Privacy protection for fog computing and the internet of things data based on blockchain

Abstract

With the development of the Internet of Things (IoT) field, more and more data are generated by IoT devices and transferred over the network. However, a large amount of IoT data is sensitive, and the leakage of such data is a privacy breach. The security of sensitive IoT data is a big issue, as the data is shared over an insecure network channel. Current solutions include symmetric encryption and access controls to secure the data transfer, but they have some drawbacks such as a single point of failure. Blockchain is a promising distributed ledger technology that can prevent the malicious tampering of data, offering reliable data storage. This paper proposes a distributed access control system based on blockchain technology to secure IoT data. The proposed mechanism is based on fog computing and the concept of the alliance chain. This method uses mixed linear and nonlinear spatiotemporal chaotic systems (MLNCML) and the least significant bit (LSB) to encrypt the IoT data on an edge node and then upload the encrypted data to the cloud. The proposed mechanism can solve the problem of a single point of failure of access control by providing the dynamic and fine-grained access control for IoT data. The experimental results of this method demonstrated that it can protect the privacy of IoT data efficiently.

A systematic review of the purposes of Blockchain and fog computing integration: classification and open issues

“…The authors created a client and web services application that allows users to store and exchange provenance information in a BC using open standards [ 146 ]. To protect IoT data, Liu et al [ 188 ] presented a decentralized access control mechanism based on BC with FC integration. To encrypt IoT data before uploading to the cloud, this technique employs mixed linear and nonlinear spatiotemporal chaotic models, as well as the least significant bit.…”

“…For BC, privacy-preserving strategies based on encryption approaches are evolving, allowing users to become anonymous and have the ability to manage their personal data (e.g., what, whom, and when personal data can be shared in each transaction). Authors proposed several mechanisms to enhance privacy ([ 70 , 88 , 115 , 116 , 162 , 169 , 217 ]); to enable and enhance identification ([ 61 , 129 , 136 , 172 , 174 , 209 , 218 ]), to ensure data privacy ([ 97 , 146 , 188 ]), and to enhance location privacy ([ 83 , 165 , 192 , 198 ]). The majority of the selected studies under this category reported that BC can enhance the level of privacy, in general, followed by identification, and the least purpose mentioned was to achieve data privacy.…”

The Future of Fog Computing in Kenya

“…Fog computing can regulate privacy [17]. Sensitive user data may be evaluated locally instead of centralized cloud infrastructure.…”

Untitled

“…At the same time, these devices, which we unconditionally trust as our digital continuation, constantly interact with each other. The Internet of Things (IoT), defined as "a system of interconnected computing devices with unique identifiers (UIDs) [that] can perform data communications without any human involvement" (Liu et al, 2021(Liu et al, , p. 1331, as well as communication between gadgetswhen your refrigerator can exchange data with your fitness bracelet, for examplefurther exacerbate the problem. For example, some researches have shown that with the advent of the IoT, the possibility of using big data as a source of official statistics is increasingly being considered, creating additional ethical and statistical problems (Tam & Kimb, 2018).…”