Efficient data management techniques based on hierarchical IoT privacy using block chains in cloud environments

As cloud services become so ubiquitous that they can be used anytime, anywhere, there is an increasing interest in IoT privacy protection. Manufacturers of small and medium-sized businesses that produce IT devices are increasingly using a variety of technologies to easily connect to other devices, with ease and affordability. However, the importance of protection against IoT privacy is growing as devices connected to the Internet do not know what information is transmitted by third parties. In this paper, we propose an IoT privacy protection technique in which users’ privacy-related elements are classified into block chains and non-block chains so that the third parties do not use the information used in the cloud environment maliciously, so that users’ privacy can be handled probabilistically by grouping them into service chains. The proposed model uses user privacy information as a block chain to handle identity attributes and access control policies so that IoT privacy information is not exposed to third parties. This process can be used to protect users’ privacy, regardless of the size or purpose of the cloud environment. In the proposed technique, IoT privacy was grouped into hierarchical multilevel forms, while efficiency was improved by an average of 11.1% using computational-intensive cryptographic policies. In addition, because the proposed technique has improved the accessibility of IoT privacy information over the existing one, it has reduced the overhead of cloud servers by more than 17.2%.