A Grey Theory Based Approach to Big Data Risk Management Using FMEA

Table 5

Description of dimensions.

Dimension	Description
Identification and access management	Given the opportunity to increase knowledge by accessing big data, it is necessary that only authorized persons can access it; thus, big data requires confidentiality and authenticity; to address this problem, [58] mentioned that sometimes both are needed simultaneously; this source recommended and proposed three different schemes: an encryption scheme, a signature scheme, and a sign-encryption scheme
Device and application registration	Data provenance refers to information about the history of a creation process; in other words, it refers to a mechanism that can be used to validate whether input data is coming from an authenticated source to guarantee a degree of information integrity [59]; then, provenance-related security and trustworthiness issues also arise in the system [60]; they include the registration of devices in machine-to-machine (M2M) and Internet-of-Things (IoT) networks, which can be considered one of the major issues in the area of security [61]
Infrastructure management	As big data physical infrastructures increase, difficulties associated with designing effective physical security also arise; thus, we use the term “system health” to describe the intersection of the information worker and the nominal conditions for infrastructure management monitoring of big data for security purposes, which include technical issues regarding the interoperability of services [62]
Data governance	Data governance can ensure appropriate controls without inhibiting the speed and flexibility of innovative big data approaches and technologies, which need to be established for different management levels with a clear security strategy