Open AccessCloud Network Data Acquisition Challenges
Author(s) -
Paula Raymond Lutui,
Brian Cusack
Publication year - 2021
Publication title -
international journal of information, communication technology and applications
Language(s) - English
Resource type - Journals
ISSN - 2205-0930
DOI - 10.17972/ijicta20217153
Subject(s) - cloud computing , computer science , virtualization , vendor , data extraction , consistency (knowledge bases) , context (archaeology) , network virtualization , distributed computing , operating system , artificial intelligence , paleontology , medline , marketing , political science , law , business , biology
The challenge and problem for network investigators is that many of the data repositories are now virtualized and Cloud distributed. This paper reviews the extraction of evidence from virtualized RAM in the Cloud context on two virtual machines. Such evidence informs network system fault correction, and attack diagnosis. The contribution of this research is to promote an awareness of valuable evidence held in Cloud virtual machines, where it is located, and the extraction tools kits required. A challenge for network investigators is the variation in distributed network architecture and protocols. There is little consistency in the Cloud environment beyond proprietary dominance of Cloud services, and vendor virtualization provisions. This exploratory research takes up this challenge and demonstrates a working solution to the extraction of data in Cloud distributed networks.