The rapid spread of misinformation on social media has underscored the importance of automatic fact-checking. Existing fact-checking pipelines typically rely on multi-stage frameworks involving evidence retrieval and claim verification. However, these methods face two major challenges: (1) the retrieval process often introduces noisy evidence, which compromises the reliability of the final veracity prediction; and (2) the verification models may overlook critical factual details, resulting in hallucinated conclusions. To address these issues, we propose a fact-checking framework SLED with Self-supervised denoising evidence retrieval and LLM-Enhanced Debate-based verification. In the retrieval stage, SLED leverage trained verifier to assess credibility and necessity of retrieved evidence, enabling the elimination of noisy evidence. In the verification stage, SLED prompts the LLM to generate dual-perspective reasoning and simulates a multi-agent debate, followed by distillation into a lightweight model for final veracity prediction. Experiments on CHEF and HOVER datasets demonstrate that SLED achieves the state-of-the-art results in complex fact verification scenarios.

Voting protocols are fundamental in modern society. With the ongoing evolution of communication technology and the Internet of Things, the importance of electronic voting protocols is anticipated to experience a significant rise in the advancement of smart cities. Leveraging the blockchain’s tamper-resistant and publicly verifiable properties, along with the concept of enabling all participants to tally election results, blockchain-based self-tallying voting protocols effectively address the shortcomings of centralized traditional electronic voting. However, existing voting protocols still face the dual challenge of security and efficiency. The primary issues include the difficulty in ensuring voter anonymity and election fairness, as well as the insufficient system robustness and low tallying efficiency resulting from security design. To tackle these concerns, we propose a novel approach to constructing efficient and flexible voting protocols that concurrently ensure fairness and anonymity. Specifically, we encapsulate the decryption private keys corresponding to the public keys of encrypted ballots in time capsules to safeguard voting fairness. Additionally, based on our proposed approach, we construct an efficient and flexible score voting protocol for smart cities. The protocol employs traceable ring signature to protect the voter anonymity and public traceability, utilizes a dual-key additive homomorphic ElGamal encryption to encapsulate ballots. We also improve signature-based set membership proofs to verify the validity of ballots. Furthermore, through security analysis and performance evaluation, we demonstrate that our proposed protocol meets all security objectives with reasonable costs.

To overcome the challenges of urbanization and population growth, smart cities use cutting-edge technologies, such as IoT and AI to offer improved public services. Although these advancements have brought convenience, they have raised security and privacy concerns. Blockchain technology has the potential to address these concerns, but existing blockchain frameworks have issues of scalability and efficiency that hinder their ability to meet the smart city demands. In this article, we propose a novel blockchain framework for smart cities, named SC-Chain. Specifically, SC-Chain incorporates a decentralized access mechanism that leverages threshold signatures and BFT-like consensus for efficient node registration and authentication in decentralized systems. Furthermore, we propose a consensus mechanism that utilizes the verifiable random function (VRF) to achieve efficient miner node election, ensuring efficiency, fairness, and security in large-scale smart city systems. We demonstrate the effectiveness and feasibility of the SC-Chain through theoretical analysis and simulations, showcasing its potential to enable the development of secure and efficient smart city infrastructure.

The attribute-based encryption (ABE) scheme, which can set specific conditions to control user access to data, has been widely studied and applied to cloud storage services. Considering file hierarchy in practical scenarios, the ABE scheme can set a hierarchical access control policy so multiple files can be associated with one access structure to reduce users’ computing overhead and save the cloud server’s storage space. However, the existing systems have the risk of user collusion due to the hierarchical access control structure parameters. This paper proposes a secure file hierarchy ABE scheme supporting user collusion resistance (CR-FH-CPABE) in cloud computing. We add a data noise vector without changing the hierarchical access control structure to prevent user ultra vires. Technically, we break the relationships that colluding users could exploit, prevent malicious users from colluding with their computing results, and extract meaningful information from the ciphertext. In addition, we provide an improved CR-FH-CPABE scheme with outsourced decryption, which helps resource-limited devices obtain computing services. Finally, we demonstrate our scheme is CPA secure and show outstanding performance through simulation results.

The fine grain of ciphertext-policy attribute-based encryption (CP-ABE) offers advantages through the amalgamation of key and user attributes; however, it also brings the issue of key misuse. To circumvent the tracking mechanisms of the white-box algorithm, malicious users manipulate the decryption key and encryption algorithm, encapsulating them to create a black-box decryption device. This necessitates black-box traceability for supervision purposes. In this article, we employ$n$-bit encrypted binary vectors to depict the user’s identity and subsequently convert it into partial decryption privileges. When encrypting plaintext, data owners can utilize a “vague specification” to define the identity vector of qualified decryptors. Furthermore, based on the vague specification mechanism, we have devised a pioneering active black-box tracing algorithm. Integrating this algorithm with CP-ABE, we propose the black-box traceable CP-ABE (EIV-BT-ABE) scheme. Our EIV-BT-ABE scheme attains strong traceability with low time complexity, effectively reducing decryption and encryption time costs. The experiment substantiated the efficiency of our scheme while demonstrating its adherence to IND-CPA security.

The smart grid, which is an important component of smart cities, is developing rapidly nowadays, while the confidentiality and integrity of consumption data of customers become significant security issues. Although existing privacy-preserving aggregation schemes reduce the communication overhead and protect the privacy of users’ multidimensional power data, most of them are vulnerable and possess no quantum-resistant properties. In this article, we combine the Chinese remainder theorem (CRT) and the bit decomposition method to provide multibit homomorphic properties for the quantum-resistant algorithm number theory research unit (NTRU), and propose the partial-homomorphic NTRU (PH-NTRU). Then, based on the algorithm, we design the lattice-based multidimensional data privacy-preserving data aggregation scheme named FTCR-LMPPDA, in which the edge devices work as aggregator gateways. Specifically, smart meters participating in the aggregation process share zero-sum numbers to resist collusion attacks. Error retransmission mechanism and random number reconstruction algorithm are introduced to enhance the robustness of this scheme and provide our system with the ability to recover from faults. In addition, security analysis shows our scheme can resist quantum attacks, collusion attacks, and other internal and external attacks as well as keep the security features, such as confidentiality, privacy and integrity of users’ data. Finally, performance evaluation demonstrates that our scheme is more efficient than existing schemes and is more suitable for devices with constrained resources.

Modern business models improve the efficiency of supply chain management by attaching tags to products. These tagged products typically change owners multiple times during their life cycles. The ownership transfer protocol authorizes the new owner by replacing the old owner’s authentication information stored in the tag with the new owner’s. Until now, a considerable amount of literature has proposed solutions to the problem of RFID ownership transfer. Unfortunately, these existing protocols are either flawed in some security properties especially in protecting new and old owners’ privacy, or are associated with huge computational overheads. In this article, we propose an ultralightweight RFID ownership transfer protocol based on permutation function. The tag and reader only use efficient bit operations, which greatly reduce the computational overhead. An important feature of the proposed protocol is that the new owner can impose calculations on data that has been encrypted by the old owner. The new owner is authorized by the old owner and does not have access to the tag’s key, which protects the old owner’s privacy stored in the tag side. We compare our protocol with existing work, and show the advantages in terms of security, computational overhead, and time cost.

With the rapid growth of data, limited by the storage capacity, more and more IoT applications choose to outsource data to Cloud Service Providers (CSPs). But, in such scenarios, outsourced data in cloud storage can be easily corrupted and difficult to be found in time, which brings about potential security issues. Thus, Provable Data Possession (PDP) protocol has been extensively researched due to its capability of supporting efficient audit for outsourced data in cloud. However, most PDP schemes require the Third-Party Auditor (TPA) to audit data for Data Owners (DOs), which requires the TPA to be trustworthy and fair. To eliminate the TPA, we present a Public Mutual Audit Blockchain (PMAB) for outsourced data in cloud storage. We first propose an audit chain architecture based on Ouroboros and an incentive mechanism based on credit to allow CSPs to audit each other mutually with anticollusion (any CSP is not willing to help other CSPs conceal data problems). Then, we design an audit protocol to achieve public audit efficiently with low cost of audit verification. Rigorous analysis explains the security of PMAB using game theory, and performance analysis shows the efficiency of PMAB using the real-world dataset.

As the number of people using social networks increases, users are often assigned to different domains for better digital right management. However, they are no longer satisfied with accessing data just in one domain with the rapid expansion of information, so there is an urgent need for a way to access data among different domains while guarantee their privacy and security. In this paper, we propose a cross-domain access control scheme based on multi-authority attribute-based encryption for big data from social networks. In our construction, we use a hybrid encryption algorithm that based on symmetric encryption and CP-ABE not only to achieve cross-domain access control, but also to improve the efficiency of the system. Besides, the trusted proxy users for proper storage of symmetric keys ensures the security of the system. Meanwhile, the use of an inter-domain trusted proxy user, instead of an intra-domain data owner to formulate an access control policy, reduces the huge computational overhead associated with the ciphertext re-encryption technology and greatly improves the efficiency of the entire system. Finally, security analysis and performance analysis show that the proposed scheme is a secure and trusted networking.