In the dynamic landscape of Quantum Software Engineering (QSE), ensuring the integrity of sensitive data is critical, which stipulates integrating security and privacy measures during the Quantum Software Development Life Cycle (QDLC) rather than providing cost-inefficient post-production software fixes. This paper proposes a Quantum Privacy Knowledge Base (QPKB) and Quantum Privacy-Oriented Software Development (QPOSD) approach that integrates privacy and security protocols into quantum hybrid software development, complementing existing software development processes. QPKB is formalized as the interrelationship between five key elements: Quantum Privacy by Design principles, Quantum Privacy Design Strategies, Quantum Privacy Patterns, Quantum Bugs and Vulnerabilities, and Quantum Hybrid Context. The step-by-step methodology for QPOSD spans analysis, design, coding, verification and validation, and deployment phases. With the help of a scenario, we demonstrate how QPOSD can effectively integrate security and privacy imperatives in QDLC. This study acts as a starting point for serving operational guidelines for quantum development teams, providing strategies for integrating privacy and security measures into QSE practices.

Currently and in the near future, Smart Cities are vital to enhance urban living, address resource challenges, optimize infrastructure, and harness technology for sustainability, efficiency, and improved quality of life in rapidly urbanizing environments. Owing to the high usage of networks, sensors, and connected devices, Smart Cities generate a massive amount of data. Therefore, Smart City security concerns encompass data privacy, Internet-of-Things (IoT) vulnerabilities, cyber threats, and urban infrastructure risks, requiring robust solutions to safeguard digital assets, citizens, and critical services. Some solutions include robust cybersecurity measures, data encryption, Artificial Intelligence (AI)-driven threat detection, public–private partnerships, standardized security protocols, and community engagement to foster a resilient and secure smart city ecosystem. For example, Security Information and Event Management (SIEM) helps in real-time monitoring, threat detection, and incident response by aggregating and analyzing security data. To this end, no integrated systems are operating in this context. In this paper, we propose a Hybrid Quantum-Classical Architecture for bolstering Smart City security that exploits Quantum Machine Learning (QML) and SIEM to provide security based on Quantum Artificial Intelligence and patterns/rules. The validity of the hybrid quantum-classical architecture was proven by conducting experiments and a comparison of the QML algorithms with state-of-the-art AI algorithms. We also provide a proof of concept dashboard for the proposed architecture.