Abstract
With the rapid development of the Internet of Things (IoT), more and more user devices access the network and generate large amounts of genome data. These genome data possess significant medical value when researched. However, traditional genome analysis confronts security and efficiency challenges, including access pattern leakage, low efficiency, and single analysis methods. Thus, we propose a secure and efficient dynamic analysis scheme for genome data within a Software Guard Extension (SGX)-assisted server, called SEDASGX. Our approach involves designing a secure analysis framework based on SGXs and implementing various analysis methods within the enclave. The access pattern of genome data is always obfuscated during the analysis and update process, ensuring privacy and security. Furthermore, our scheme not only achieves higher analysis efficiency but also enables dynamic updating of genome data. Our results indicate that the SEDASGX analysis method is nearly 2.5 times more efficient than non-SGX methods, significantly enhancing the analysis speed of large-scale genome data.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
