As a decentralized, public, and digital ledger technology in Peer-to-Peer network, blockchain has received much attention from various fields, including finance, healthcare, supply chain, etc. However, some challenges (e.g., scalability, privacy, and security issues) severely affects the wide adoption of blockchain technology. Recently, Intel software guard extensions (SGX), as new trusted computing technologies, have provided a new solution to the above challenges in the blockchain area. Although many studies have focused on using SGX technology to enhance their schemes in the blockchain areas, no comprehensive survey has systematically analyzed and delineated these studies. This paper is the first to systematically discuss the application status of SGX in the blockchain area. In this paper, we study the scheme designs, advantages, and disadvantages of the existing works using a six-layer hierarchical structure of the blockchain. We also summarize the functions of SGX and formally analyze the advantages and disadvantages of SGX. Finally, we review the remaining challenges and present a list of possible directions for future research.

Despite the existence of data privacy regulations, such as the general data protection regulation (GDPR), data leaks in the Internet of Things (IoT) still occur and cause significant harm due to the noncompliance of data users. To address this issue, a notable solution involves recording the process in an open, immutable blockchain and utilizing the trusted execution environment (TEE) for reliable compliance verification. Although substantial progress has been made in designing compliance schemes in recent years, current approaches suffer from various limitations, including compliance incompleteness, regulation faultiness, and privacy leak. This article introduces PACTA, an IoT data privacy regulation compliance scheme that leverages TEE and blockchain technology. In the protocol, PACTA efficiently handles both dynamic and static consent of data owners and utilizes TEE for compliance analysis of requests and processes. By storing encrypted critical data, the blockchain facilitates privacy-preserving audits of the entire compliance process. Additionally, we have designed a challenge–response protocol to address the silent behavior of the TEE. We demonstrate that PACTA effectively enforces regulation compliance while safeguarding privacy. We thoroughly evaluate our implementation’s efficiency and effectiveness using Ethereum and Intel SGX platforms.

Privacy-preserving distributed data fusion is a pretreatment process in data mining involving security models. In this paper, we present a method of implementing multi-party data fusion, wherein redundant attributes of a same set of individuals are stored by multiple parties. In particular, the merged data does not suffer from background attacks or other reasoning attacks, and individual attributes are not leaked. To achieve this, we present three algorithms that satisfy K-Anonymous and differential privacy. Experimental results on real data sets suggest that the proposed algorithm can effectively preserve information in data mining tasks.