Smart grid systems have become popular and necessary for the development of a sustainable power grid. These systems use different technologies to provide optimized services to the users of the network. Regarding computing, these systems optimize electrical services by processing a large amount of the data generated. However, privacy and security are essential in this kind of system. With a large amount of data generated, it is necessary to protect the privacy of users, because this data may reveal the users’ personal information. Today, blockchain technology has proven to be an efficient architecture for solving privacy and security problems in different scenarios. Over the years, different blockchain platforms have emerged, attempting to solve specific problems in different areas. However, the use of different platforms fragmented the market, which was no different in the smart grid scenario. This work proposes a blockchain architecture that uses sidechains to make the system scalable and adaptable. We used three blockchains to ensure privacy, security, and trust in the system. To universalize the proposed solution, we used the Open Smart Grid Protocol and smart contracts. The results show that architecture security and privacy are guaranteed, making it feasible for implementation in real systems; although scalability issues regarding the storage of the data generated still exist.

Since the early 2000s, life in cities has changed significantly due to the Internet of Things (IoT). This concept enables developers to integrate different devices collecting, storing, and processing a large amount of data, enabling new services to improve various professional and personal activities. However, privacy issues arise with a large amount of data generated, and solutions based on blockchain technology and smart contract have been developed to address these issues. Nevertheless, several issues must still be taken into account when developing blockchain architectures aimed at the IoT scenario because security flaws still exist in smart contracts, mainly due to the lack of ease when building the code. This article presents a blockchain storage architecture focused on license plate recognition (LPR) systems for smart cities focusing on privacy, performance, and security. The proposed architecture relies on the Ethereum platform. Each smart contract matches the privacy preferences of a license plate to be anonymized through public encryption. The storage of data captured by the LPR system can only be done if the smart contract enables it. However, in the case of motivation foreseen by the legislation, a competent user can change the smart contract and enable the storage of the data captured by the LPR system. Experimental results show that the performance of the proposed architecture is satisfactory, regarding the scalability of the built private network. Furthermore, tests on our smart contract using security and structure analysis tools on the developed script demonstrate that our solution is fraud-proof. The results obtained in all experiments bring evidence that our architecture is feasible to be used in real scenarios.

With the popularization of the Internet-of-Things, various applications have emerged to make life easier. These applications generate a large amount of user data. Analyzing the data obtained from these applications, one can infer personal information about each user. Considering this, it is clear that ensuring privacy in this type of application is essential. To guarantee privacy various solutions exist, one of them is UbiPri middleware. This paper presents a decentralized implementation of UbiPri middleware using the Ethereum blockchain. Smart contracts were used in conjunction with a communication gateway and a distributed storage service to ensure users privacy. The results obtained show that the implementation of this work ensures privacy at different levels, data storage security, and performance regarding scalability in the Internet of Things environments.

With the evolution of technology over the years, it has become possible to develop intelligent environments based on the concept of the Internet of Things, distributed systems, and machine learning. Such environments are infused with various solutions to solve user demands from services. One of these solutions is the Ubiquitous Privacy (UBIPRI) middleware, whose central concept is to maintain privacy in smart environments and to receive notifications as one of its services. However, this service is freely performed, disregarding the privacy that the environment employs. Another consideration is that, based on the researched related work, it was possible to identify that the authors do not use statistical hypothesis tests in their solutions developed in the presented context. This work proposes an architecture for notification management in smart environments, composed by a notification manager named Privacy Notification Manager (PRINM) to assign it to UBIPRI and to aim to perform experiments between classification algorithms to delimit which one is most feasible to implement in the PRINM decision-making mechanism. The experiments showed that the J48 algorithm obtained the best results compared to the other algorithms tested and compared.

This work presents a simulation model for point-to-point transmission of encrypted data using the application layer of Open Smart Grid Protocol (OSGP). The simulation aims to verify the integrity of the data transmitted from one point to another using Power Line Communication (PLC). The simulation model was developed in MATLAB and uses RSA, AES, RC-6, and 3-DES cryptographies to encode data. Data transmission uses PLC technique with Gaussian Minimmum Shift Key (GMSK) modulation. Results demonstrate that it is possible to use the OSGP protocol in the application layer with different criteria, which can be used according to the data size. It was applied a Additive White Gaussian Noise (AWGN) in the transmission to simulate the effects that exist in a real network. The experiments demonstrate that RC-6 outperforms the other cryptographic algorithms, presenting the smallest execution time, with low memory requirements.