A Confidentiality-based data Classification-as-a-Service (C2aaS) for cloud security

Munwar Ali, Low Tang Jung, Ali Hassan Sodhro, Asif Ali Laghari, Samir Birahim Belhaouari*, Zeeshan Gillani

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

Rapid development and massive use of Information Technology (IT) have since pro-duced a massive amount of electronic data. In tandem, the demand for data outsourcing and the associated data security is increasing exponentially. Small organizations are often finding it expen-sive to save and process their huge amount of data, and keep the data secure from unauthorized access. Cloud computing is a suitable and affordable platform to provide services on user demand. The cloud platform is preferable used by individuals, Small, and Medium Enterprises (SMEs) that cannot afford large-scale hardware, software, and security maintenance cost. Storage and process-ing of big data in the cloud are becoming the key appealing features to SMEs and individuals. How-ever, the processing of big data in the cloud is facing two issues such as security of stored data and system overload due to the volume of the data. These storage methods are plain text storage and encrypted text storage. Both methods have their strengths and limitations. The fundamental issue in plain text storage is the high risk of data security breaches; whereas, in encrypted text storage, the encryption of complete file data may cause system overload. This paper propose a feasible solu-tion to address these issues with a new service model called Confidentiality-based Classification-as -a-Service (C2aaS) that performs data processing by treating data dynamically according to the data security level in preparation for data storing in the cloud. In comparison to the conventional methods, our proposed service model is strongly showing good security for confidential data and is proficient in reducing cloud system overloading.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
Original languageEnglish
Pages (from-to)749-760
Number of pages12
JournalAlexandria Engineering Journal
Volume64
DOIs
Publication statusPublished - 1 Feb 2023

Keywords

  • Cloud storage method
  • Data classification
  • Data confidentiality
  • Security level

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