IEICE TRANSACTIONS on Communications
Towards Trusted Result Verification in Mass Data Processing Service
Summary :
Computation integrity is difficult to verify when mass data processing is outsourced. Current integrity protection mechanisms and policies verify results generated by participating nodes within a computing environment of service providers (SP), which cannot prevent the subjective cheating of SPs. This paper provides an analysis and modeling of computation integrity for mass data processing services. A third-party sampling-result verification method, named TS-TRV, is proposed to prevent lazy cheating by SPs. TS-TRV is a general solution of verification on the intermediate results of common MapReduce jobs, and it utilizes the powerful computing capability of SPs to support verification computing, thus lessening the computing and transmission burdens of the verifier. Theoretical analysis indicates that TS-TRV is effective on detecting the incorrect results with no false positivity and almost no false negativity, while ensuring the authenticity of sampling. Intensive experiments show that the cheating detection rate of TS-TRV achieves over 99% with only a few samples needed, the computation overhead is mainly on the SP, while the network transmission overhead of TS-TRV is only O(log N).
- Publication
- IEICE TRANSACTIONS on Communications Vol.E97-B No.1 pp.19-28
- Publication Date
- 2014/01/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E97.B.19
- Type of Manuscript
- Special Section PAPER (Special Section on Management for Flexible ICT Systems and Services)
- Category
Authors
Yan DING
National University of Defense Technology
Huaimin WANG
National University of Defense Technology
Peichang SHI
National University of Defense Technology
Hongyi FU
National University of Defense Technology
Xinhai XU
National University of Defense Technology
Keyword
Latest Issue
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Yan DING, Huaimin WANG, Peichang SHI, Hongyi FU, Xinhai XU, "Towards Trusted Result Verification in Mass Data Processing Service" in IEICE TRANSACTIONS on Communications,
vol. E97-B, no. 1, pp. 19-28, January 2014, doi: 10.1587/transcom.E97.B.19.
Abstract: Computation integrity is difficult to verify when mass data processing is outsourced. Current integrity protection mechanisms and policies verify results generated by participating nodes within a computing environment of service providers (SP), which cannot prevent the subjective cheating of SPs. This paper provides an analysis and modeling of computation integrity for mass data processing services. A third-party sampling-result verification method, named TS-TRV, is proposed to prevent lazy cheating by SPs. TS-TRV is a general solution of verification on the intermediate results of common MapReduce jobs, and it utilizes the powerful computing capability of SPs to support verification computing, thus lessening the computing and transmission burdens of the verifier. Theoretical analysis indicates that TS-TRV is effective on detecting the incorrect results with no false positivity and almost no false negativity, while ensuring the authenticity of sampling. Intensive experiments show that the cheating detection rate of TS-TRV achieves over 99% with only a few samples needed, the computation overhead is mainly on the SP, while the network transmission overhead of TS-TRV is only O(log N).
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E97.B.19/_p
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@ARTICLE{e97-b_1_19,
author={Yan DING, Huaimin WANG, Peichang SHI, Hongyi FU, Xinhai XU, },
journal={IEICE TRANSACTIONS on Communications},
title={Towards Trusted Result Verification in Mass Data Processing Service},
year={2014},
volume={E97-B},
number={1},
pages={19-28},
abstract={Computation integrity is difficult to verify when mass data processing is outsourced. Current integrity protection mechanisms and policies verify results generated by participating nodes within a computing environment of service providers (SP), which cannot prevent the subjective cheating of SPs. This paper provides an analysis and modeling of computation integrity for mass data processing services. A third-party sampling-result verification method, named TS-TRV, is proposed to prevent lazy cheating by SPs. TS-TRV is a general solution of verification on the intermediate results of common MapReduce jobs, and it utilizes the powerful computing capability of SPs to support verification computing, thus lessening the computing and transmission burdens of the verifier. Theoretical analysis indicates that TS-TRV is effective on detecting the incorrect results with no false positivity and almost no false negativity, while ensuring the authenticity of sampling. Intensive experiments show that the cheating detection rate of TS-TRV achieves over 99% with only a few samples needed, the computation overhead is mainly on the SP, while the network transmission overhead of TS-TRV is only O(log N).},
keywords={},
doi={10.1587/transcom.E97.B.19},
ISSN={1745-1345},
month={January},}
Copy
TY - JOUR
TI - Towards Trusted Result Verification in Mass Data Processing Service
T2 - IEICE TRANSACTIONS on Communications
SP - 19
EP - 28
AU - Yan DING
AU - Huaimin WANG
AU - Peichang SHI
AU - Hongyi FU
AU - Xinhai XU
PY - 2014
DO - 10.1587/transcom.E97.B.19
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E97-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2014
AB - Computation integrity is difficult to verify when mass data processing is outsourced. Current integrity protection mechanisms and policies verify results generated by participating nodes within a computing environment of service providers (SP), which cannot prevent the subjective cheating of SPs. This paper provides an analysis and modeling of computation integrity for mass data processing services. A third-party sampling-result verification method, named TS-TRV, is proposed to prevent lazy cheating by SPs. TS-TRV is a general solution of verification on the intermediate results of common MapReduce jobs, and it utilizes the powerful computing capability of SPs to support verification computing, thus lessening the computing and transmission burdens of the verifier. Theoretical analysis indicates that TS-TRV is effective on detecting the incorrect results with no false positivity and almost no false negativity, while ensuring the authenticity of sampling. Intensive experiments show that the cheating detection rate of TS-TRV achieves over 99% with only a few samples needed, the computation overhead is mainly on the SP, while the network transmission overhead of TS-TRV is only O(log N).
ER -
English
