عنوان انگلیسی مقاله:
Big Data Based Security Analytics for Protecting Virtualized Infrastructures in Cloud Computing
ترجمه فارسی عنوان مقاله:
تحلیل امنیتی بر اساس داده های بزرگ برای حفاظت زیرساخت های مجازی شده در محاسبات ابری
IEEE - IEEE TRANSACTIONS ON BIG DATA, VOL: 4, NO: 1, JANUARY-MARCH 2018
Thu Yein Win، Huaglory Tianfield, and Quentin Mair
Virtualized infrastructure in cloud computing has become an attractive target for cyberattackers to launch advanced attacks.
This paper proposes a novel big data based security analytics approach to detecting advanced attacks in virtualized infrastructures.
Network logs as well as user application logs collected periodically from the guest virtual machines (VMs) are stored in the Hadoop
Distributed File System (HDFS). Then, extraction of attack features is performed through graph-based event correlation and
MapReduce parser based identification of potential attack paths. Next, determination of attack presence is performed through two-step
machine learning, namely logistic regression is applied to calculate attack’s conditional probabilities with respect to the attributes, and
belief propagation is applied to calculate the belief in existence of an attack based on them. Experiments are conducted to evaluate the
proposed approach using well-known malware as well as in comparison with existing security techniques for virtualized infrastructure.
The results show that our proposed approach is effective in detecting attacks with minimal performance overhead.
Index Terms: Virtualized infrastructure, virtualization security, cloud security, malware detection, rootkit detection, security analytics, event correlation, logistic regression, belief propagation