Susceptible data classification and security reassurance in cloud-IoT based computing environment

• DOI: 10.1007/s12046-021-01740-y
• Publication Date: 2021-10-19T16:47:06Z
• Authors: Soumya Ray; Kamta Nath Mishra; Sandip Dutta
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

Susceptible data recognition has become a fundamental requirement in any network administration system. Though, in suitable sharing and usage, the susceptible data could wipe out the user’s privacy. So, susceptible data detection and its security re-assurance in a cloud-IoT (Internet of Things) integrated distributive communication network are mandatory. In this paper, the authors have anticipated novel susceptible data detection and re-assurance algorithms. The algorithms are capable to make out the identical attributes from diverse data sources which are precised by the domain expert. In the proposed method, the sensitivity scores of distinct attributes are measured as significant features for susceptible data identification and assurance. However, the distinctions of sensitivity scores will be able to distinguish the susceptible data from the non-susceptible data in a cloud-IoT integrated distributed computing environment. The authors have explicated various ways through which susceptible data may be exposed in the distributed system environment. Moreover, the authors have proposed novel algorithms for the security re-assurance of static/dynamic susceptible data. The decision tables are considered for each of the definite cases of security re-assurance in a cloud-IoT enabled distributive computing platform. These decision tables will facilitate the network managers to validate the legitimacy of the requests which are arriving from various extents of distributive internetworked systems. In this research work, the results of security re-assurance processes of static and dynamic susceptible data are authenticated through the two dimensional (2D) and three dimensional (3D) graphic representations. The two- and three-dimensional graphical representations designate that the requests initiated from inter/intra networks are being traced and the illegitimate requests are being leftover by the automated model in a cloud-IoT environment. This process will avert the attacks generated from identical internet protocol (IP) addresses. As a summing up it can be said that the research paper primarily emphasizes an innovative approach to recognizing the susceptible data in a cloud-IoT integrated distributive environment and the anticipated technique defends the susceptible data from unlawful admittance by the intruders.