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Provenance based data integrity checking and verification in cloud environments

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Listed:
  • Muhammad Imran
  • Helmut Hlavacs
  • Inam Ul Haq
  • Bilal Jan
  • Fakhri Alam Khan
  • Awais Ahmad

Abstract

Cloud computing is a recent tendency in IT that moves computing and data away from desktop and hand-held devices into large scale processing hubs and data centers respectively. It has been proposed as an effective solution for data outsourcing and on demand computing to control the rising cost of IT setups and management in enterprises. However, with Cloud platforms user’s data is moved into remotely located storages such that users lose control over their data. This unique feature of the Cloud is facing many security and privacy challenges which need to be clearly understood and resolved. One of the important concerns that needs to be addressed is to provide the proof of data integrity, i.e., correctness of the user’s data stored in the Cloud storage. The data in Clouds is physically not accessible to the users. Therefore, a mechanism is required where users can check if the integrity of their valuable data is maintained or compromised. For this purpose some methods are proposed like mirroring, checksumming and using third party auditors amongst others. However, these methods use extra storage space by maintaining multiple copies of data or the presence of a third party verifier is required. In this paper, we address the problem of proving data integrity in Cloud computing by proposing a scheme through which users are able to check the integrity of their data stored in Clouds. In addition, users can track the violation of data integrity if occurred. For this purpose, we utilize a relatively new concept in the Cloud computing called “Data Provenance”. Our scheme is capable to reduce the need of any third party services, additional hardware support and the replication of data items on client side for integrity checking.

Suggested Citation

  • Muhammad Imran & Helmut Hlavacs & Inam Ul Haq & Bilal Jan & Fakhri Alam Khan & Awais Ahmad, 2017. "Provenance based data integrity checking and verification in cloud environments," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-19, May.
  • Handle: RePEc:plo:pone00:0177576
    DOI: 10.1371/journal.pone.0177576
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    References listed on IDEAS

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    1. Muhammad Imran & Javeria Niazi, 2011. "Infrastructure and Growth," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 50(4), pages 355-364.
    2. Shuai Ding & Chen-Yi Xia & Kai-Le Zhou & Shan-Lin Yang & Jennifer S Shang, 2014. "Decision Support for Personalized Cloud Service Selection through Multi-Attribute Trustworthiness Evaluation," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-11, June.
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