An Architectural Framework for Metadata and Examine Its Impact On Security Indicators in This Area

In emerging metadata technology, the collection, processing, data mining,
and extraction of knowledge from a wide variety of large amounts of data is
performed by complex software systems such as Hadoop. Optimizing the opportunities
created and managing security threats and challenges in this area
requires considering all aspects and processes in the form of an architectural
framework. The main objective of this study is to provide an architectural
framework for metadata. To do this, the components of the initial framework
are modified and reviewed by comparing and critically reviewing the research
conducted through interviews with experts, and then, its effect on metadata
security indicators using structural equation modeling and software Smart
PLS Quantitatively was evaluated. This research is applied in terms of purpose
and descriptive-survey in terms of method. The statistical population
also includes 55 experts in organizational architecture and cyberspace security,
of which 35 were selected as the statistical sample. The research findings
confirm the proper fit of the proposed architectural framework and the
significant impact of its components on metadata security.