Visible to the public One Quantifiable Security Evaluation Model for Cloud Computing Platform

TitleOne Quantifiable Security Evaluation Model for Cloud Computing Platform
Publication TypeConference Paper
Year of Publication2018
AuthorsSun, A., Gao, G., Ji, T., Tu, X.
Conference Name2018 Sixth International Conference on Advanced Cloud and Big Data (CBD)
ISBN Number978-1-5386-8034-6
KeywordsAPI, application program interfaces, application security, cloud computing, cloud computing platform, cloud resources, Computational modeling, dynamic security scanning score, Engines, G-Cloud platform, graph theory, maintenance engineering, mixed cloud, multiple clouds, private cloud, pubcrawl, public cloud, quantifiable evaluation, quantifiable security evaluation model, resilience, Resiliency, security, security of data, security recovery engine, security scanning engine, security situation, security view, Security Visualization, System recovery, visual display module, visual graphs, visualization
Abstract

Whatever one public cloud, private cloud or a mixed cloud, the users lack of effective security quantifiable evaluation methods to grasp the security situation of its own information infrastructure on the whole. This paper provides a quantifiable security evaluation system for different clouds that can be accessed by consistent API. The evaluation system includes security scanning engine, security recovery engine, security quantifiable evaluation model, visual display module and etc. The security evaluation model composes of a set of evaluation elements corresponding different fields, such as computing, storage, network, maintenance, application security and etc. Each element is assigned a three tuple on vulnerabilities, score and repair method. The system adopts ``One vote vetoed'' mechanism for one field to count its score and adds up the summary as the total score, and to create one security view. We implement the quantifiable evaluation for different cloud users based on our G-Cloud platform. It shows the dynamic security scanning score for one or multiple clouds with visual graphs and guided users to modify configuration, improve operation and repair vulnerabilities, so as to improve the security of their cloud resources.

URLhttps://ieeexplore.ieee.org/document/8530839
DOI10.1109/CBD.2018.00043
Citation Keysun_one_2018