
Vulnerability assessments are best practices for computersecurity and requirements for regulatory compliance. Potentialand existing security holes can be identified during vulnerabilityassessments and security breaches could be averted. However, the unique nature of cloud computing environmentsrequires more dynamic assessment techniques. The proliferationof cloud services and cloud-aware applications introduce morecloud vulnerabilities. But, current measures for identification, mitigation and prevention of cloud vulnerabilities do not suffice. Our investigations indicate a possible reason for this inefficiencyto lapses in availability of precise, cloud vulnerability information. We observed also that most research efforts in the context of cloud vulnerability concentrate on IaaS, leaving other cloud models largely unattended. Similarly, most cloud assessment efforts tackle general cloud vulnerabilities rather than cloud specific vulnerabilities. Yet, mitigating cloud specific vulnerabilities is important for cloud security. Hence, this paper proposes a new approach that addresses the mentioned issues by monitoring, acquiring and adapting publicly available cloud vulnerability information for effective vulnerability assessments. We correlate vulnerability information from public vulnerability databases and develop Network Vulnerability Tests for specific cloud vulnerabilities. We have implemented, evaluated and verified the suitability of our approach.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
