学术文献库

The financial crisis made companies around the world search for cheaper and more efficient solutions to cover their needs in terms of computational power and storage. Their quest came to end with the birth of Cloud Computing infrastructures. However, along with the new promising technology, new attack vectors were born, and one old and known threat, that of Malicious Insiders reappeared. Insiders can use their privileged position inside the Cloud infrastructure to accomplish or help in attacks against a Cloud infrastructure. In this paper, we propose a practical and efficient intrusion detection system solution for Cloud infrastructures based on Graphical Processing Unit (GPU) acceleration. Our solution monitors the deployed virtual machines' operations and especially those of the host Operating System, known as Dom0, correlating the collected information to detect uncommon behavior based on the Smith-Waterman algorithm. Our proposal makes possible the cooperation of a variety of known hypervisors along with every known GPU acceleration unit used, thus offering the maximum of security mechanics while at the same time minimizing the imposed overhead in terms of Central Processing Unit (CPU) usage.