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The concept of smart cities has emerged as an ongoing research in recent years. In this case, there is a proven association between the smart cities and the smart devices, which have caused the power systems to become more flexible, controllable and detectable. Along with these promising results, many disputes have been generated over the cyber-attacks as unpredictable destructive threats, if not properly repelled, which could seriously endanger the power system. With this in mind, this paper explores a novel stochastic virtual assignment (SVA) method based on a directed acyclic graph (DAG) approach, where the essential data of the system sections are broadcasted decentralized through the data blocks, as a worthwhile step to deal with the cyber attacks’ risk. To do so, an additional security layer is added to the data blocks aiming to enhance the security of the data against the long lasting data sampling by virtually assigning the hash addresses (HAs) to the data blocks, which are randomly changed based on a stochastic process. The basic network architecture is based on a Provchain structure as a new framework to constantly monitor data operation. Two pivotal strategies also represented to deal with the energy and time needed for the HAs generation process, which have improved the proposed method. In this paper, the proposed security framework is implemented in a smart city environment to provide a secure energy transaction platform. Results show the authenticity of this model and demonstrate the effectiveness of the SVA method in decreasing the successful probability of cyber threat, increasing the time needed for the cyber attacker to decrypt and manipulate the data block. [ABSTRACT FROM AUTHOR]

• Providing a management framework for enhancing the efficiency of the smart city. • Collaborative operation of smart cities considering water, heat, cooling and electrical system. • Introducing an allocation algorithm of the subway synergism hub. • Modeling of the traffic jam and the recharging lines of smart transportation systems. • Developing a secure energy and data transactions framework. This paper is centered on establishing a secure framework for the optimal concurrent operation of a smart city, encompassing transportation, water, heat, electrical, and cooling energy systems. The studied smart city includes the microgrid, smart transportation system (STS), energy hub (EH) and smart grid. In this regard, a subway synergism hub (SSH) as a new non-energy system is added to the smart city with the aim of serving the subway's water, heat, electrical and cooling demands as well as diminishing the operation cost of the smart city. The EH within the SSH cooperated with a desalination unit is considered to supply the subway's stations water demand by using the sea water. The investigation of the optimal allocation of the SSH unit for reducing the cost of smart city operation is also conducted by introducing a novel intelligent priority selection (IPS) analytical algorithm. In comparison to common meta-heuristic algorithms for allocation problems, the accurate optimal solution can be found in low runtime by the IPS algorithm. To achieve an accurate model of the smart city, directed acyclic graph (DAG) based blockchain approach is provided which can enhance the data and energy exchanges security within the smart city. This research paper introduces a security framework deployed in a smart city setting to establish a secure platform for energy transactions. The findings validate the effectiveness of this model and highlight the value of the IPS method. The effectiveness of the suggested approach has been assessed using the smart city system is comprised of various sections, including EVs, smart grid, microgrid, and SSH, demonstrating the credibility and accuracy of this study. [ABSTRACT FROM AUTHOR]

• Co-dynamic-static model of energy management in real community transportation system • DAG based modified blockchain framework to manage a reliable and decentralized smart city • Uncertainty quantization based on copula-PEM for EV traffic flow This paper addresses a secured co-dynamic model for the energy management of Electrical Vehicles (EVs) within the real community transportation system (RCTS). The proposed model aims to facilitate interoperability among mobile energy resources within the smart city, enabling the RCTS to model the co-dynamic-static transportation systems (TSs) simultaneously. The energy management model within the traffic flow system focuses on dynamic assignment, considering the power consumption associated with the density of moving vehicles. EVs play a key role in economically managing energy in both static and dynamic behaviors within charging stations while aligning with the current traffic flow. To enhance data security within the smart city ecosystem, a directed acyclic graph (DAG)-based decentralized cyber security approach is recommended. This approach ensures that data transactions involving mobile energy resources are secured against cyber-attacks through the use of public, private, and transaction blocks. Additionally, an uncertainty-based copula function is presented to create a precise management environment within the smart city. The results indicate that the proposed model for transportation energy resources tends to reduce energy costs by optimally controlling energy consumption within traffic flow, compared to normal conditions. [ABSTRACT FROM AUTHOR]