Minxin Du, Peipei Jiang, Qian Wang, Sherman S. M. Chow, Lingchen Zhao
{"title":"屏蔽图精确分析与SGX","authors":"Minxin Du, Peipei Jiang, Qian Wang, Sherman S. M. Chow, Lingchen Zhao","doi":"10.1109/tdsc.2023.3241164","DOIUrl":null,"url":null,"abstract":"Graphs nicely capture data from various domains, allowing the computations of many analytic tasks via graph queries. Graphs of real-world data are often large, albeit useful, and the involved computation can be too heavyweight for commodity computers. For secure outsourcing, we propose (SGX)<inline-formula><tex-math notation=\"LaTeX\">$^{2}$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mn>2</mml:mn></mml:msup></mml:math><inline-graphic xlink:href=\"wang-ieq1-3241164.gif\"/></alternatives></inline-formula>, a forward-secure structured encryption scheme for graph data, which uses lightweight cryptographic techniques with a trusted execution environment such as SGX. To process million-scale graphs by the limited memory of SGX, we load data on-demand using Dijkstra's algorithm and Fibonacci heap. Compared with most prior graph encryption schemes, (SGX)<inline-formula><tex-math notation=\"LaTeX\">$^{2}$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mn>2</mml:mn></mml:msup></mml:math><inline-graphic xlink:href=\"wang-ieq2-3241164.gif\"/></alternatives></inline-formula> supports exact shortest-distance queries instead of approximation and can be easily extended to other graph-based analytics.","PeriodicalId":13047,"journal":{"name":"IEEE Transactions on Dependable and Secure Computing","volume":null,"pages":null},"PeriodicalIF":7.0000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Shielding Graph for eXact Analytics with SGX\",\"authors\":\"Minxin Du, Peipei Jiang, Qian Wang, Sherman S. M. Chow, Lingchen Zhao\",\"doi\":\"10.1109/tdsc.2023.3241164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Graphs nicely capture data from various domains, allowing the computations of many analytic tasks via graph queries. Graphs of real-world data are often large, albeit useful, and the involved computation can be too heavyweight for commodity computers. For secure outsourcing, we propose (SGX)<inline-formula><tex-math notation=\\\"LaTeX\\\">$^{2}$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mn>2</mml:mn></mml:msup></mml:math><inline-graphic xlink:href=\\\"wang-ieq1-3241164.gif\\\"/></alternatives></inline-formula>, a forward-secure structured encryption scheme for graph data, which uses lightweight cryptographic techniques with a trusted execution environment such as SGX. To process million-scale graphs by the limited memory of SGX, we load data on-demand using Dijkstra's algorithm and Fibonacci heap. Compared with most prior graph encryption schemes, (SGX)<inline-formula><tex-math notation=\\\"LaTeX\\\">$^{2}$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mn>2</mml:mn></mml:msup></mml:math><inline-graphic xlink:href=\\\"wang-ieq2-3241164.gif\\\"/></alternatives></inline-formula> supports exact shortest-distance queries instead of approximation and can be easily extended to other graph-based analytics.\",\"PeriodicalId\":13047,\"journal\":{\"name\":\"IEEE Transactions on Dependable and Secure Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Dependable and Secure Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1109/tdsc.2023.3241164\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Dependable and Secure Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/tdsc.2023.3241164","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Graphs nicely capture data from various domains, allowing the computations of many analytic tasks via graph queries. Graphs of real-world data are often large, albeit useful, and the involved computation can be too heavyweight for commodity computers. For secure outsourcing, we propose (SGX)$^{2}$2, a forward-secure structured encryption scheme for graph data, which uses lightweight cryptographic techniques with a trusted execution environment such as SGX. To process million-scale graphs by the limited memory of SGX, we load data on-demand using Dijkstra's algorithm and Fibonacci heap. Compared with most prior graph encryption schemes, (SGX)$^{2}$2 supports exact shortest-distance queries instead of approximation and can be easily extended to other graph-based analytics.
期刊介绍:
The "IEEE Transactions on Dependable and Secure Computing (TDSC)" is a prestigious journal that publishes high-quality, peer-reviewed research in the field of computer science, specifically targeting the development of dependable and secure computing systems and networks. This journal is dedicated to exploring the fundamental principles, methodologies, and mechanisms that enable the design, modeling, and evaluation of systems that meet the required levels of reliability, security, and performance.
The scope of TDSC includes research on measurement, modeling, and simulation techniques that contribute to the understanding and improvement of system performance under various constraints. It also covers the foundations necessary for the joint evaluation, verification, and design of systems that balance performance, security, and dependability.
By publishing archival research results, TDSC aims to provide a valuable resource for researchers, engineers, and practitioners working in the areas of cybersecurity, fault tolerance, and system reliability. The journal's focus on cutting-edge research ensures that it remains at the forefront of advancements in the field, promoting the development of technologies that are critical for the functioning of modern, complex systems.