Post-Quantum Link-based Ring Signature Model and Artificial Bee Colony (ABC) Algorithm for Effective Data Management in IoT-based Smart Cities

<ns7:p>Background The Internet of Things (IoT) is a swiftly advancing technology with wide-ranging applications in smart cities, where substantial data exchange and real-time services necessitate high standards of security, privacy, and operational efficiency. Current IoT frameworks frequently face difficulties in delivering strong protection against emerging post-quantum threats while also preserving system performance, especially in decentralized and data-heavy smart city settings. Methods To tackle these issues, this article introduces a Post-Quantum Ring Signature and ABC-based Effective IoT (PQRAEI) framework. This model combines blockchain technology, post-quantum cryptography, and hybrid swarm optimization methods. Initially, data preprocessing is conducted using the K-Nearest Neighbour (KNN) algorithm for data imputation and min–max scaling for normalization. Secure and privacy-preserving decentralized transactions are guaranteed through a Post-Quantum Linkable Ring Signature (PQLRS) scheme, which functions through a three-phase cryptographic process. Additionally, air quality forecasting is improved using an Artificial Bee Colony (ABC) optimization algorithm enhanced with Q-learning, facilitating efficient exploration and identification of optimal environmental parameters that affect the Air Quality Index (AQI). Results The effectiveness of the proposed PQRAEI framework is assessed against existing models, specifically FHPCC, ELDSE, and PQBFR, utilizing metrics such as signing time, verification time, Peak Signal-to-Noise Ratio (PSNR), latency, and throughput. Experimental findings indicate that PQRAEI achieves significantly reduced latency and increased throughput, while ensuring strong cryptographic efficiency and data integrity in comparison to the benchmark models. Conclusions The proposed PQRAEI framework significantly improves security, privacy, and performance in IoT-based smart city environments. By utilizing post-quantum cryptography, blockchain, and intelligent swarm optimization, the model offers a scalable and future-ready solution.</ns7:p>