Blockchain technology (BCT) provides a new way to mitigate the default risks of lease contracts resulting from the information asymmetry in leasing. The conceptual architecture of a consortium blockchain-based leasing platform (CBLP) is first proposed to facilitate information sharing between small and medium-sized enterprises (SMEs, the “lessees”) and leasing firms (LFs, the “lessors”). Then, based on evolutionary game theory (EGT), this study builds a two-party game model and analyzes the influences of four types of factors (i.e., information sharing, credit, incentive–penalty, and risk) on SMEs’ contract compliance or default behaviors with/without blockchain empowerment. The primary findings of this study are as follows: (1) SMEs and LFs eventually evolve to implement the ideal “win–win” strategies of complying with the contract and adopting BCT. (2) The large residual value of the leased asset can tempt SMEs to conduct a default action of unauthorized asset disposal, while leading LFs to access the CBLP to utilize information shared on-chain. (3) When the maintenance service is outsourced instead of being provided by lessors, the maintenance fee is not a core determinant affecting the equilibrium state. (4) There is a critical value concerning the default penalty on-chain to incentivize the involved parties to keep their commitments. (5) The capability of utilizing information, storage overhead, and security risk should all be taken into consideration when deciding on the optimal strategies for SMEs and LFs. This study provides comprehensive insights for designing an incentive mechanism to encourage lessees and lessors to cooperatively construct a sustainable and trustworthy leasing environment.

Ensuring edge data integrity is crucial for reliable and secure low-latency services in mobile edge computing. However, existing edge data integrity (EDI) schemes suffer from certain limitations. These include the generation of excessive communication overhead and significant time consumption due to multi-round communications between application vendors and individual edge servers during the integrity verification process. Additionally, there is a notable straggler effect when employing batch verification techniques. To overcome these challenges, this paper presents a pioneering solution scheme for per-edge one-round EDI, referred to as OR-EDI. The proposed scheme effectively mitigates communication overhead, reduces time consumption, and eliminates the straggler effect, while simultaneously maintaining a high level of corruption detection accuracy. To implement OR-EDI, we introduce a novel verification structure known as the Minimal Verification Tree (MVT) and devise algorithms for acquiring Auxiliary Verification Information (AVI) and constructing the MVT. To comprehensively evaluate the performance of OR-EDI, we conduct a rigorous analysis that encompasses its correctness, efficiency, and security aspects. Furthermore, we implement the proposed scheme and perform a comparative assessment against existing EDI schemes, presenting extensive experimental results. These results affirm the effectiveness and efficiency of OR-EDI in effectively addressing the challenges associated with EDI.

To accurately retrieve similar objects from different domains, domain adaptive retrieval method is applied to cope with the domain shift problem in information retrieval. However, existing methods still have two problems: a) they fail to filter out low-confidence samples, leading to error accumulation; and b) they ignore the negative effect of domain discrepancy. To address these two issues, we propose an efficient method called Dynamic Confidence Sampling and Label Semantic Guidance Learning (DCS-LSG). First, Dynamic Confidence Sampling (DCS) is employed to dynamically select high-confidence samples from the target domain so as to improve the effectiveness of learning. Second, Label Semantic Guidance (LSG) learning is presented to enhance the label semantics of features during domain adaptive retrieval. In addition, we introduce a Dual-Projection Relaxation (DPR) strategy to learn more effective features on two specific projection spaces. At last, a two-step hashing strategy is used to generate high-quality hash codes. Experiments on multiple cross-domain retrieval datasets demonstrate that the proposed DCS-LSG can achieve a significant performance improvement. The source code is available at https://github.com/Kybin-kb/DCS-LSG-code/tree/master .

Mobile edge computing allows for high-performance and low-latency applications by delegating computation and data processing tasks to edge servers. However, ensuring the integrity of cached data on these servers can be challenging due to their limited resources. Current designs often use a per-edge multi-round approach, which necessitates multiple communication rounds between each edge server and the application vendor (AppVend). This approach results in high communication and computational costs, as well as the stragglers effect during batch verification. To address these inefficiencies, we propose a Hierarchical Signature Aggregation for Edge Data Integrity (HSA-EDI) verification design. Our design adopts a novel per-edge one-round approach, which significantly reduce the number of communication rounds to one for each edge server, while mitigating the impact of stragglers. Furthermore, it remarkably reduces computational costs through a hierarchical aggregation mechanism. This mechanism supports intra-edge signature aggregation at the edge server level, followed by inter-edge aggregation at the AppVend, which enhances overall efficiency. We then conduct a theoretical analysis of HSA-EDI’s correctness, security, and communication, computation, and storage efficiency. Experimental results validate its superior performance over state-of-the-art designs.

Ensuring data integrity in edge computing environments presents significant challenges, primarily due to the distributed architecture of edge servers and the inherent risk of data corruption. Traditional edge data integrity (EDI) verification methods predominantly rely on sampling techniques, provide only probabilistic integrity assurances and often struggle with scalability and efficient corruption localization. To overcome these limitations, we introduce the deterministic integrity assurance and rapid corruption localization EDI (DL-EDI) verification scheme, a novel approach that combines extended Merkle grid (EM-Grid) with Boneh–Lynn–Shacham (BLS) signatures. DL-EDI leverages EM-Grid for comprehensive data integrity verification, ensuring deterministic integrity validation across all data blocks while facilitating rapid block corruption localization. Additionally, we incorporate a hierarchical signature aggregation method using BLS signatures to optimize verification efficiency and minimize communication and computational overhead. A thorough performance analysis of DL-EDI is conducted, evaluating its verification accuracy, communication and computational efficiency, and resilience against various security threats. Comparative experimental evaluations of DL-EDI against four established EDI schemes highlight its superior effectiveness and efficiency in addressing the challenges of EDI.