Weili Wang, Sen Deng, Jianyu Niu, M. Reiter, Yinqian Zhang
{"title":"灌输","authors":"Weili Wang, Sen Deng, Jianyu Niu, M. Reiter, Yinqian Zhang","doi":"10.1145/3548606.3560639","DOIUrl":null,"url":null,"abstract":"This paper presents the first critical analysis of building highly secure, performant, and confidential Byzantine fault-tolerant (BFT) consensus by integrating off-the-shelf crash fault-tolerant (CFT) protocols with trusted execution environments (TEEs). TEEs, like Intel SGX, are CPU extensions that offer applications a secure execution environment with strong integrity and confidentiality guarantees, by leveraging techniques like hardware-assisted isolation, memory encryption, and remote attestation. It has been speculated that when implementing a CFT protocol inside Intel SGX, one would achieve security properties similar to BFT. However, we show in this work that simply combining CFT with SGX does not directly yield a secure BFT protocol, given the wide range of attack vectors on SGX. We systematically study the fallacies in such a strawman design by performing model checking, and propose solutions to enforce safety and liveness. We also present ENGRAFT, a secure enclave-guarded Raft implementation that, firstly, achieves consensus on a cluster of 2f+1 machines tolerating up to f nodes exhibiting Byzantine-fault behavior (but well-behaved enclaves); secondly, offers a new abstraction of confidential consensus for privacy-preserving state machine replication; and finally, allows the reuse of a production-quality Raft implementation, BRaft, in the development of a highly performant BFT system.","PeriodicalId":435197,"journal":{"name":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"ENGRAFT\",\"authors\":\"Weili Wang, Sen Deng, Jianyu Niu, M. Reiter, Yinqian Zhang\",\"doi\":\"10.1145/3548606.3560639\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the first critical analysis of building highly secure, performant, and confidential Byzantine fault-tolerant (BFT) consensus by integrating off-the-shelf crash fault-tolerant (CFT) protocols with trusted execution environments (TEEs). TEEs, like Intel SGX, are CPU extensions that offer applications a secure execution environment with strong integrity and confidentiality guarantees, by leveraging techniques like hardware-assisted isolation, memory encryption, and remote attestation. It has been speculated that when implementing a CFT protocol inside Intel SGX, one would achieve security properties similar to BFT. However, we show in this work that simply combining CFT with SGX does not directly yield a secure BFT protocol, given the wide range of attack vectors on SGX. We systematically study the fallacies in such a strawman design by performing model checking, and propose solutions to enforce safety and liveness. We also present ENGRAFT, a secure enclave-guarded Raft implementation that, firstly, achieves consensus on a cluster of 2f+1 machines tolerating up to f nodes exhibiting Byzantine-fault behavior (but well-behaved enclaves); secondly, offers a new abstraction of confidential consensus for privacy-preserving state machine replication; and finally, allows the reuse of a production-quality Raft implementation, BRaft, in the development of a highly performant BFT system.\",\"PeriodicalId\":435197,\"journal\":{\"name\":\"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3548606.3560639\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3548606.3560639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents the first critical analysis of building highly secure, performant, and confidential Byzantine fault-tolerant (BFT) consensus by integrating off-the-shelf crash fault-tolerant (CFT) protocols with trusted execution environments (TEEs). TEEs, like Intel SGX, are CPU extensions that offer applications a secure execution environment with strong integrity and confidentiality guarantees, by leveraging techniques like hardware-assisted isolation, memory encryption, and remote attestation. It has been speculated that when implementing a CFT protocol inside Intel SGX, one would achieve security properties similar to BFT. However, we show in this work that simply combining CFT with SGX does not directly yield a secure BFT protocol, given the wide range of attack vectors on SGX. We systematically study the fallacies in such a strawman design by performing model checking, and propose solutions to enforce safety and liveness. We also present ENGRAFT, a secure enclave-guarded Raft implementation that, firstly, achieves consensus on a cluster of 2f+1 machines tolerating up to f nodes exhibiting Byzantine-fault behavior (but well-behaved enclaves); secondly, offers a new abstraction of confidential consensus for privacy-preserving state machine replication; and finally, allows the reuse of a production-quality Raft implementation, BRaft, in the development of a highly performant BFT system.