Biblio

The world is witnessing an exceptional expansion in the cloud enabled services which is further growing day by day due to advancement & requirement of technology. However, the identification of vulnerabilities & its exploitation in the cloud computing will always be the major challenge and concern for any cloud computing system. To understand the challenges and its consequences and further provide mitigation techniques for the vulnerabilities, the identification of cloud specific vulnerabilities needs to be examined first and after identification of vulnerabilities a detailed taxonomy must be positioned. In this paper several cloud specific identified vulnerabilities have been studied which is listed by the NVD, ENISA CSA etc accordingly a unified taxonomy for security vulnerabilities has been prepared. In this paper we proposed a comprehensive taxonomy for cloud specific vulnerabilities on the basis of several parameters like attack vector, CVSS score, complexity etc which will be further act as input for the analysis and mitigation of cloud vulnerabilities. Scheming of Taxonomy of vulnerabilities is an effective way for cloud administrators, cloud mangers, cloud consumers and other stakeholders for identifying, understanding and addressing security risks.

SCADA system is an essential component for automated control and monitoring in many of the Critical Infrastructures (CI). Cyber-attacks like Stuxnet, Aurora, Maroochy on SCADA systems give us clear insight about the damage a determined adversary can cause to any country's security, economy, and health-care systems. An in-depth analysis of these attacks can help in developing techniques to detect and prevent attacks. In this paper, we focus on the assessment of SCADA vulnerabilities from the widely used National Vulnerability Database (NVD) until May 2019. We analyzed the vulnerabilities based on severity, frequency, availability, integrity and confidentiality impact, and Common Weaknesses. The number of reported vulnerabilities are increasing yearly. Approximately 89% of the attacks are the network exploits severely impacting availability of these systems. About 19% of the weaknesses are due to buffer errors due to the use of insecure and legacy operating systems. We focus on finding the answer to four key questions that are required for developing new technologies for securing SCADA systems. We believe this is the first study of its kind which looks at correlating SCADA attacks with publicly available vulnerabilities. Our analysis can provide security researchers with useful insights into SCADA critical vulnerabilities and vulnerable components, which need attention. We also propose a domain-specific vulnerability scoring system for SCADA systems considering the interdependency of the various components.

The software supply chain is a source of cybersecurity risk for many commercial and government organizations. Public data may be used to inform automated tools for detecting software supply chain risk during continuous integration and deployment. We link data from the National Vulnerability Database (NVD) with open version control data for the open source project OpenSSL, a widely used secure networking library that made the news when a significant vulnerability, Heartbleed, was discovered in 2014. We apply the Alhazmi-Malaiya Logistic (AML) model for software vulnerability discovery to this case. This model predicts a sigmoid cumulative vulnerability discovery function over time. Some versions of OpenSSL do not conform to the predictions of the model because they contain a temporary plateau in the cumulative vulnerability discovery plot. This temporary plateau feature is an empirical signature of a security failure mode that may be useful in future studies of software supply chain risk.