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Defeating Colluding Nodes in Desktop Grid Computing Platforms

Bibliographic Details
Main Author: Silaghi, Gheorghe Cosmin
Publication Date: 2009
Other Authors: Araujo, Filipe, Silva, Luis Moura, Domingues, Patricio, Arenas, Alvaro E.
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.8/12896
Summary: Desktop Grid systems reached a preeminent place among the most powerful computing platforms in the planet. Unfortunately, they are extremely vulnerable to mischief, because computing projects exert no administrative or technical control on volunteers. These can very easily output bad results, due to software or hardware glitches (resulting from over-clocking for instance), to get unfair computational credit, or simply to ruin the project. To mitigate this problem, Desktop Grid servers replicate work units and apply majority voting, typically on 2 or 3 results. In this paper, we observe that simple majority voting is powerless against malicious volunteers that collude to attack the project. We argue that to identify this type of attack and to spot colluding nodes, each work unit needs at least 3 voters. In addition, we propose to post-process the voting pools in two steps. i) In the first step, we use a statistical approach to identify nodes that were not colluding, but submitted bad results; ii) then, we use a rather simple principle to go after malicious nodes which acted together: they might have won conflicting voting pools against nodes that were not identified in step i. We use simulation to show that our heuristic can be quite effective against colluding nodes, in scenarios where honest nodes form a majority.
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spelling Defeating Colluding Nodes in Desktop Grid Computing PlatformsDesktop gridsVolunteer computingCollusionReplicationDesktop Grid systems reached a preeminent place among the most powerful computing platforms in the planet. Unfortunately, they are extremely vulnerable to mischief, because computing projects exert no administrative or technical control on volunteers. These can very easily output bad results, due to software or hardware glitches (resulting from over-clocking for instance), to get unfair computational credit, or simply to ruin the project. To mitigate this problem, Desktop Grid servers replicate work units and apply majority voting, typically on 2 or 3 results. In this paper, we observe that simple majority voting is powerless against malicious volunteers that collude to attack the project. We argue that to identify this type of attack and to spot colluding nodes, each work unit needs at least 3 voters. In addition, we propose to post-process the voting pools in two steps. i) In the first step, we use a statistical approach to identify nodes that were not colluding, but submitted bad results; ii) then, we use a rather simple principle to go after malicious nodes which acted together: they might have won conflicting voting pools against nodes that were not identified in step i. We use simulation to show that our heuristic can be quite effective against colluding nodes, in scenarios where honest nodes form a majority.SpringerRepositório IC-OnlineSilaghi, Gheorghe CosminAraujo, FilipeSilva, Luis MouraDomingues, PatricioArenas, Alvaro E.2025-05-16T09:53:55Z2009-08-192009-08-19T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.8/12896eng1570-787310.1007/s10723-009-9124-5info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-05-18T02:31:51Zoai:iconline.ipleiria.pt:10400.8/12896Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T07:35:11.612951Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Defeating Colluding Nodes in Desktop Grid Computing Platforms
title Defeating Colluding Nodes in Desktop Grid Computing Platforms
spellingShingle Defeating Colluding Nodes in Desktop Grid Computing Platforms
Silaghi, Gheorghe Cosmin
Desktop grids
Volunteer computing
Collusion
Replication
title_short Defeating Colluding Nodes in Desktop Grid Computing Platforms
title_full Defeating Colluding Nodes in Desktop Grid Computing Platforms
title_fullStr Defeating Colluding Nodes in Desktop Grid Computing Platforms
title_full_unstemmed Defeating Colluding Nodes in Desktop Grid Computing Platforms
title_sort Defeating Colluding Nodes in Desktop Grid Computing Platforms
author Silaghi, Gheorghe Cosmin
author_facet Silaghi, Gheorghe Cosmin
Araujo, Filipe
Silva, Luis Moura
Domingues, Patricio
Arenas, Alvaro E.
author_role author
author2 Araujo, Filipe
Silva, Luis Moura
Domingues, Patricio
Arenas, Alvaro E.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório IC-Online
dc.contributor.author.fl_str_mv Silaghi, Gheorghe Cosmin
Araujo, Filipe
Silva, Luis Moura
Domingues, Patricio
Arenas, Alvaro E.
dc.subject.por.fl_str_mv Desktop grids
Volunteer computing
Collusion
Replication
topic Desktop grids
Volunteer computing
Collusion
Replication
description Desktop Grid systems reached a preeminent place among the most powerful computing platforms in the planet. Unfortunately, they are extremely vulnerable to mischief, because computing projects exert no administrative or technical control on volunteers. These can very easily output bad results, due to software or hardware glitches (resulting from over-clocking for instance), to get unfair computational credit, or simply to ruin the project. To mitigate this problem, Desktop Grid servers replicate work units and apply majority voting, typically on 2 or 3 results. In this paper, we observe that simple majority voting is powerless against malicious volunteers that collude to attack the project. We argue that to identify this type of attack and to spot colluding nodes, each work unit needs at least 3 voters. In addition, we propose to post-process the voting pools in two steps. i) In the first step, we use a statistical approach to identify nodes that were not colluding, but submitted bad results; ii) then, we use a rather simple principle to go after malicious nodes which acted together: they might have won conflicting voting pools against nodes that were not identified in step i. We use simulation to show that our heuristic can be quite effective against colluding nodes, in scenarios where honest nodes form a majority.
publishDate 2009
dc.date.none.fl_str_mv 2009-08-19
2009-08-19T00:00:00Z
2025-05-16T09:53:55Z
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url http://hdl.handle.net/10400.8/12896
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1570-7873
10.1007/s10723-009-9124-5
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