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

Forskningsoutput: TidskriftsbidragArtikelPeer review

26 Citeringar (Scopus)
71 Nedladdningar (Pure)

Sammanfattning

Rapid development and massive use of Information Technology (IT) have since produced 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 expensive 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 processing of big data in the cloud are becoming the key appealing features to SMEs and individuals. However, 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 solution 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.

OriginalspråkEngelska
Sidor (från-till)749-760
Antal sidor12
TidskriftAlexandria Engineering Journal
Volym64
DOI
StatusPublicerad - 2022-nov.-02

Nationell ämneskategori

  • Datorsystem (20206)

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