Multi-view clustering (MVC) methods based on non-negative matrix factorization (NMF) have gained popularity owing to their ability to provide interpretable clustering results. However, these NMF-based MVC methods generally process each view independently and thus ignore the potential relationship between views. Besides, they are limited in the ability to capture nonlinear data structures. To overcome these weaknesses and inspired by deep learning, we propose a multi-view clustering method based on deep non-negative tensor factorization (MVC-DNTF). With deep tensor factorization, our method can well exploit the spatial structure of the original data and is capable of extracting more deep and nonlinear features embedded in different views. To further extract the complementary information of different views, we adopt the weighted tensor Schatten p-norm regularization term. An optimization algorithm is developed to effectively solve the MVC-DNTF objective. Extensive experiments are performed to demonstrate the effectiveness and superiority of our method.

Mobile Crowdsourcing (MCS) is a widely adopted data collection method that utilizes ubiquitous mobile devices as sensors. The centralized nature of traditional MCS introduces certain weaknesses, leading to a growing interest in blockchainbased MCS. Although decentralized MCS proves to be effective, it also presents several privacy and trust concerns. Specifically, ensuring node trust authentication in an anonymous and decentralized manner is critical due to the susceptibility of a trustworthy and decentralized MCS platform to various attacks. Nevertheless, the absence of a centralized and trusted entity in blockchain poses significant challenges in managing node keys for authentication. Moreover, trust often conflicts with privacy, and the transparency of blockchain further complicates the achievement of anonymous authentication while preserving privacy. To address these challenges, we propose a scheme for decentralized anonymous authentication based on threshold and partial blind signature, which provides a key alternation service. The proposed scheme enables trust credential issuance without disclosing the linkable relationship between the public keys before and after the alternation. Extensive analyses and experiments are conducted to demonstrate the security and efficiency of the proposed scheme.