Biblio

The explosive growth of IT infrastructures, cloud systems, and Internet of Things (IoT) have resulted in complex systems that are extremely difficult to secure and protect against cyberattacks which are growing exponentially in complexity and in number. Overcoming the cybersecurity challenges is even more complicated due to the lack of training and widely available cybersecurity environments to experiment with and evaluate new cybersecurity methods. The goal of our research is to address these challenges by exploiting cloud services. In this paper, we present the design, analysis, and evaluation of a cloud service that we refer to as Cybersecurity Lab as a Service (CLaaS) which offers virtual cybersecurity experiments that can be accessed from anywhere and from any device (desktop, laptop, tablet, smart mobile device, etc.) with Internet connectivity. In CLaaS, we exploit cloud computing systems and virtualization technologies to provide virtual cybersecurity experiments and hands-on experiences on how vulnerabilities are exploited to launch cyberattacks, how they can be removed, and how cyber resources and services can be hardened or better protected. We also present our experimental results and evaluation of CLaaS virtual cybersecurity experiments that have been used by graduate students taking our cybersecurity class as well as by high school students participating in GenCyber camps.

Cloud Computing is emerging as a new paradigm that aims delivering computing as a utility. For the cloud computing paradigm to be fully adopted and effectively used, it is critical that the security mechanisms are robust and resilient to faults and attacks. Securing cloud systems is extremely complex due to the many interdependent tasks such as application layer firewalls, alert monitoring and analysis, source code analysis, and user identity management. It is strongly believed that we cannot build cloud services that are immune to attacks. Resiliency to attacks is becoming an important approach to address cyber-attacks and mitigate their impacts. Resiliency for mission critical systems is demanded higher. In this paper, we present a methodology to develop an Autonomic Resilient Cloud Management (ARCM) based on moving target defense, cloud service Behavior Obfuscation (BO), and autonomic computing. By continuously and randomly changing the cloud execution environments and platform types, it will be difficult especially for insider attackers to figure out the current execution environment and their existing vulnerabilities, thus allowing the system to evade attacks. We show how to apply the ARCM to one class of applications, Map/Reduce, and evaluate its performance and overhead.