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Forensics Readiness survey in cloud computing with a meta-analysis approach
Kristyan S.A.a, Suhardia
a Sekolah Teknik Elektro Dan Informatika, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.Cloud computing is one of the fastest growing technologies in the history of computing. It also changes the way of information technology to manage, access, provide and create services. Cloud computing also brings many benefits to end users and organizations. However, the rapid growth of cloud computing has made a new arena of crime called cybercrime. This poses new challenges in technical, legal and governance matters such as how to conduct appropriate digital investigations in the cloud environment and how to proactively collect data before incidents occur to save time, money and effort. This study aims to get the most ideal model/framework for forensics readiness on the cloud from previously published research. This paper discusses the literature study using a meta-analysis approach that applies social network analysis from 38 papers that discuss forensic readiness with its supporting factors. From the results of the study it is known that the ideal framework was proposed by Elyas 2014 with thirteen factors, which can be seen from the results of the calculation of social network analysis with the value betweenness centrality obtained value of 0.037 which shows the highest value of all the models previously studied. This value comes from a number of factors (after normalization) used by the model proposed by Elyas 2014 compared to other researchers.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Betweenness centrality,Cloud environments,Digital investigation,Forensic readiness,Forensics readiness,History of computing,Literature studies,Meta analysis[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Forensics readiness,Meta-analysis,Social-network analysis[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICITSI.2018.8695992[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]