{"title":"使用可信执行的实用卷隐藏范围可搜索对称加密","authors":"Xu Yang, Ke Li, Saiyu Qi, Hongguang Zhao","doi":"10.1016/j.future.2025.107930","DOIUrl":null,"url":null,"abstract":"<div><div>Searchable symmetric encryption (SSE) enables clients to securely outsource private data to cloud servers while preserving search functionality. Addressing the increasing demand for range queries, which involve matching documents to fields with a range of keywords, remains a challenge. Existing volume-hiding range query schemes fail to address volume pattern leakage during the document fetch phase and lack support for dynamic operations such as addition and deletion of documents. To overcome these limitations, we propose EDVHRQ, an efficient, dynamic, and volume-hiding range query scheme enabled by Intel SGX. Our scheme introduces novel strategies: (1) packetization, which conceals response sizes while minimizing server storage and communication costs, and (2) the optimal best range cover (OBRC) method, which transforms query ranges into a minimal set of trapdoors to accelerate range queries. Unlike existing solutions, EDVHRQ achieves a single roundtrip query process between the client and the cloud server. We formally analyze the security guarantees of EDVHRQ, demonstrating its robustness against volume pattern leakage. Experimental evaluations highlight its superior performance, achieving up to 18.8<span><math><mo>×</mo></math></span> and 56.5<span><math><mo>×</mo></math></span> <em>faster</em> query execution compared to HybrIDX and SEAL, respectively, while significantly reducing server storage costs.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"174 ","pages":"Article 107930"},"PeriodicalIF":6.2000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Practical volume-hiding range searchable symmetric encryption using trusted execution\",\"authors\":\"Xu Yang, Ke Li, Saiyu Qi, Hongguang Zhao\",\"doi\":\"10.1016/j.future.2025.107930\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Searchable symmetric encryption (SSE) enables clients to securely outsource private data to cloud servers while preserving search functionality. Addressing the increasing demand for range queries, which involve matching documents to fields with a range of keywords, remains a challenge. Existing volume-hiding range query schemes fail to address volume pattern leakage during the document fetch phase and lack support for dynamic operations such as addition and deletion of documents. To overcome these limitations, we propose EDVHRQ, an efficient, dynamic, and volume-hiding range query scheme enabled by Intel SGX. Our scheme introduces novel strategies: (1) packetization, which conceals response sizes while minimizing server storage and communication costs, and (2) the optimal best range cover (OBRC) method, which transforms query ranges into a minimal set of trapdoors to accelerate range queries. Unlike existing solutions, EDVHRQ achieves a single roundtrip query process between the client and the cloud server. We formally analyze the security guarantees of EDVHRQ, demonstrating its robustness against volume pattern leakage. Experimental evaluations highlight its superior performance, achieving up to 18.8<span><math><mo>×</mo></math></span> and 56.5<span><math><mo>×</mo></math></span> <em>faster</em> query execution compared to HybrIDX and SEAL, respectively, while significantly reducing server storage costs.</div></div>\",\"PeriodicalId\":55132,\"journal\":{\"name\":\"Future Generation Computer Systems-The International Journal of Escience\",\"volume\":\"174 \",\"pages\":\"Article 107930\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2025-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Future Generation Computer Systems-The International Journal of Escience\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167739X25002250\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Generation Computer Systems-The International Journal of Escience","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167739X25002250","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Practical volume-hiding range searchable symmetric encryption using trusted execution
Searchable symmetric encryption (SSE) enables clients to securely outsource private data to cloud servers while preserving search functionality. Addressing the increasing demand for range queries, which involve matching documents to fields with a range of keywords, remains a challenge. Existing volume-hiding range query schemes fail to address volume pattern leakage during the document fetch phase and lack support for dynamic operations such as addition and deletion of documents. To overcome these limitations, we propose EDVHRQ, an efficient, dynamic, and volume-hiding range query scheme enabled by Intel SGX. Our scheme introduces novel strategies: (1) packetization, which conceals response sizes while minimizing server storage and communication costs, and (2) the optimal best range cover (OBRC) method, which transforms query ranges into a minimal set of trapdoors to accelerate range queries. Unlike existing solutions, EDVHRQ achieves a single roundtrip query process between the client and the cloud server. We formally analyze the security guarantees of EDVHRQ, demonstrating its robustness against volume pattern leakage. Experimental evaluations highlight its superior performance, achieving up to 18.8 and 56.5 faster query execution compared to HybrIDX and SEAL, respectively, while significantly reducing server storage costs.
期刊介绍:
Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications.
Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration.
Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.