A new mechanism to ensure integrity for MapReduce in cloud computing.

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Názov: A new mechanism to ensure integrity for MapReduce in cloud computing.
Autori: Bendahmane, Ahmed, Essaaidi, Mohammad, El moussaoui, Ahmed, Younes, Ali
Zdroj: 2012 International Conference on Multimedia Computing & Systems; 1/ 1/2012, p785-790, 6p
Abstrakt: MapReduce has been widely used as a powerful parallel data processing model and is adopted by most cloud providers to built cloud computing framework. However, in open cloud systems, security of computation becomes a great challenge. Moreover, MapReduce data-processing services are long-running, which increase the opportunity that an adversary launches attack to the workers and make them behave maliciously and, then tamper with the computation integrity of user tasks where their executions are generally performed in different administration domains out of the user control. Thus, the results of the computation might be erroneous and dishonest. In this paper, we propose a new mechanism based on weighted t-first voting method for ensuring the integrity of MapReduce in open cloud computing environment. Our mechanism can defeat both collusive and non-collusive malicious entities and thus guarantee high computation accuracy. [ABSTRACT FROM PUBLISHER]
Copyright of 2012 International Conference on Multimedia Computing & Systems is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A new mechanism to ensure integrity for MapReduce in cloud computing.
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  Data: <searchLink fieldCode="AR" term="%22Bendahmane%2C+Ahmed%22">Bendahmane, Ahmed</searchLink><br /><searchLink fieldCode="AR" term="%22Essaaidi%2C+Mohammad%22">Essaaidi, Mohammad</searchLink><br /><searchLink fieldCode="AR" term="%22El+moussaoui%2C+Ahmed%22">El moussaoui, Ahmed</searchLink><br /><searchLink fieldCode="AR" term="%22Younes%2C+Ali%22">Younes, Ali</searchLink>
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  Data: 2012 International Conference on Multimedia Computing & Systems; 1/ 1/2012, p785-790, 6p
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  Data: MapReduce has been widely used as a powerful parallel data processing model and is adopted by most cloud providers to built cloud computing framework. However, in open cloud systems, security of computation becomes a great challenge. Moreover, MapReduce data-processing services are long-running, which increase the opportunity that an adversary launches attack to the workers and make them behave maliciously and, then tamper with the computation integrity of user tasks where their executions are generally performed in different administration domains out of the user control. Thus, the results of the computation might be erroneous and dishonest. In this paper, we propose a new mechanism based on weighted t-first voting method for ensuring the integrity of MapReduce in open cloud computing environment. Our mechanism can defeat both collusive and non-collusive malicious entities and thus guarantee high computation accuracy. [ABSTRACT FROM PUBLISHER]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of 2012 International Conference on Multimedia Computing & Systems is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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