VC3: Trustworthy Data Analytics in the Cloud using SGX

被引:366
作者
Schuster, Felix [1 ,2 ]
Costa, Manuel [1 ]
Fournet, Cedric [1 ]
Gkantsidis, Christos [1 ]
Peinado, Marcus [1 ]
Mainar-Ruiz, Gloria [1 ]
Russinovich, Mark [1 ]
机构
[1] Microsoft Res, Cambridge, England
[2] Ruhr Univ Bochum, HGI, Bochum, Germany
来源
2015 IEEE SYMPOSIUM ON SECURITY AND PRIVACY SP 2015 | 2015年
关键词
D O I
10.1109/SP.2015.10
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We present VC3, the first system that allows users to run distributed MapReduce computations in the cloud while keeping their code and data secret, and ensuring the correctness and completeness of their results. VC3 runs on unmodified Hadoop, but crucially keeps Hadoop, the operating system and the hypervisor out of the TCB; thus, confidentiality and integrity are preserved even if these large components are compromised. VC3 relies on SGX processors to isolate memory regions on individual computers, and to deploy new protocols that secure distributed MapReduce computations. VC3 optionally enforces region self-integrity invariants for all MapReduce code running within isolated regions, to prevent attacks due to unsafe memory reads and writes. Experimental results on common benchmarks show that VC3 performs well compared with unprotected Hadoop: VC3' s average runtime overhead is negligible for its base security guarantees, 4.5% with write integrity and 8% with read/write integrity.
引用
收藏
页码:38 / 54
页数:17
相关论文
共 71 条
[1]  
Abadi M., 2005, P 12 ACM C COMP COMM, P340, DOI [10.1145/1102120.1102165, DOI 10.1145/1102120.1102165]
[2]   Preventing memory error exploits with WIT [J].
Akritidis, Periklis ;
Cadar, Cristian ;
Raiciu, Costin ;
Costa, Manuel ;
Castro, Miguel .
PROCEEDINGS OF THE 2008 IEEE SYMPOSIUM ON SECURITY AND PRIVACY, 2008, :263-+
[3]  
Anati I., 2013, PROC INT WORKSHOP HA
[4]  
[Anonymous], 2013, USENIX SEC S
[5]  
[Anonymous], [No title captured]
[6]  
[Anonymous], 2014, USENIX S OP SYST DES
[7]  
[Anonymous], 2004, NIST MODES OPERATION
[8]  
[Anonymous], INT C SUP ICS
[9]  
[Anonymous], Hadoop
[10]  
[Anonymous], MSRTR201439