Visible to the public Biblio

Filters: Keyword is multiple clouds  [Clear All Filters]
2020-03-18
Zhang, Ruipeng, Xu, Chen, Xie, Mengjun.  2019.  Powering Hands-on Cybersecurity Practices with Cloud Computing. 2019 IEEE 27th International Conference on Network Protocols (ICNP). :1–2.
Cybersecurity education and training have gained increasing attention in all sectors due to the prevalence and quick evolution of cyberattacks. A variety of platforms and systems have been proposed and developed to accommodate the growing needs of hands-on cybersecurity practice. However, those systems are either lacking sufficient flexibility (e.g., tied to a specific virtual computing service provider, little customization support) or difficult to scale. In this work, we present a cloud-based platform named EZSetup for hands-on cybersecurity practice at scale and our experience of using it in class. EZSetup is customizable and cloud-agnostic. Users can create labs through an intuitive Web interface and deploy them onto one or multiple clouds. We have used NSF funded Chameleon cloud and our private OpenStack cloud to develop, test and deploy EZSetup. We have developed 14 network and security labs using the tool and included six labs in an undergraduate network security course in spring 2019. Our survey results show that students have very positive feedback on using EZSetup and computing clouds for hands-on cybersecurity practice.
2019-02-14
Sun, A., Gao, G., Ji, T., Tu, X..  2018.  One Quantifiable Security Evaluation Model for Cloud Computing Platform. 2018 Sixth International Conference on Advanced Cloud and Big Data (CBD). :197-201.

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.