failure. As an integral part of ${\mathcal{AHKA}}$x , the algorithm significantly enhances our scheme's practicability. Security analyses indicate that ${\mathcal{AHKA}}$x can effectively withstand both forgery and replace attacks on audit proofs. The smart contract component ensures that our scheme's processes can be monitored and regulated. Experimental data corroborate that deploying ${\mathcal{AHKA}}$x on the client side and on the blockchain is both efficient and feasible.

The goal of the energy internet is to enable communication between distributed energy endpoints to facilitate information exchange and trading matching. Blockchain, which ensures content consistency, bridges the gaps between multiple energy stakeholders and satisfies the need for universal trust. However, applying blockchain directly in peer-to-peer trading can result in the permanent inclusion of illegal or outdated data in blockchain databases, hindering efficient interaction. Driven by emerging application requirements and legal regulations, redactable blockchain (EuroS&P 2017) was introduced, allowing the block history to be rewritten via collisions in chameleon hash functions (CHFs). Nevertheless, current solutions still face challenges, including trapdoor security risks, privacy leakage, and indefinite redactions. This article presents a redactable energy blockchain scheme (REBS) with partially attribute-based policy hiding, which enables controlled multiauthority key generation and redactor attribute verification. To prevent the abuse of redaction permission, REBS employs time-updatable CHFs for redaction. Additionally, we design a delegation algorithm that adds dynamic flexibility to attribute verification nodes, permitting them to delegate key share distribution authority to other nodes on demand. The detailed security proofs and performance evaluations demonstrate the feasibility of REBS.

Fully homomorphic encryption (FHE) fundamentally solves the problems of confidentiality when datas and operations are entrusted to third parties. It can play an important role in secure data computation for Internet of Things (IoT). However, the storage complexities of existing FHE schemes are still not friendly. Our work focuses on optimizing the storage complexity of FHE, in order to further promote the practical process of FHE in IoT. The FHE schemes based on learning with errors (LWE) have become the mainstream of FHE schemes due to its simplicity, security and ease of efficient implementation. The key switching technology is the ingenious and crucial technique that led to LWE-based FHE. By proposing a low-noise key switching technology, and using Bin-LWE assumption twice (first on the public key, and then again on the ciphertext), we design a leveled FHE scheme with small parameters (without expensive bootstrapping technology). Meanwhile, a detailed analysis of noise growth for homomorphic evaluation is made, and the specific security parameters are given.