By increasing smart objects as high-potential computing devices and 5G technology, the Internet of Things (IoT) has emerging technology to provide a data-centric infrastructure for detecting safe device-to-device communications by supporting security and privacy issues. As 5G-enabled communication technology, Vehicle-to-Vehicle (V2V) communication provides a wirelessly exchange information connection between smart vehicles, intelligent devices and cloud-edge computing environment. This connection should be established with a safe and secured run-time protection system to avoid many critical anomalies and misbehavior problems. Detecting run-time malicious transformations with data-centric misbehaving reactions is a main challenge for autonomous vehicle communications with 5G-enabled communication technology. This paper provides a hybrid Genetic Algorithm-based Ensemble Bagged Trees (GA-EBT) algorithm for a data-centric misbehavior detection approach to support the V2V communications against malicious and misbehavior transactions. For evaluation of the proposed algorithm, four real test-cases are applied for messaging injection attacks in the V2V environments with compare to the state-of-the-art machine learning algorithms. The experimental results show that the proposed hybrid approach can achieve to optimal high rate accuracy factor with 99.999, precision and recall factors with 100% and F1-Score factor with 100% to detect unexpected cyber-attacks for the V2V communications in the IoT environment.

The extension of emerging renewable energy sources such as wind and water turbines, solar panels, and the increasing usage of electric vehicles requires the supply and distribution of energy in a small device on local scale and it has created new methods of supplying and selling electricity. Middle buyers and end users can obtain the local energy with the peer-to-peer trading method in this large and hierarchical market. This method enables market to manage and exchange the electricity between major suppliers and medium and local levels. Blockchain technology is developing in peer-to-peer exchange of electricity and acts as a reliable, efficient and safe technology in the electricity trading market. In this method, while preserving the privacy of electricity users, by using smart contracts and by removing intermediaries in the energy supply and demand market, direct commercial interactions between energy suppliers and consumers are done. The Blockchain technology, while creating trust between the parties in the energy market, reduces the cost of electricity trading and increases its scalability with using the intermediate energy aggregators. In this research, the blockchain-based model, is presented for distribution and peer-to-peer transactions in the energy market. The suggested model provides the possibility of registration low-cost instant transactions at the power grid in any specific period of time. The above method, unlike periodic payments, provides immediate access to bills and small payments. Since the transactions outside the blockchain chain are not recorded, this system guarantees its honest and independent operation without fraud and failure. The smart contract method based on blockchain, reduces the transaction fees and speeds up electricity trading.