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.
翻译:金融危机让世界各地的公司寻找更便宜、更高效的解决方案,以满足其在计算能力和存储方面的需要。他们的追求随着云计算基础设施的诞生而告终。然而,随着新的有希望的技术的诞生,出现了新的攻击矢量,并出现了一个古老和已知的威胁,即恶意内鬼的威胁重新出现。内幕人员可以利用他们在云基础设施内的特权地位完成或帮助对云层基础设施的袭击。在本文件中,我们提议基于图形处理股加速的云层基础设施的实用而高效的入侵探测系统解决方案。我们的解决方案监测所部署的虚拟机器的运行,特别是主机操作系统(称为Dom0)的运行,将收集到的信息与基于史密斯-沃特曼算法的异常行为联系起来。我们的建议使得有可能与所有已知的GPU加速装置合作,从而提供最大限度的安全机械,同时最大限度地减少中央处理股使用的间接费用。