New cognitive sharing algorithms for cloud service management

• Published in: Concurrency and computation Vol. 33; no. 23
• Main Authors: Ogiela, Lidia, Ogiela, Marek R.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 10.12.2021; Wiley Subscription Services, Inc
• Subjects: Algorithms; Cloud computing; cognitive sharing algorithms; Data management; information division; Information systems; security protocols; Semantics; service management processes
• ISSN: 1532-0626; 1532-0634
• DOI: 10.1002/cpe.6354

Summary This article will present new classes of confidential data management algorithms for the protection and safeguarding of classified data. These algorithms will constitute a solution dedicated to supporting the process of safeguarding and protecting information with various meanings and in different forms. A special type of data is services, understood as information subject to the processes of management and protection. These processes will be discussed on the example of selected solutions dedicated to the concealment of information with secret character. A novelty presented in this article is the possibility to apply algorithms based on the meaning interpretation of the analyzed data in order to secure the data properly; there is also a possibility of executing the proposed solutions regardless of the structure, in which these solutions are to be implemented. An effective execution of data protection tasks will be discussed on the example of two‐stage secret protection algorithms, that is, the protection of the basic data set and the information set with meanings generated on the basis of the semantic secret analysis. Standard secret division approaches are not dependent on semantic content of shared information. In this article, we will be presented such novel approach, which allow to divide data depending on its semantic meaning or content. The problem of semantic meaning evaluation will be solved using cognitive information systems, allowing to extract meaning hidden in the splitted data.