Reputation-Based Collusion Detection with Majority of Colluders

Junbeom HUR; Mengxue GUO; Younsoo PARK; Chan-Gun LEE; Ho-Hyun PARK

doi:10.1587/transinf.2015EDP7318

Reputation-Based Collusion Detection with Majority of Colluders

Junbeom HUR, Mengxue GUO, Younsoo PARK, Chan-Gun LEE, Ho-Hyun PARK

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The reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.

Publication: IEICE TRANSACTIONS on Information Vol.E99-D No.7 pp.1822-1835

Publication Date: 2016/07/01

Publicized: 2016/04/07

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2015EDP7318

Type of Manuscript: PAPER

Category: Information Network

Authors

Junbeom HUR
  Korea University
Mengxue GUO
  Chung-Ang University
Younsoo PARK
  Chung-Ang University
Chan-Gun LEE
  Chung-Ang University
Ho-Hyun PARK
  Chung-Ang University

Keyword

cloud computing, collusion detection, majority voting, reputation

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Junbeom HUR, Mengxue GUO, Younsoo PARK, Chan-Gun LEE, Ho-Hyun PARK, "Reputation-Based Collusion Detection with Majority of Colluders" in IEICE TRANSACTIONS on Information, vol. E99-D, no. 7, pp. 1822-1835, July 2016, doi: 10.1587/transinf.2015EDP7318.
Abstract: The reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2015EDP7318/_p

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@ARTICLE{e99-d_7_1822,
author={Junbeom HUR, Mengxue GUO, Younsoo PARK, Chan-Gun LEE, Ho-Hyun PARK, },
journal={IEICE TRANSACTIONS on Information},
title={Reputation-Based Collusion Detection with Majority of Colluders},
year={2016},
volume={E99-D},
number={7},
pages={1822-1835},
abstract={The reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.},
keywords={},
doi={10.1587/transinf.2015EDP7318},
ISSN={1745-1361},
month={July},}

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TY - JOUR
TI - Reputation-Based Collusion Detection with Majority of Colluders
T2 - IEICE TRANSACTIONS on Information
SP - 1822
EP - 1835
AU - Junbeom HUR
AU - Mengxue GUO
AU - Younsoo PARK
AU - Chan-Gun LEE
AU - Ho-Hyun PARK
PY - 2016
DO - 10.1587/transinf.2015EDP7318
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2016
AB - The reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.
ER -