In this paper, we propose a novel Central Bank Digital Currency (CBDC) system based on a two-tier architecture, named ARC-CBDC, where the central bank issues digital currency to commercial banks, which in turn manage transactions among anonymous users throughout the currency's lifecycle. Unlike existing systems that offer only conditional anonymity, ARC-CBDC extends traditional electronic cash to provide full user anonymity, even against commercial banks, despite their ability to observe coin accumulation during withdrawals and reductions during deposits. By utilizing BBS+ signatures, users can open bank accounts, withdraw coins, and deposit received coins without revealing their real identities. A distinctive feature of ARC-CBDC is that commercial banks are allowed to modify a recorded transaction only once within a permissioned blockchain shared between the central bank and participating commercial banks. As the trusted authority, the central bank handles coin issuance and enforces financial regulations. To prevent double spending, the central bank performs batch verification of transactions, enabling efficient detection and tracing of double-spent coins. ARC-CBDC is specifically designed with CBDC architectural requirements in mind, introducing novel mechanisms to support strong anonymity and full traceability. Through formal security proofs and performance analysis, we demonstrate that the security of ARC-CBDC relies on standard cryptographic assumptions and that it is both efficient and practical, suitable for implementation on a range of devices, including laptops and mobile phones.

E-petition has played an important role in health and politics that collects public opinions and requests a superior or an authority to take actions towards a health or political problem. However, this activity exposes the privacy of the signers who participate to express opinions. In this paper, we propose a privacy-preserving fine-grained e-petition system that supports attribute-based identity verification for signers, while protecting their privacy. By considering the target groups of signers in a specific health or political petition, an attribute policy is defined to ensure that only the signers with the attributes that satisfy the attribute policy can sign the petition. The fine-grained petition is better than the traditional e-petitions because it can improve the trustworthiness of the petition results via proactive signer selection. Moreover, the new petition system protects the identities of the signers by using the non-interactive zero-knowledge proof system, such that the signers are anonymous in signing petitions. In addition, the proposed petition system supports the tracing of double-signing, a cheating behavior that an anonymous signer can submit more than one signature in a petition without being detected. Finally, we prove that the proposed petition system achieves the desirable security properties, including anonymity, unforgeability, and traceability, and demonstrate that the system is efficient to be implemented on the mobile devices.

In this paper, we propose a new central bank digital currency (CBDC) system based on the two-tier architecture. The proposed system enhances the traditional bank-user framework of electronic cash and employs the commercial banks for account and coin management. The coin splitting is supported during coin withdrawal of users and the coin combination is achieved for coin deposit at the commercial banks, such that the efficiency of coin management is improved. The other distinguished feature is that the proposed system achieves the anonymity against the commercial banks, while enabling the central bank to support user tracing and double-spending prevention. Specifically, by utilizing the BBS+ signatures, the users can create bank accounts, withdraw coins, and deposit the received coins at the commercial banks without exposing their real identities. As a trusted party, the central bank is responsible for money issuing and financial regulation. In addition, to ensure the system inclusive, users can receive payments from others even they do not have bank accounts at commercial banks. Finally, we demonstrate that the proposed system achieves the desirable properties of balance, anonymity, and traceability and show the efficiency and practicality for the implementation on mobile devices.

Realistic speech-driven 3D facial animation is a challenging problem due to the complex relationship between speech and face. In this paper, we propose a deep architecture, called Geometry-guided Dense Perspective Network (GDPnet), to achieve speaker-independent realistic 3D facial animation. The encoder is designed with dense connections to strengthen feature propagation and encourage the re-use of audio features, and the decoder is integrated with an attention mechanism to adaptively recalibrate point-wise feature responses by explicitly modeling interdependencies between different neuron units. We also introduce a non-linear face reconstruction representation as a guidance of latent space to obtain more accurate deformation, which helps solve the geometry-related deformation and is good for generalization across subjects. Huber and HSIC (Hilbert-Schmidt Independence Criterion) constraints are adopted to promote the robustness of our model and to better exploit the non-linear and high-order correlations. Experimental results on the public dataset and real scanned dataset validate the superiority of our proposed GDPnet compared with state-of-the-art model. The code is available for research purposes at http://cic.tju.edu.cn/faculty/likun/projects/GDPnet.