Analysis and Evaluation of Intel Software Guard Extension-Based Trusted Execution Environment Usage in Edge Intelligence and Internet of Things Scenarios

Zhiyuan Wang and Yuezhi Zhou ()
Additional contact information
Zhiyuan Wang: Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
Yuezhi Zhou: Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China

Future Internet, 2025, vol. 17, issue 1, 1-24

Abstract: With the extensive deployment and application of the Internet of Things (IoT), 5G and 6G technologies and edge intelligence, the volume of data generated by IoT and the number of intelligence applications derived from these data are rapidly growing. However, the absence of effective mechanisms to safeguard the vast data generated by IoT, along with the security and privacy of edge intelligence applications, hinders their further development and adoption. In recent years, Trusted Execution Environment (TEE) has emerged as a promising technology for securing cloud data storage and cloud processing, demonstrating significant potential for ensuring data and application confidentiality in more scenarios. Nevertheless, applying TEE technology to enhance security in IoT and edge intelligence scenarios still presents several challenges. This paper investigates the technical challenges faced by current TEE solutions, such as performance overhead and I/O security issues, in the context of the resource constraints and data mobility that are inherent to IoT and edge intelligence applications. Using Intel Software Guard Extensions (SGX) technology as a case study, this paper validates these challenges through extensive experiments. The results provide critical assessments and analyses essential for advancing the development and usage of TEE in IoT and edge intelligence scenarios.

Keywords: Trusted Execution Environment (TEE); Software Guard Extensions (SGX); Internet of Things (IoT); edge intelligence; performance evaluation; security (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1999-5903/17/1/32/pdf (application/pdf)
https://www.mdpi.com/1999-5903/17/1/32/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jftint:v:17:y:2025:i:1:p:32-:d:1565992

Access Statistics for this article

Future Internet is currently edited by Ms. Grace You

More articles in Future Internet from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().