## 2 Summary of This Special Issue  
The articles within the present Special Issue encompass the most promising approaches and ideas across various domains, including sustainable transportation, smart grid technologies, smart healthcare, security and privacy measures, and other pertinent areas.  
[PERSON] et al. (Contribution 1) introduced the dynamic aware transmission range parallel Euclidean distance (DA-TRPED) technique to enhance intelligent vehicular clustering routing protocols. They incorporated heuristic-based solutions within an enhanced ant colony optimizer (ACO) framework to evaluate vehicular nodes based on parallel Euclidean distance (PED), simplifying the search process. This enhancement was reflected in performance metrics such as data packet delivery, data packet drop, lifetime analysis, and other parameters of vehicular ad hoc network (VANET) clustered nodes.  
[PERSON] et al. (Contribution 2) assessed information security risk assessment (ISRA) for advanced metering infrastructure (AMI) by harmonizing evaluation criteria for energy metering systems with ISRA methodologies in smart grid applications. Their study offers an extensive comparison of cutting-edge ISRA techniques, considering various input specifications, tool characteristics, and risk assessment methodologies. Furthermore, the research explored crucial prerequisites for AMI system risk evaluations and matched AMI risk assessment requirements with multiple ISRA approaches to determine the most appropriate method in smart grid contexts.  
[PERSON] et al. (Contribution 3) focused on developing an authentication protocol ensuring data privacy and security in smart city applications while maintaining a minimalist model. The proposed framework enabled secure access to smart city applications via the IoT environment, ensuring mutual authentication between users and gateways. Security analysis confirmed the framework's effectiveness in minimizing energy consumption and computational overhead. Performance evaluation using BAN logic and AVISPA security verification tools demonstrated its reliability and superior performance compared to existing methods.  
[PERSON] et al. (Contribution 4) introduced a novel hybrid trust management approach for enhancing the security and privacy of IoT-based smart parking systems. Integrating machine learning approaches, they focused on trustworthiness, accessibility, and confidence as key parameters. Employing ensemble machine learning techniques, they ensured efficient system performance and reliability, achieving impressive results in identifying and neutralizing malicious or compromised nodes.  
[PERSON] et al. (Contribution 5) presented Covidblock as a blockchain-based decentralized distributed assistance system, aimed at protecting the privacy and security of electronic health records (EHRs) during the pandemic. The researchers suggested a decentralized distributed storage system (DDSS) and a distributed, decentralized resource access control (DDRAC) approach to uphold data privacy. Using an Ethereum test network exhibited Covidblock's real-time functionality and markedly enhanced performance compared to prevailing cloud-based healthcare cyber-physical systems (CPSs) utilizing blockchain methodology.