Security and Privacy Issues in IoT-Based Big Data Cloud Systems in a Digital Twin Scenario

Abstract

Due to its unique type of services, Cloud Computing could operate as a “base technology” for other technologies; this attracts researchers to develop sustainable Cloud systems. It is a new generation of services that offers an opportunity for users to access and manage their information, applications, and data regardless of place and time. Nevertheless, there is a type of service that can include large amounts of data, called Big Data, and it consists of the rapid use of the Internet of Things (IoT) to produce large data sets. In this work, initially, we present Cloud Computing (CC) and Big Data (BD) exported from IoT, focusing on the security and management challenges of both. Notably, we combine the two aforementioned technologies to examine their related characteristics and discover new perspectives and opportunities for their integration and to achieve a sustainable environment called a Digital Twin scenario. Subsequently, we present how Cloud Computing contributes to IoT-based Big Data, aiming to fill a scientific gap in the sector of their integration regarding security and privacy. Finally, we additionally survey the security challenges of the integrated model of BD and CC and then propose a novel security algorithm for sustainable Cloud systems in a Digital Twin scenario. The experimental results presented are based on the use of the encryption algorithms AES, RC5, and RSA, and our proposed model extends the advances of CC and IoT-based BD, offering a highly novel and scalable service platform to achieve better privacy and security services.