Compound Facial Expressions consist of multiple basic expressions and present increased complexity in recognition tasks. Enhancing the representation of primary and secondary expressions is critical for improving the classification performance. However, when features are enhanced indiscriminately, irrelevant information may also be amplified, leading to the ‘Indiscriminate Enhancement Trap' and robustness degradation. To address these issues, we propose a novel Bi-Enhancement based Disentangled Dual-Attention (BED2A) Framework. The bi-enhancement strategy is devised to achieve signal complementarity between channel and spatial features. By transferring semantic information from channel attention to spatial attention in the latent space, the proposed method enhances the ability to localize salient regions. Subsequently, primary and secondary expression features are disentangled across tri-branch feature enhancement architecture, thereby enabling more effective dual-attention based classification. Specifically, the Differential Cross-Consistency mechanism is introduced to disentangle inter-expression features and enhance the precision of expression representations. Dual-Attention mechanism leverages attention to primary and secondary expressions to optimize the classification center and improve inter class separability. Experimental results demonstrate that BED2A effectively optimizes feature enhancement to improve robustness, achieving state-of-the-art performance.

Passwordless user authentication schemes with FIDO as the standard have been widely deployed in web applications. Users use hardware tokens to store their identity credentials (i.e., signing keys) and implement strong authentication through a challenge-response mechanism, avoiding the security risks associated with traditional password-based authentication. Distributed Web services can greatly alleviate the system reliability problem caused by single points of failure, and thus have received increasing attention and research. In distributed systems, resources are distributed across multiple servers, and users must interact with them (or a subset of them in thresholding) to obtain network services. User authentication among the distributed (threshold) systems also poses a challenge: how to ensure security and ease of use at the same time? In particular, users need to authenticate to multiple servers when accessing distributed services, and in the case of using FIDO authentication, users need to authenticate to each server using challenge-response authentication, which will greatly reduce the user experience. In this work, we propose the concept namedThreshold Passwordless Authentication(ThPlA) to address this issue. ThPlA allows users to authenticate to at-of-nthresholding system. ThPlA is designed to be compatible with existing FIDO tokens and requires no extra hardware modifications; the user only needs to interact with the hardware token once during an authentication session; and on the service side, the servers do not need to communicate with each other. ThPlA is based on the component namedNon-interactive Threshold Nonce Generation(NI-ThNG), which extends the two-party challenge-response mechanism tot-of-nsettings. We provide a formal definition of ThPlA and NI-ThNG and give practical constructions. We also provide a performance evaluation of ThPlA and NI-ThNG, respectively. Our experimental results show that the schemes are efficient and practical for real-world applications, even in large-scale distributed systems.

The MPC-in-the-Head framework has been proposed as a solution for Non-Interactive Zero-Knowledge Arguments of Knowledge (NIZKAoK) due to its efficient proof generation. However, most existing NIZKAoK constructions using this approach require multiple MPC evaluations to achieve negligible soundness error, resulting in proof size and time that are asymptotically at least λ times the size of the circuit of the NP relation. In this paper, we propose a novel method to eliminate the need for repeated MPC evaluations, resulting in a NIZKAoK protocol for any NP relation that we call Diet. The proof size and time of Diet are asymptotically only polylogarithmic with respect to the size of the circuit C of the NP relation, but are independent of the security parameter λ. Hence, both the proof size and time can be significantly reduced.Moreover, Diet offers promising concrete efficiency for proving Learning With Errors (LWE) problems and its variants. Our solution provides significant advantages over other schemes in terms of both proof size and proof time, when considering both factors together. Specifically, Diet is a promising method for proving knowledge of secret keys for lattice-based key encapsulation mechanisms (KEMs) such as Frodo and Kyber, offering a practical solution to future post-quantum certificate management. For Kyber 512, our implementation achieves an online proof size of 83.65 kilobytes (KB) with a preprocessing overhead of 152.02KB. The implementation is highly efficient, with an online proof time of only 0.68 seconds and a preprocessing time of 0.81 seconds. Notably, our approach provides the first reported implementation of proving knowledge of secret keys for Kyber 512 using post-quantum primitives-based zero-knowledge proofs.