DocumentCode
724620
Title
VC3: Trustworthy Data Analytics in the Cloud Using SGX
Author
Schuster, Felix ; Costa, Manuel ; Fournet, Cedric ; Gkantsidis, Christos ; Peinado, Marcus ; Mainar-Ruiz, Gloria ; Russinovich, Mark
fYear
2015
fDate
17-21 May 2015
Firstpage
38
Lastpage
54
Abstract
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 hyper visor 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.
Keywords
cloud computing; data analysis; data integrity; trusted computing; SGX; TCB; VC3; average runtime overhead; base security guarantees; cloud; hypervisor; memory regions; read-write integrity; region self-integrity invariants; secure distributed MapReduce computations; trustworthy data analytics; unmodified Hadoop; Encryption; Operating systems; Program processors; Protocols; Virtual machine monitors;
fLanguage
English
Publisher
ieee
Conference_Titel
Security and Privacy (SP), 2015 IEEE Symposium on
Conference_Location
San Jose, CA
ISSN
1081-6011
Type
conf
DOI
10.1109/SP.2015.10
Filename
7163017
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