Rapid progress in healthcare technology has enabled the adoption of digital twin (DT) systems, allowing accurate simulations and real-time monitoring of patients through their virtual counterparts. Nonetheless, the vast amount of data generated in DT-based healthcare, coupled with privacy concerns and potential threats from quantum computing, poses significant challenges for secure data management. To address these issues, this paper introduces a novel framework, Lightweight Authentication for Post-Quantum Secure Blockchain in Digital Twin Healthcare (LAPQ-BDTH). The proposed scheme utilizes lattice-based cryptography to provide quantum-resistant security and leverages blockchain with smart contracts to achieve immutable, decentralized storage of DT data, thereby improving integrity and transparency. The performance of LAPQ-BDTH is evaluated against several existing authentication and post-quantum schemes, demonstrating its advantages in computational efficiency and communication overhead. Extensive security analysis and performance evaluation confirm that LAPQ-BDTH effectively preserves data confidentiality and integrity. This research lays the foundation for developing secure, resilient, and future-ready healthcare systems.

The integration of Internet of Things (IoT) technologies into modern healthcare systems has significantly enhanced patient care and real-time monitoring. However, this advancement introduces serious security and privacy concerns, such as data breaches, unauthorized access, and identity leakage, which are especially critical in healthcare environments. These threats are further intensified by the emergence of quantum computing, rendering traditional cryptographic schemes increasingly vulnerable. To address these challenges, we propose secure and efficient lattice-based signcryption for blockchain-enabled IoT healthcare (SELSBH ). The scheme leverages the quantum-resistant hardness of the Learning With Errors (LWE) problem to ensure strong confidentiality, authentication, and data integrity. It also supports user anonymity and unlinkability on the blockchain, while maintaining lightweight operations suitable for resource-constrained IoT devices. The security of SELSBH is formally validated using the Scyther tool and the Random Oracle Model (ROM), demonstrating its resilience against both classical and quantum adversaries. Additionally, we conduct a comprehensive performance evaluation by comparing SELSBH with existing protocols in terms of security features, communication cost, and computational efficiency. The results highlight the advantages of SELSBH in achieving a robust, privacy-preserving, and quantum-secure solution for next-generation e-healthcare systems.

This paper aims to present a new multi-attribute group decision-making (MAGDM) approach for solving problems in an uncertain and complex environment. In any MAGDM problem, the key challenge is how to quantify and aggregate the objective uncertainty information contained in the data. To answer this, in this paper, we utilize the idea of linguistic Pythagorean fuzzy set (LP y FS) to describe the information in terms of linguistic membership degree (LMD) and linguistic non-membership degree (LNMD). We first present some new operations of LP y FS, including Aczel–Alsina (AA) sum, AA product, and AA scalar multiplication. At that point, we develop various LP y F aggregation operators which are based on these defined operations, including the LP y F Aczel–Alsina weighted averaging (LP y FAAWA) operator, the LP y F Aczel–Alsina ordered weighted averaging (LP y FAAOWA) operator, LP y F Aczel–Alsina weighted geometric (LP y FAAWG) operator and LP y F Aczel–Alsina ordered weighted geometric (LP y FAAOWG) operator. We configure these operators with different characteristics. It can be seen that the proposed operators have commutativity, monotonicity, boundary, and idempotency properties. Then, we design a new technique dependent on these operators to solve MAGDM problems. The applicability of the established approach is demonstrated through a case study related to smart city development. The result demonstrates the new technique's feasibility and applicability. In the end, sensitivity analysis and a systematic comparison between the prevailing and suggested techniques are given.